1999 EOS Reference

Handbook

A Guide to NASA’s

Earth Science Enterprise

and the

Earth Observing System

http://eos.nasa.gov/
1999 EOS Reference

Handbook

A Guide to NASA’s

Earth Science Enterprise

and the

Earth Observing System
Special thanks are extended to the EOS Principal Investigators and Team Leaders for

providing detailed information about their

respective instruments, and to the Principal

Investigators of the various Interdisciplinary

Science Investigations for descriptions of

their studies. In addition, members of the

EOS Project at the Goddard Space Flight

Center are recognized for their assistance in

verifying and enhancing the technical content of the document. Finally, appreciation

is extended to the international partners for

providing up-to-date specifications of the

instruments and platforms that are key elements of the International Earth Observing

Mission.

Support for production of this document,

provided by Winnie Humberson, William

Bandeen, Carl Gray, Hannelore Parrish and

Charlotte Griner, is gratefully acknowledged.

Acknowledgements

Editors

Michael D. King

Reynold Greenstone

Design and Production

Sterling Spangler

For Additional Copies:

EOS Project Science Office

Code 900

NASA/Goddard Space Flight Center

Greenbelt, MD 20771

Phone: (301) 441-4259

Internet: lmcgrier@pop900.gsfc.nasa.gov
Table of Contents

Preface 5

Earth Science Enterprise 7

The Earth Observing System 15

EOS Data and Information System (EOSDIS) 27

Data and Information Policy 37

Pathfinder Data Sets 45

Earth Science Information Partners and the

 Working Prototype-Federation 47

EOS Data Quality: Calibration and Validation 51

Education Programs 53

International Cooperation 57

Interagency Coordination 65

Mission Elements 71

EOS Instruments 89

EOS Interdisciplinary Science Investigations 157

Points-of-Contact 340

Acronyms and Abbreviations 354

Appendix 361

 1. Changes in Atmospheric Carbon Dioxide Concentration 7

 2. NASA’s Earth Science Enterprise 9

 3. Earth Science Mission Profile 20

 4. Earth Science Program and Flight Elements 21

 5. EOSDIS Architecture 30

 6. Geographic Distribution of EOSDIS DAACs 31

 7. Terra Payload 71

 8. U.S. and International Partner Earth Observing Missions 86-87

 9. EOS Program-Level Architecture 88

 1. ESE Phase I: NASA Contributions 10

 2. ESE Pre-EOS: Non-NASA Contributions 11

 3. EOS Era (First Series) Remote-Sensing Satellites 13-14

 4. EOS Program History 15

 5. EOS, NMP and ESSP Instrument Complement: Phase 1 22

 6. EOS and NMP Platform Instrument Counts and Data Rates 23

 7. Links to IPCC Areas of Uncertainty 24

 8. EOS Distributed Active Archive Centers 28

 9. Some of the Major Foreign Contributions to NASA’s Earth Science Enterprise 60

10. Some of the Major Satellite Missions in the

 International Earth Observing System 61-63

List of Figures

List of Tables
1999 EOS Reference Handbook Preface • 5

Preface

This 1999 edition of the Earth Observing System (EOS) Reference Handbook has

been prepared to present the latest status of this evolving program.

As will become clear through reading this Handbook, the Earth Science Enterprise

has adopted a more-flexible approach to planning new missions in the period following 2002. This has become possible, in part, through the funding of technology

development that supports more-efficient and cost-effective instrument implementation that shortens mission development cycles.

A special feature of this edition is the addition of the descriptions of new Interdisciplinary Science Investigations (IDS) that have been added to the EOS Program since

the 1995 edition was published. The new investigations will significantly broaden the

scope of the science that has been the province of the original IDS Investigations from

the very beginnings of EOS. IDS Investigations have the special function of performing the scientific analyses that will benefit from the vast array of remote-sensing data

that are now becoming available from various sources. The investigations are developing and applying the skills needed to take advantage of data from the highly sophisticated instruments that will be launched onboard EOS satellite platforms and onboard

the complementary satellite platforms from the international community.

Functioning in an interactive mode, the various IDS investigations are testing the

capabilities of NASA’s new Earth Observing System Data and Information System

(EOSDIS). Prior to launch of the first EOS spacecraft in 1999, they are using early

versions of EOSDIS to perform their scientific studies. Their experiences in using the

system now permit them to feed back suggestions for improvement to the EOSDIS

developers.

The scientific investigations associated with EOS instruments play a major role in

supporting overall EOS science objectives. The geophysical parameters that are

supplied to the interdisciplinary investigations as EOS instrument products are themselves the products of considerable research by members of the many EOS instrument

teams. Research by the instrument team members makes possible the conversion of

instrument signals to the geophysical parameters that are then used by the interdisciplinary investigators as well as instrument investigators in their work. The instrument

team members not only provide the geophysical parameters (standard instrument

products), but also participate in the field experiments and mathematical analyses

required to provide the necessary assurances of the validity of the data. They also

conduct inter-instrument investigations that are the basis for multi-sensor products that

would not be available from instruments flying alone.

An electronic version of this Handbook is available online at:

http://eos.nasa.gov/eos_homepage/misc_html/refbook.html.

I hope you will find this document informative as well as useful. I will be glad to

respond to any comments or questions you may have.

Michael D. King

EOS Senior Project Scientist
1999 EOS Reference Handbook Earth Science Enterprise • 7

Earth Science Enterprise

Background

In the next century, planet Earth faces the potential hazard

of rapid environmental changes, including climate

warming, rising sea level, deforestation, desertification,

atmospheric ozone depletion, acid rain, and reduction in

biodiversity. Such changes would have a profound impact

on all nations, yet many important scientific questions

remain unanswered. For example, while most scientists

agree that global warming is likely, its magnitude

and timing (especially at the regional level) are

quite uncertain. Additional information on the

rate, causes, and effects of global change is

essential to develop the understanding needed to

cope with it. The National Aeronautics and Space

Administration (NASA) is working with the

national and international scientific communities

to establish a sound scientific basis for addressing

these issues through research efforts coordinated

under the U.S. Global Change Research Program

(USGCRP), the International GeosphereBiosphere Program (IGBP), and the World

Climate Research Program (WCRP).

Scientific research shows that the Earth has

changed over time and continues to change.

Human activity has altered the condition of the

Earth by reconfiguring the landscape, by

changing the composition of the global

atmosphere, and by stressing the biosphere in

countless ways. There are strong indications that

natural change is being accelerated by human

intervention. In its quest for improved quality of

life, humanity has become a force for change on

the planet, building upon, reshaping, and

modifying nature—often in unintended ways.

The byproducts of human activities, such as carbon

dioxide, methane, nitrous oxide, and other gases, trap heat

emitted from the Earth’s surface, thus potentially warming

the global atmosphere. Measurements over the past several

decades have documented a rapid rise in concentrations

of these greenhouse gases (e.g., Figure 1). Changes in

other variables, such as global cloudiness, concentration

of atmospheric dust particles, sea-ice concentrations, and

ocean circulation patterns, also have an impact on Earth’s

climate. The existing space-based systems for global

1960 1970 1990

310

320

330

340

350

360

370

Year

ppmv

CO2

monitoring lack the spatial, temporal, and spectral

coverage needed to provide observations of the accuracy

and precision desired to interpret the interactions among

these variables and their individual and combined

contributions to global climate. Furthermore, current

modeling of these interactive processes does not represent

them with sufficient accuracy to generate reliable

predictions of the magnitude and timing of global climate

change.

Only through systematic, comprehensive research can

scientists further knowledge of Earth’s climate and its

variations, thereby providing guidance to policymakers,

who must balance the needs of constituents with the welfare of the planet and the species that inhabit it. The study

of ozone levels by the Upper Atmosphere Research Program (UARP) illustrates how Earth science research yields

a clear picture of human-induced global change. In the

1970s, scientists first proposed the chemical processes by

which human-made chlorofluorocarbons (CFCs) deplete

stratospheric ozone. After a long-term research program

Figure 1. Atmospheric carbon dioxide monthly mean mixing ratios as observed

by Tans and Keeling at Mauna Loa, Hawaii. Data prior to May 1974 are from the

Scripps Institution of Oceanography, and data since May 1974 are from the

National Oceanic and Atmospheric Administration (NOAA).

1980
8 • Earth Science Enterprise 1999 EOS Reference Handbook

based on in situ and space-based observations, the international scientific community reached a consensus on

global ozone depletion. The evidence and understanding

gained from this research led to the 1987 Montreal Protocol for worldwide reduction in the production of CFCs.

Overview

The Earth Science Enterprise (ESE; Figure 2), formerly

called Mission to Planet Earth, is a NASA-initiated concept that uses space-, ground-, and aircraft-based measurement systems to provide the scientific basis for understanding the climate system and its variations. NASA’s

contributions to ESE include ongoing and near-term satellite missions, new missions under development, planned

future missions, management and analysis of satellite and

in situ data, and a continuing basic research program focused on process studies, modeling, and data analysis.

The space-based components of ESE will provide a constellation of satellites to monitor the Earth from space.

Sustained observations will allow researchers to monitor

Earth’s climate variables over time to determine trends;

however, space-based monitoring alone is not sufficient.

A comprehensive data and information system, a community of scientists performing research with the data

acquired, and extensive ground and airborne campaigns

are all important components. More than any other factor, the commitment to make Earth science data easily

available to the research community proves critical to

mission success.

Satellites operating in a variety of orbits form the

space component of ESE. No single orbit permits the gathering of complete information on Earth processes. For

example, the medium-inclination orbit of the Upper Atmosphere Research Satellite (UARS) was chosen specifically because of UARP focus on the processes influencing ozone depletion. High-inclination, polar-orbiting satellites are needed to observe phenomena that require relatively detailed observations on a routine basis, often from

a constant solar illumination angle. Geostationary satellites are needed to provide continuous monitoring of hightemporal-resolution processes; an international array of

these platforms now provides coverage on a near-global

basis. This coverage may be improved early in the next

century by geostationary satellites with advanced instrumentation planned by NASA and its international partners.

Science Objectives

ESE science objectives address the fundamental physical, chemical, and biological phenomena that govern and

integrate the Earth system. In pursuit of these overall objectives ESE has established five key science priority areas:

• Biology and biogeochemistry of ecosystems and the

global carbon cycle, including terrestrial ecology,

ocean biology and biogeochemistry, and land cover and

land use change.

• Global water and energy cycle, including atmospheric

circulation dynamics and thermodynamics, land surface processes and hydrology, clouds, aerosol and radiation in the Earth's climate, and atmospheric fourdimensional data assimilation.

• Climate variability and prediction, including radiative

forcing factors, global ocean circulation and sea-ice,

ice sheets and glaciers, and global modeling.

• Atmospheric chemistry, including atmospheric composition and ozone research.

• Solid Earth science, including space geodesy and the

international terrestrial reference frame, gravity field,

magnetic field, and global geology.

These five science priority areas are in general accord

with the four environmental science issues that have been

defined by the USGCRP as discussed below. A notable

exception is the addition of “Solid Earth science, including natural hazards research and applications” to the list.

ESE observations will permit assessment of various Earth

system processes, including the following:

• Hydrologic processes that govern the interactions of

land and ocean surfaces with the atmosphere through

the transport of heat, moisture, and momentum;

• Biogeochemical processes that contribute to the formation, dissipation, and transport of trace gases and

aerosols, and their global distributions;

• Atmospheric processes that control the formation, dissipation, and distribution of clouds and aerosols and

their interactions with solar radiation;

• Ecological processes that are affected by and/or will

affect global change, and their response to such changes

through adaptation; and

• Geophysical processes that have shaped or continue

to modify the surface of the Earth through tectonics,

volcanism, and the melting of glaciers and sea ice.

The goal of ESE is to advance scientific understanding

of the entire Earth system by developing a deeper comprehension of the components of that system and the interactions among them. To quantify changes in the Earth
1999 EOS Reference Handbook Earth Science Enterprise • 9 — Laboratory — Ground — Sea — Balloon — Aircraft — etc. — UARS — TOMS — SeaWiFS — etc. — VCL — GRACE — PICASSO-CENA — CloudSat — etc. — Interagency (i.e., NOAA/NPOESS) — International (e.g., IGOS, IEOS) — Inter-enterprise Coordin- ation (e.g., STS, ISS, ELVs) — Biennial Reviews — R&A — Program Scientists — IDS Mgmt. — Airborne Sci. Off. — CENR, USGCRP, ESSAAC, etc. — International Science Cooperation — Education — Public Comm. — Workshops — Data Policy Coord. — Natural Hazards — etc. — EO-1 ALI — etc. — Instr. Sci. Teams — IDS — Science Community — EOSDIS — Pathfinder Data sets — etc. — Facility — PI (EOS supported by other ESE elements) — Landsat 7 — Terra — PM — ICESat — CHEM — etc. NASA Earth Science Enterprise (ESE) Earth Observing System (EOS) Instruments Calibration/ Validation Data Science Spacecraft NMP Business Program Planning & Coordination Other Satellite Programs ESSP Research Applications & Outreach Agency-level Council Membership White House Initiatives IPO Responsibilities Strategic Planning Domestic & International Commitments Figure 2. NASA’s Earth Science Enterprise
10 • Earth Science Enterprise 1999 EOS Reference Handbook

system, ESE’s principal element, the Earth Observing

System (EOS), will provide systematic, continuous observations from low Earth orbit for a minimum of 15 years.

EOS broad mission objectives in support of this goal are

to:

• Create an integrated scientific observing system that

will enable multidisciplinary study of the Earth’s critical, life-enabling, interrelated processes involving the

atmosphere, oceans, ice, and land surfaces, and the dynamic and energetic interactions among them.

• Develop a comprehensive data and information system,

including a data retrieval and processing system, to

serve the needs of scientists contributing to an integrated, multidisciplinary study of planet Earth.

• Support the overall USGCRP by acquiring and assembling a global database of remote-sensing measurements

from space; priorities for acquiring these data will conform to the four priority environmental science issues

identified by the USGCRP as key to understanding global climate change, including:

1) Understanding the Earth’s Climate System, with a

focus on improving our understanding of the climate

system as a whole, rather than focusing on its individual components, and thus improving our ability

to predict climate change and variability.

2) Biology and Biogeochemistry of Ecosystems, with a

focus on improving understanding of the relationship

between a changing biosphere and a changing climate and the impacts of global change on managed

and natural ecosystems.

NASA Satellites/Instruments

(Launch Status)

ERBS (Operational)

Earth Radiation Budget Satellite

UARS (Operational)

Upper Atmosphere Research Satellite

NASA Spacelab Series

TOPEX/Poseidon (Operational)

Ocean Topography Experiment

SeaWiFS/OrbView-2 (Operational)

Sea-viewing Wide Field-of-view Sensor

TOMS/Earth Probe 96 (Operational)

Total Ozone Mapping Spectrometer

NSCAT/ADEOS (1996-1997)

NASA Scatterometer

TOMS/ADEOS (1996-1997)

Total Ozone Mapping Spectrometer

TRMM (Operational)

Tropical Rainfall Measuring Mission

Mission Objectives

Earth radiation budget, aerosol, and ozone data

from 57° inclination orbit

Stratospheric and mesospheric chemistry and

dynamic processes

A series of Shuttle-based experiments to

measure atmospheric and solar dynamics

(ATLAS), atmospheric aerosols (LITE), and

surface radar backscatter, polarization, and

phase information (SIR-C and X-SAR—joint with

Germany and Italy)

Ocean circulation (joint with France)

Purchase of ocean color data to monitor ocean

productivity

Ozone mapping and monitoring

Ocean surface wind vectors (joint with Japan)

Ozone mapping and monitoring (joint with Japan)

Precipitation, clouds, lightning, and radiation

processes over tropical regions (joint with Japan)

Table 1. ESE Phase I: NASA Contributions
1999 EOS Reference Handbook Earth Science Enterprise • 11

3) Composition and Chemistry of the Atmosphere, with

a focus on improving our understanding of the global-scale impacts of natural and human processes on

the chemical composition of the atmosphere and determining the effect of such changes on air quality

and human health.

4) The Global Water Cycle, with a focus on improving

our understanding of the movement of water through

the land, atmosphere, and ocean, and on how global

change may increase or decrease regional water availability.

Pre-EOS: 1990 - 1998

Table 1 delineates NASA’s contributions to Phase I of

ESE (the period of Earth observations preceding the

launch of NASA’s first EOS satellites in 1999). Table 2

identifies other U.S. and international Earth observation

satellites that will be in place during this period.

EOS First Series: 1999-2003

The Earth Observing System—consisting of a science

segment, a data system, and a space segment made up of

a series of polar-orbiting and low-inclination satellites for

long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans—is the centerpiece of ESE. In concert with EOS, the polar-orbiting

and mid-inclination platforms from Europe, Japan, and

the U.S. National Oceanic and Atmospheric AdministraNon-NASA Satellites/Instruments

(Launch Status)

Table 2. ESE Pre-EOS: Non-NASA Contributions

POES (U.S. - Operational)

NOAA Polar-orbiting Operational

Environmental Satellites

Landsat 5 (U.S. - Operational)

Land Remote Sensing Satellite

DMSP (U.S. - Operational)

Defense Meteorological Satellite Program

ERS-1 (ESA - On standby since June

1996)

European Remote-Sensing Satellite

JERS-1 (Japan - 1992-1998)

Japan’s Earth Resources Satellite

ERS-2 (ESA - Operational)

European Remote-Sensing Satellite

Radarsat-1 (Canada - Operational)

Radar Satellite

ADEOS (Japan, 1996-1997)

Advanced Earth Observing Satellite

Mission Objectives

Earth’s surface and atmosphere visible and

radiance/reflectance, infrared atmospheric

sounding, and ozone measurements; space

environmental monitoring

High spatial resolution visible and infrared

radiance/reflectance and terrestrial surfaces

Visible, infrared, and passive microwave

atmospheric and surface measurements

C-band SAR, microwave altimeter, scatterometer,

and sea surface temperature

L-band SAR backscatter and high spatial

resolution surface visible and infrared radiance/

reflectance

Same as ERS-1, plus ozone mapping and

monitoring

C-band SAR measurements of Earth’s surface

(joint U.S./Canadian mission)

Surface visible and near-infrared radiance/

reflectance scatterometry, and tropospheric and

stratospheric chemistry (joint with Japan)
12 • Earth Science Enterprise 1999 EOS Reference Handbook

tion (NOAA) form the basis for a comprehensive International Earth Observing System (IEOS). NASA, Japan,

and the European Space Agency (ESA) programs will

establish an international Earth-observing capability that

will operate for at least 15 years. IEOS will allow scientists to obtain information at many levels of detail, covering all major Earth system processes.

Tables 3a and 3b identify the NASA, other U.S., and

international contributions of Earth observing satellites

during the EOS First Series period. Additional details on

these satellites are presented in the Mission Elements section of this Handbook. EOS satellites will carry two classes

of instruments: Facility Instruments supplied by NASA

in response to general mission requirements, and Principal Investigator (PI) Instruments selected through a competitive process and aimed at the focused research interests of the selected investigators. Of course, the PI Instruments are also responsive to overall EOS objectives.

The EOS Instruments section provides details on the science to be accomplished and the high-level engineering

specifications for the instruments now included in the EOS

Program.

The EOS Program has a number of major elements

other than the EOS spacecraft and instruments. These essential elements—the EOS Data and Information System

(EOSDIS), interdisciplinary science research, calibration

and validation, education, and international cooperation—

receive coverage later in this Handbook.

The data collection segment of ESE—EOS, Pathfinders, geostationary satellites, and aircraft- and ground-based

programs—will provide the comprehensive global observations necessary to understand how the processes that

govern global change interact as part of the Earth system.

Through this refined knowledge, models will be developed to help predict future environmental change on local, regional, and global scales. For those who make observations of the Earth system and develop models of its

operation, Earth system science involves the creation of

interdisciplinary models that couple elements from formerly disparate sciences, such as terrestrial ecology and

meteorology.

EOS Follow-on (Post 2003)

NASA’s long-range planning calls for continuation of ESE

beyond 2003. Plans include a new generation of satellites

in geostationary orbit and additional small Pathfinder satellites addressing specific Earth science investigations.

NASA also has initiated a technology program for developing a new generation of sensor technologies. These technologies will eventually migrate into future EOS flight

programs. Of course, the data system aspects of ESE will

continue throughout and beyond the lifetime of the EOS

mission.

Several mission categories have been identified to

provide critical Earth science measurements not provided

by the currently scheduled international constellation of

satellites. NASA intends to pursue collaborations with domestic and/or international partners in the following disciplines: Gravity and magnetic fields, solid-Earth topography, and ocean topography. Specific instruments and

platforms have yet to be identified for these missions.

Additional Earth System Science Pathfinder (ESSP) and

New Millennium Program (NMP) missions will be

launched as particular observations are requested by the

national and international science community, or as data

gaps develop. The main driver behind this program is to

provide focused missions in a faster, better, and cheaper

manner, alleviating lengthy procurements. These smallto-moderate-sized satellites will have highly focused objectives and obtain measurements that are not provided

by EOS or other instrument suites. NASA is currently

examining alternative strategies for implementation of the

second EOS missions, with some missions focused on

long-term monitoring of key data sets initiated by the first

series, some focused on process studies to improve our

understanding of focused Earth system processes and

some aimed at demonstrating operational capability.

Emphasis will be on small satellite technology whenever

appropriate.

EOS missions will provide high-spatial-resolution

global information. The various orbits of these spacebased elements of ESE will give Earth scientists a comprehensive, cohesive set of observations—providing a

wide range of scales—on Earth system processes.

Contribution to the U.S. Global Change Research

Program

ESE is NASA’s contribution to the U.S. Global Change

Research Program (USGCRP), which is the focal point

of U.S. activities in support of the worldwide research

collaboration now underway to study global change.

USGCRP coordinates the efforts of numerous participating Federal agencies under the guidance of the Committee on the Environment and Natural Resources (CENR),

itself one of nine standing research and development coordinating subcommittees under the National Science and

Technology Council, which was established in November 1993 (see section on Interagency Coordination).

CENR has acknowledged the absolute necessity of

the remote sensing from space of certain key Earth system variables, and reaffirmed the science strategy that had

earlier been put forth by its predecessor organization, the

Committee on Earth and Environmental Sciences (CEES).

Thus, CENR, and thereby the National Science and Technology Council, affirm the relevance of ESE to national

policy relating to global change.

The ESE science contributions can be viewed for convenience as a means of obtaining global measurements

(with appropriate characteristics) of the 24 Earth system

variables in the Appendix on page 361.
1999 EOS Reference Handbook Earth Science Enterprise • 13

References

NASA, 1998: Earth Science Strategic Enterprise Plan,

1998-2002. NASA Headquarters, Code YS, 300 E Street,

SW, Washington, DC 20546.

NASA 1999: ESE Science Implementation Plan, October

1999. NASA Headquarters, Code YS, 300 E Street, SW,

Washington, DC 20546.

Our Changing Planet—the FY 2000 U.S. Global Change

Research Program, a report by CENR. This publication

Satellites

(Launch Status)

QuikScat (1999)

SeaWinds Scatterometer

Landsat 7 (1999)

Land Remote-Sensing Satellite

Terra (1999)

Earth Observing System

Morning Crossing (Descending)

ACRIMSAT (1999)

Advanced Cavity Radiometer Irradiance

Monitor Satellite

NMP/EO-1 (1999)

First Earth science technology mission

METEOR 3M-1 (Russia - 2000)

Stratospheric Aerosol and Gas

Experiment III

Jason-1 (2000)

EOS Ocean Altimetry Mission

ENVISAT Series (ESA - 2000)

Environmental Satellite

ADEOS II (Japan - 2000)

Advanced Earth Observing Satellite II

Mission Objectives

Ocean surface wind vectors

High-spatial-resolution visible and infrared radiance/

reflectance to monitor land surface (joint with USGS)

Clouds, aerosols, and radiation balance,

characterization of the terrestrial ecosystem; land use,

soils, terrestrial energy/moisture, tropospheric

chemical composition; contribution of volcanoes to

climate, and ocean primary productivity (includes

Canadian and Japanese instruments)

Total solar irradiance

Provide paired scene comparisons between EO-1

Advanced Land Imager (ALI) and Landsat 7 Enhanced

Thematic Mapper Plus (ETM+)

Retrieve global profiles of atmospheric aerosols,

ozone, water vapor, other trace gases, temperature

and pressure in the mesosphere, stratosphere, and

troposphere

Ocean circulation (joint with France)

Environmental studies in atmospheric chemistry and

marine biology and continuation of ERS mission

objectives

Visible-to-thermal-infrared radiance/reflectance,

microwave imaging, scatterometry, ozone, aerosols,

atmospheric temperature, winds, water vapor, SST,

energy budget, clouds, snow and ice, ocean current,

ocean color/biology (includes French and U.S.

instruments)

Table 3a. EOS Era (First Series) Remote-Sensing Satellites

outlines all of the U.S. Federal Government activities

consisting of both ground- and space-based efforts in research, data-gathering, and modeling activities, as well

as economic research, with near- and long-term scientific

and public policy benefits. Budgets are presented by

agency and by scientific element. This publication is published annually.

Earth Science Enterprise URL

http://www.earth.nasa.gov/
14 • Earth Science Enterprise 1999 EOS Reference Handbook

Satellites

(Launch Status)

ESSP/VCL (2000)

First Earth System Science Pathfinder

mission

EOS PM (2000)

Earth Observing System

Afternoon Crossing (Ascending)

ESSP/GRACE (2001)

Second Earth System Science Pathfinder

mission

ICESat (2001)

EOS Ice-Sheet Altimetry Mission

ALOS (Japan - 2001)

Advanced Land Observational Satellite

SORCE (2002)

Solar Radiation and Climate Experiment

EOS CHEM (2002)

EOS Chemistry Mission

Space Station-SAGE III (2003)

International Space Station

ESSP/PICASSO-CENA (2003)

Third Earth System Science Pathfinder

mission

ESSP/CloudSat (2003)

Fourth Earth System Science Pathfinder

mission

METOP Series (EUMETSAT/ESA - 2003)

Meteorological Operational Satellite

ATMOS Series (Japan and NASA -

Proposed for 2003)

Precipitation Mission

Mission Objectives

Measure heights of the vegetation canopy

Atmospheric temperature and humidity; clouds,

precipitation, and radiative balance; characterization

of terrestrial and oceanic processes including

productivity; air-sea fluxes of energy and moisture;

and sea-ice and snow-cover extents (includes

Brazilian and Japanese instruments)

Measure Earth’s gravity field

Ice sheet mass balance and cloud-top and landsurface topography and vertical profiles of aerosol and

cloud properties

Land surface, cartography, and disaster monitoring

Total and spectral solar irradiance

Atmospheric chemical composition; troposphericstratospheric exchange of energy and chemicals;

chemistry-climate interactions; air quality (includes

joint Netherlands/Finland and joint U.K./U.S.

instruments)

Mid-inclination, low-altitude flight of SAGE III for

measuring atmospheric aerosols, ozone, water vapor,

other trace gases, temperature and pressure in the

mesosphere, stratosphere, and troposphere

Vertical distribution of clouds and aerosols (joint with

France)

Increase the understanding of the role of optically

thick clouds on the Earth’s radiation budget (joint with

Canada)

Operational meteorology and climate monitoring, with

the future objective of operational climatology (joint

with NOAA)

Precipitation and related variables and Earth radiation

budget in middle and higher latitudes; also trace gases

Table 3b. EOS Era (First Series) Remote-Sensing Satellites
1999 EOS Reference Handbook The Earth Observing System • 15

The Earth Observing System

Planning for the EOS mission began in the early 1980s,

and an Announcement of Opportunity (AO) for the selection of instruments and science teams was issued in 1988.

458 proposals were received in response to the AO. Early

in 1990, NASA announced the selection of 30 instruments

to be developed for EOS, along with their science teams;

29 Interdisciplinary Science Investigation teams were also

selected at that time.

EOS was recognized in 1990 as part of the Presidential initiative, Mission to Planet Earth (now called the Earth

Science Enterprise), receiving its “new start” from Congress in October. The EOS Program was funded under a

continuing resolution, and ramped up to its full funding

with the approval of the FY 91 budget in January 1991.

At that time, plans called for the instruments to be divided into three groups—those on the EOS-A and EOSB series spacecraft, and those for flight as attached payloads on Space Station Freedom. Instrument selections

were also made for the proposed Japanese and European

polar-orbiting satellites, then referred to as the Japanese

Polar-Orbiting Platform (JPOP) and the European PolarOrbiting Platform (EPOP). A NASA research announcement (NRA) for the selection of new investigations, instrument teams, and young investigators was issued in

1995. 309 proposals were received in response to the

NRA. On July 1, 1996, NASA announced the selection

of team members for 5 instrument teams, including

Landsat 7, 31 Interdisciplinary Science Investigation

Teams, and 21 New Investigators. Table 4 provides the

major milestones of the EOS Program to date.

EOS Science Objectives

The overarching goal of the EOS Program is to determine the extent, causes, and regional consequences of

global climate change. The extent (e.g., the change in average temperature and the time scale over which it will

occur) is presently unknown. Causes can be either natural or human-induced. Both must be understood to determine how to alter human behavior appropriately to avoid

climate changes that prove most detrimental to the environment. The regional consequences (e.g., changes in precipitation patterns, length of growing seasons, severity of

storms, change of sea level) must be understood to determine which aspects of climate change are most harmful,

and how to adapt to those changes that the human species

cannot avoid.

The EOS Investigators Working Group (IWG) defined the following science and policy priorities for EOS

observations, based on scientific recommendations by national and international programs such as the Intergovernmental Panel on Climate Change (IPCC) and the Committee on Earth and Environmental Sciences (CEES)/

Table 4. EOS Progam History

Mission Planning 1982-87

Announcement of Opportunity 1988

Peer Review Process 1988-89

Letter Review (Academia/Government)

Panel Review (Academia/Government)

Prioritization Panel (Academia/Government)

Definition Phase 1989-90

Announcement of Selection 1990

New Start 1990

Execution Phase 1990 on

Restructuring Process 1991-92

Restructuring Confirmation 1992

Rescoping Process 1992

National Space Policy 1992

Directive 7

Rescoping Confirmation 1993

Rebaselining 1994

Reshaping 1995

NASA Research Announcement 1995

Landsat 7 Team

Augmentation to MODIS, AIRS, AMSR

 Teams

Interdisclipinary Science Teams

Young Investigators

Peer Review Process 1995-96

First Biennial Review 1997

NASA Research Announcement 1997

Jason-1 Science Team

Terra/SAGE III Validation Program

Peer Review Process 1997-98
16 • The Earth Observing System 1999 EOS Reference Handbook

Committee on the Environment and Natural Resources

Research (CENR):

1) Clouds and Radiation

Cloud formation, dissipation, and radiative properties,

which influence response of the atmosphere to greenhouse forcing.

Large-scale hydrology and moisture processes, including precipitation and evaporation.

2) Oceans

Exchange of energy, water, and chemicals between the

ocean and atmosphere, and between the upper layers

of the ocean and deep ocean (includes sea ice and formation of bottom water).

3) Greenhouse Gases

Links to the hydrologic cycle and ecosystems, transformations of greenhouse gases in the atmosphere, and

interactions inducing climate change.

4) Land Surface Hydrology and Ecosystem Processes

Improved estimates of runoff over the land surface

and into the oceans, sources and sinks of greenhouse

gases, exchange of moisture and energy between the

land surface and atmosphere, and changes in land

cover.

5) Glaciers and Polar Ice Sheets

Predictions of sea-level change and global water balance.

6) Ozone and Stratospheric Chemistry

Chemical reactions, solar-atmosphere relations, and

sources and sinks of radiatively important gases.

7) Solid Earth

Volcanoes and their role in climatic change.

The IWG—which includes all selected Interdisciplinary

Science Investigation Principal Investigators (PIs) and CoInvestigators (Co-PIs), Instrument Investigators and CoInvestigators, and Facility Instrument Team Leaders and

Team Members—establishes EOS science objectives in

coordination with the national and international Earth

science community.

The IWG and the following Panels and Working

Groups provide NASA with recommendations related to

the design and implementation of all elements of EOS:

Science Panels

Atmospheres

Biogeochemical Cycles

Land

Oceans

Physical Climate and Hydrology

Functional Panels

EOSDIS

Payload

Working Groups

SWAMP [Science Working Group for the AM (Terra)

Platform]

PM Working Group

Cryosphere Working Group

Chemistry Working Group

The EOS Program provides resources to support the scientific research required to turn satellite measurements

into science data products for inclusion in, or comparison with, model results; specifically, EOS supports scientific investigations through its Interdisciplinary Science Investigations and Instrument Teams.

EOS Interdisciplinary Science Investigations are scientific studies selected through a competitive process to

develop and refine integrated Earth system models, which

will use EOS instrument observations to help in understanding the Earth as a system (see the EOS Interdisciplinary Science Investigations section for details on the

studies chosen as part of the EOS Program).

NASA issues NRAs every two-to-three years to allow broader participation in the EOS Program by members of the Earth science community.

EOS Instrument Teams, also selected through a competitive process, help define the scientific requirements

for their respective instruments, and generate the algorithms that will be used to process the data into useful

data products. (See the Algorithm Theoretical Basis

Documents [ATBDs] on the World Wide Web for an indepth presentation of the algorithms. Each ATBD may

be downloaded at http://eos.nasa.gov/atbd/pg1.html).

In 1995 NASA solicited new investigations in support of other EOS facility instruments such as AIRS, MODIS, and AMSR-E. It is envisioned that this opportunity

will be renewed once every two-to-three years to allow

broader participation in the EOS Program by members

of the Earth science community. NASA has also formed

new Science Teams for the Landsat 7 and Jason-1 missions, and will form the OMI facility instrument team in

1999.

EOS investigations are intended to characterize the

Earth system as an integrated whole, while also quantifying the regional processes that govern it. Research will

be based initially on the existing sources of ground- and

space-based observations (see Pathfinder Data Sets section) and will continue through and beyond the launch of

the EOS satellites. Efforts to understand these Earth system elements will shed light on how the Earth functions

as a coupled and integrated system, how it responds to

human-induced perturbations, and how this response

manifests itself as global climate change.

Discussion of the different types of products to be

made available as EOSDIS evolves to a full operational
1999 EOS Reference Handbook The Earth Observing System • 17

capability is included in the EOS Data and Information

System section of this Handbook.

The EOS Program has undergone major revisions

since the last edition of this Handbook was published in

1995. The following subsection provides, in bullet form,

an overview of the successive reconfigurations of the program, which resulted initially from a Congressional mandate and Executive Branch requirements to reduce substantially the budget through 2000. The Pathfinder Data

Sets section is intended to inform readers of what is being done now to further global change research. A section

on Interagency Coordination presents the roles played by

other Federal agencies, in cooperation with NASA, to

make and analyze observations of the Earth. The Mission

Elements section provides details of the international instrument suites that constitute the International Earth Observing System (IEOS). This section provides as comprehensive and up-to-date coverage as possible, given the

transient nature of payload configurations imposed by constrained national budgets the world over. This section and

the EOS Instruments section describe the current Earth

remote-sensing satellite scenario and the instrumentation

that will yield the observations needed to further global

change research.

The section on EOS Interdisciplinary Science Investigations gives a broad picture of the many science investigations that are in place to perform Earth System Science, taking particular advantage of the unprecedented

flow of Earth observations to be provided from a variety

of sources.

The original extensive discussion going from the Restructuring Process through the Rebaselining Process

(pages 14-23 of the 1995 Reference Handbook) has been

deleted in this version. This material is replaced by the

“bulleted” material that follows. In addition there is new

bulleted material relating to the Reshape Study and the

Biennial Review of 1997.

EOS Program Revisions

Starting in 1991 there has been a series of major revisions of the EOS Program, generally prompted by the need

for substantial budget reductions. Key elements of each

of these program revisions are presented in outline form

in the subsections that follow. The successive revisions

have been dubbed, “The Restructuring Process,” “The

Rescoping Process,” “The Rebaselining Process,” and

“The Reshape Process.” Further revisions of the EOS

Program are occurring as a consequence of recommendations that were made in the first “Biennial Review” of

ESE.

The Restructuring Process (1991)

Directed by the U.S. Congressional Committee on Appropriations

Purpose:

• focus on global climate change

• obtain flexibility by flying on multiple smaller platforms

• reduce EOS cost from $17 billion to $11 billion through

FY 2000

Guiding Principles:

• ensure continuity of observations for 15 years

• prioritize policy-relevant science questions

• identify instruments whose measurements can be met

by other programs

• deselect instruments as appropriate

Outcome:

• restructured program approved by U.S. Congress

(March 1992) and formally endorsed by the National

Space Council in National Space Policy Directive 7

(NSPD 7, June 1992)

• 17 instruments to fly before 2002; six later

• 7 instruments deselected

• series of smaller expendable launch vehicles (ELVs)

adopted in lieu of Titan 4 class launch vehicle

• 6-month earlier launch of EOS AM spacecraft

• EOS AM* and EOS PM concept adopted, permitting

study of diurnal variations

• NSPD 7 stipulates that NASA coordinate production

of an interagency program plan entitled The SpaceBased Global Change Observation System (S-GCOS)

Program Plan to achieve integration of Earth remotesensing activities of NASA, DoE, and DoD

The Rescoping Process (1992)

Purpose:

• respond to U.S. Congress reduction in EOS decadal budget from $11 billion to $8 billion (budget established in

FY 1993 appropriations bill)

Guiding Principles:

• reduce program contingency funds

• preserve science requirements identified in restructuring process

• depend increasingly on international partners

Outcome:

• commitments to fly international instruments; June 1998

launch date for EOS AM-1 maintained

• common spacecraft to be developed for EOS PM,

CHEM, AM-2/AM-3; EOS AM-1 spacecraft unique

• HIRIS instrument eliminated

• number of at-launch data products decreased

• TOPEX/Poseidon follow-on replaced by mission based

on French instruments

• GGI instrument concept replaced by French DORIS instrument

* EOS AM (or EOS AM-1) has recently been renamed Terra.
18 • The Earth Observing System 1999 EOS Reference Handbook

• several flight of opportunity (FOO) instruments to be

included in CHEM series

• number of instruments to fly on EOS platforms reduced

to 22 (15 to fly before 2003)

The Rebaselining Process (1994)

Purpose:

• respond to administration budget request for FY 1995

representing approximately a 9% reduction in the EOS

budget compared to the rescoped ($8 billion) budget

approved only one year before.

Guiding Principles:

• maintain AM-1 launch date at June 1998

• make available elements of EOSDIS needed to support

AM-1 in June 1998 and TRMM in August 1997

• use common spacecraft as standard platform for at least

PM-1 and CHEM-1 missions

Outcome:

• six-year launch centers adopted for AM and PM series

• combined radar/laser altimeter mission rephased as two

separate missions; launch of laser mission slipped by

12 months

• move TES from AM-2 to CHEM-1

• remove ACRIM III, SAGE III, and SOLSTICE from

CHEM-1

• add Landsat 7 to EOS Program

• fly ETM+ type instrument on AM-2 (avoiding cost of

Landsat 8 launch and spacecraft)

• cancel EOS Color

• phase some of the processing and archiving of EOS

standard products

The Reshape Process (June 1995)

Purpose:

• respond to need to redefine NASA’s approach to accomplishing ESE objectives in the post-2000 era while

maintaining cost cap

Guiding Principles:

• EOS program to fit within a $1 billion annual cost cap

• EOS program to end in the year 2019

• NASA/NOAA cooperation to increase

• Some EOS missions to be designated “monitoring” and

others “process study” missions

• establish 24 EOS measurement-set concept

Outcome:

• advanced MODIS and advanced MISR will fly on

AM-2

• CHEM-2 mission will be split into a monitoring and a

process study mission

• new PM-2A mission will be designed to complement

the National Polar-orbiting Operational Environmental Satellite System (NPOESS) C-1 mission

• second series of EOS missions will incorporate advanced technology developments from the New Millennium Program (NMP)

• third series of EOS missions will be “continuity missions” and will also feature missions from NMP

The Biennial Review of ESE (1997)

Purpose:

• to institute regular assessments of the entire ESE, starting in 1997, with results in time to shape the development of the FY 1999 budget request

Guiding Principles:

• the scientific objectives of the Earth Observing System

remain the same; what is evolving is the strategy for

implementation and the integration of EOS with other

elements of ESE

• better capitalize on advances in science and technology and identify opportunities for new and expanded

collaborations with commercial, international, and interagency partners

• enable a fundamentally different and vastly more flexible means of planning and implementing Earth System Science missions

Outcome:

• Atmospheric Chemistry Review Panel established; recommended use of Common Spacecraft for CHEM-1

mission

• indefinite quantity, indefinite delivery or “catalog”

policy adopted for procurement of small commercial

spacecraft

• ICESat-1 mission spacecraft will be a “catalog” procurement with Geoscience Laser Altimeter System

(GLAS) instrument developed on parallel path; this approach leads to acceleration of mission by nine months

and cost saving of $30 million

EOSDIS Core System

• enhanced role and responsibilities established for the

Data Processing Resources Board

• EOSDIS Review Group (ERG) established; all satellite data to be processed to Level 1 with ramp up to

Level 2/3 in a pattern of 25-50-75-100% over the first

four years of EOS missions; production of interdependent data sets to be phased in over period of two years;

prototype EOSDIS Federation Experiment to proceed

as planned

Program Balance

• Research and Analysis (R & A) funding to be restored

to about FY 94 level as part of decision to improve

ESE program balance
1999 EOS Reference Handbook The Earth Observing System • 19

• responsibility and budget for validation activities moved

to Science Division at NASA Headquarters

• Science Implementation Plans are to be developed by

responsible teams as the basis for planning future ESE

missions and technology investments responsive to each

of the ESE spheres of research activity

Technology Infusion Strategy

• new, more-flexible strategy adopted for planning post2002 missions

• “just in time” implementation planning and decisionmaking strategy adopted for future EOS missions and

the acquisition of data

• technology development efforts to be based on science

needs

• technology development must support more-efficient

and cost-effective instrument implementation that will

shorten mission development cycles

• development and infusion of advanced technologies will

be pursued through the ESE Core Technology Program,

the ESE New Millennium Program (NMP), the ESE

Instrument Incubator Program (IIP), and related NASA

activities in High Performance Computing and Communications and Small Business and Innovative Research (SBIR)

Implementation of ESE Program after 2002

• instrument and spacecraft development can be

decoupled, thus proceeding on parallel paths

• smaller launch vehicles commercially available can be

used

• technology development efforts can be focused on advanced instruments

• specific mission identification not required until as late

as three years prior to launch

• data from one mission can be evaluated in time to make

decisions for a follow-on continuity mission

• different approaches can be adopted for “monitoring”

vs. “process” measurement missions (monitoring missions require continuity of measurements over longer

mission lifetimes whereas process measurements can

be flown in quick-turnaround, shorter lifetime missions)

• new project management approaches are possible

• “catalog” spacecraft procurements may be made

• instrument development may be entrusted to a PI or a

Team Leader (for Facility Instruments)

• science missions may be managed end-to-end (PI

model) by a Principal Investigator responsible for implementing the complete mission

• partnerships for supplying instruments, spacecraft,

launch vehicles, or entire missions can be established

in conjunction with commercial, interagency, and international entities

• new instrument technologies can be funded through the

Instrument Incubator Program (IIP), and instrument development can follow through the IIP, the ESE core

program, the New Millennium Program, or SBIR

Outreach and Partnerships

• new partnership opportunities have been identified: several proposed industrial ventures involving commercially owned and operated satellite systems may supply some of the land cover and ocean productivity measurements required at the end of the lifetime of the Terra

mission

• the tri-agency NPOESS may offer the best opportunity

for long-term monitoring of some climate parameters

Conclusion

• the first Biennial Review brought closure to several program-level issues in the EOS 1st series, and it provided

the first look into the future of ESE beyond 2002; the

Biennial Review set the tone for a new ESE strategy

for planning future missions—one more flexible, more

responsive to science needs, and more accommodating

of partnerships

The Current Status of the Program

Current mission schedules are illustrated in Figures 3 and 4

and Table 5 for the first series of Earth Science missions,

including EOS, NMP, and ESSP missions. The resulting

data communication requirements are shown in Table 6.

Program flight elements to 2006 are illustrated in tables

in the International Cooperation section. These illustrations show that AM-1 has been renamed Terra; the recommended split of altimetry missions between radar and

laser has been adopted; TES is to be accommodated on

EOS CHEM; an Advanced Land Imager (ALI) is to be

flown in a technology-validation mode on the first NMP/

EO-1 mission; and a flight of SAGE III on the International Space Station has been incorporated.

The rebaselining process introduced another category

of risk to the EOS Program. The intended lifetime design

of all EOS instruments is 5 years while the replacement

cycle is 6 years. This means, barring any launch failures,

EOS instruments must operate at least one year longer to

provide continuity of observations throughout the 15-year

period. (The calibration strategy requires an additional 6

months of overlap between instruments on different satellites to allow their intercalibration.)

More details concerning the status of the EOS and

related Earth Science Program appear in the Mission Elements section of this Handbook.
20 • The Earth Observing System 1999 EOS Reference Handbook Figure 3. Earth Science Mission Profile EOSDIS VERSION RELEASES METEOR 3M-1 (Russia) 3/00

• SAGE III

1020 km

99.5°

9:30 AM

Spacecraft not provided by NASA

• Items in italics not funded by NASA

* SAGE III is funded by the International Space Station Program

ACRIMSAT

• ACRIM III

10/99

685 km

98.13°

10:50 AM

NMP/EO-1

12/99

• ALI• Hyperion• Atmospheric Corrector

705 km

98.2°

10:01 AM 

Landsat 7

4/15/99

•

705 km

ETM+

98.2°

10:00 AM

QuikScat

6/19/99

• SeaWinds 

803 km

98.6°

6:00 AM

8/94

V0

8/97

V1

12/99

V2

7/99

V2.0

11/00

V3

9/02

V4

11/27/97

350 km

 35°

• CERES• LIS• VIRS• TMI

• PR

TRMM

 (Japan)

• PICASSO-CENA and CloudSat share the same launch vehicle

Currently in orbit

Terra

(AM)

705 km

98.2°

10:30 AM

• CERES (2)• MISR• MODIS

• ASTER

 (Japan)

• MOPITT (Canada)

11/99

 1997 1998 1999 2000

ESSP/

CloudSat

4/03

• PABSI• CPR

(US/Canada)

98.08°

705 km

1:31 PM

ESSP/

PICASSOCENA

(France)

4/03

• LIDAR• ABS• WFC• IIR

 (France)

98.08°

705 km

1:30 PM

EOS PM

12/00

705 km

98.2°

1:30 PM

• AIRS• AMSU-A• CERES (2)• MODIS

• HSB (Brazil)• AMSR-E

 (Japan)

ADEOS II

(Japan)

11/00

803 km

98.6°

10:30 AM 

• SeaWinds• AMSR• GLI

• ILAS-2

 (Japan)

• POLDER

(France)

SORCE

7/02

600 km 40°

• TIM• SIM• SOLSTICE

• XPS

EOS CHEM

705 km

98.2°

1:45 PM

• MLS• TES• HIRDLS  (UK/US)

• OMI

 (Netherlands/

 Finland)

12/02

• SAGE III *

3/03

51.6°

Space

335 km

Station

Jason-1

(France)

5/00

1336 km

66°

• JMR• GPS

• Poseidon 2• DORIS

 (France)

ESSP/VCL

9/00

• MBLA• GPS

400 km

67°

 2000 2001 2002 2003

ICESat

• GLAS• GPS

600 km

94°

7/01

ESSP/

GRACE

6/01

• HAIRS• GPS• SuperStar (US/France)

485 km

89°
1999 EOS Reference Handbook The Earth Observing System • 21

Figure 4. Earth Science Program and Flight Elements

Ice Sheets

Ecosystem

Dynamics

Rain

Volcanology Snow

2002 2001

Jason -1 (5/00)

France

• Ocean circulation• Sea level

JMR Poseidon 2

2000 1999

LANDSAT 7 (4/99)

• Terrestrial surface

ETM+

Sea Ice

Ocean Biology Land Biology

• 

• 

A DARK BOX WITH WHITE TEXT ( ) INDICATES AN INSTRUMENT PROVIDED BY AN INTERNATIONAL PARTNER

A WHITE BOX WITH DARK TEXT ( ) INDICATES A JOINT US / INTERNATIONAL PARTNERSHIP

A

A

GRACE (7/01) 

• Time-varying nature of Earth’s gravity field

SORCE (7/02) 

 TIM SIM SOLSTICE XPS 

• Solar spectral irradiance• Total solar irradiance

EOS CHEM (12/02) 

HIRDLS

• Atmospheric chemical species and their transformation 

TES OMI MLS

QuikScat (6/99)

• Surface wind speed and direction over the global oceans 

SeaWinds

Terra (11/99)

• Clouds, aerosols, and radiative balance• Characterization of terrestrial surface• Carbon cycle

CERES (2) MISR MODIS

ASTER MOPITT

ACRIMSAT (10/99) 

• Solar irradiance

ACRIM III

ADEOS II (11/00)

Japan

• Surface wind speed and direction over the global oceans 

SeaWinds

AMSR POLDER ILAS-2 GLI

EOS PM (12/00)

Clouds, precipitation, and radiative balance

Atmospheric temperature / moisture profileTerrestrial snow and sea iceSea-surface temperature and ocean productivity

••••

CERES (2) MODIS

AIRS / AMSU-A /

AMSR-E

HSB

EO-1 (12/99)

• Innovative approach to future land imaging

ALI Hyperion

VCL (9/00)

• Vegetation canopy heights

MBLA GPS

ICESat (7/01) 

• Ice sheet mass balance• Cloud heights

GLAS GPS

HAIRS GPS SuperStar

Evaporation Evaporation

METEOR 3M-1 (3/00)

Russia

• Atmospheric aerosols• Atmospheric chemical species

SAGE III

Atmospheric Corrector
22 • The Earth Observing System 1999 EOS Reference Handbook

Table 5. EOS, NMP, and ESSP Instrument Complement: Phase I

1997

1999

1999

1999

1999

1999

1999

2000

2000

2000

2000

2001

2001

2002

2002

2002

2003

2003

TRMM

Landsat 7

Terra

QuikScat

ACRIMSAT

METEOR 3M-1

NMP/EO-1

Jason-1

ESSP-1/VCL

ADEOS II

EOS PM

ESSP-2/GRACE

ICESat

Space Station

SORCE

EOS CHEM

ESSP-3/

PICASSO-CENA

ESSP-4/

CloudSat

 3 yrs

5 yrs

6 yrs

3 yrs

5 yrs

3 yrs

1 yrs

5 yrs

2 yrs

5 yrs

6 yrs

5 yrs

3 yrs

5 yrs

5 yrs

6 yrs

3 yrs

2 yrs

CERES • LIS

ETM+

MODIS • MISR • CERES (2) • MOPITT • ASTER

SeaWinds

ACRIM III

SAGE III

ALI • Hyperion • Atmospheric Corrector

JMR • Poseidon 2 • DORIS • GPS

MBLA • GPS

SeaWinds

MODIS • AMSR-E • CERES (2) • AIRS • AMSU-A • HSB

HAIRS • GPS • SuperStar

GLAS • GPS

SAGE III

TIM • SIM • SOLSTICE • XPS

MLS • TES • HIRDLS • OMI

LIDAR • ABS • WFC • IIR

PABSI • CPR

1

2,3

5

4

6

7

2

6

5

6

6

Launch Spacecraft EOS, NMP, and ESSP Instrument Complement Lifetime See Notes

Notes:

TRMM is a joint U.S/Japan mission, launched November 28, 1997. It also flies a Precipitation Radar (PR), TRMM Microwave Imager (TMI), and

Visible/Infrared Scanner (VIRS).

AIRS, AMSU-A, HSB, AMSR-E, and MODIS data available via direct broadcast (X band).

ASTER data available via direct downlink.

The New Millennium Program (NMP) is charged to develop and flight-validate breakthrough technologies that will reduce the cost of highpriority science missions of the 21st Century while enhancing their scientific capability. During the first year, the Advanced Land Imager (ALI),

including the Hyperion, will be subjected to a technology validation. If the results are promising, operations will continue for a second year of

data utilization.

Series of ACRIM, SORCE, or similar missions planned to maintain continuity in the total solar irradiance data set for at least 15 years.

The Earth System Science Pathfinders (ESSP) program is designed to explore the Earth’s dynamic systems and to achieve maximum science

value while complementing existing or planned flight missions. The Principal Investigator is responsible for developing the flight mission

hardware from selection to a launch-ready condition within 36 months, and along with the mission team is responsible for accomplishing the

science objectives.

ADEOS II is a Japanese mission. It will also fly an Advanced Microwave Scanning Radiometer (AMSR), a Global Imager (GLI), a Polarization

and Directionality of Earth's Reflectances (POLDER) instrument, and an Improved Limb Atmospheric Spectrometer (ILAS-2).

1.

2.

3.

4.

5.

6.

7.
1999 EOS Reference Handbook The Earth Observing System • 23

Ø

Ø

1997

ACRIM III

AIRS

ALI

AMSR-E

AMSU-A

ASTER

CERES

CloudSat

Poseidon-2

ETM+

GLAS

GRACE

HIRDLS

HSB

JMR

LIS

MISR

MLS

MODIS

MOPITT

OMI

PICASSO-CENA

SAGE III

SeaWinds

SORCE

TES

VCL

EOS Instrument 1998 1999 2000 2001 2002 2003

Terra

17.848 Mbps

Landsat 7

12.963 Mbps

EOS PM

7.755 Mbps

EOS Chem

5.856 Mbps

ICESat

0.450 Mbps

METEOR 3M

(SAGE III)

0.024 Mbps

Space Station

(SAGE III)

0.024 Mbps

ADEOS II (SeaWinds)

0.040 Mbps

QuikScat (SeaWinds)

0.040 Mbps

TRMM (CERES & LIS)

0.016 Mbps

Jason-1

0.024 Mbps

SORCE

0.007 Mbps

ACRIMSAT

0.001 Mbps

NMP/EO-1

105 Mbps (See Note 3)

ESSP (VCL, GRACE,

PICASSO-CENA,

CloudSat)

(See Note 4)

Platform Average Data Rates

3 3 5 4 4

Numbers in timeline bars indicate copies in orbit once the instruments have commenced routine operations.

The “Instruments in Flight” entry is the maximum number of instruments operating at the same time during the year. For example, there will be 3 CERES

instruments operating after the launch of Terra in 1999 when the following missions overlap: TRMM (1 CERES) and Terra (2 CERES). (See Figure 3.)

The average data rate of the ALI instrument is 105 Mbps. However, only 4 snapshots are taken each day and their total readout time is only about 30 minutes.

Hence, this data rate is NOT included in the total Average Data Rate because it would present a grossly-distorted picture of the actual value over 24 hours.

The ESSP (VCL, GRACE, PICASSO-CENA, and CloudSat) missions are not formally part of the EOS Program and their data processing is performed at separate

facilities.

Notes:

1.

2.

3.

4.

2 2

2 3 2

2 2

Average Data Rate

Mbps

Instruments in

Flight

0.016 0.016 30.9 38.7 39.1 45.0 44.9

2 2 13 21 24 28 28

Table 6. EOS and NMP Platform Instrument Counts and Data Rates

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

Ø

2
24 • The Earth Observing System 1999 EOS Reference Handbook

Sources of greenhouse gases, which affect predictions of

their future concentrations

Clouds and radiative balance, which strongly influence

the magnitude of climate change at global and regional

scales

Oceans, which influence the timing and patterns of

climate change

Land surface hydrology, which affects regional climate

change and water availability

Polar ice sheets, which affect predictions of global sea

level changes

Ecological dynamics, which is affected by, and responds

to, climate change

AIRS/AMSU-A/HSB, HIRDLS, MLS, MODIS, MOPITT,

OMI, SAGE III, and TES

ACRIM III, AIRS/AMSU-A/HSB, CERES, EOSP, AMSR-E,

MISR, MODIS, and SORCE

JMR, AMSR-E, MODIS, SeaWinds, and Poseidon-2

AIRS/AMSU-A/HSB, ASTER, ALI, ETM+, AMSR-E, MISR,

and MODIS

ASTER, JMR, ETM+, GLAS, AMSR-E, MODIS, and

Poseidon-2

AIRS/AMSU-A/HSB, ASTER, ETM+, ALI, MISR, and

MODIS

IPCC Category EOS Instrument Complement

Table 7. Links to IPCC Areas of Uncertainty

Contributions of ESE and EOS to National

Objectives

In pursuit of U.S. policy relative to global change, ESE

undertakes observations from space and performs interdisciplinary science studies to interpret and apply these

observations. Integrated and conceptual models, substantiated by space-based observations, have already provided

policymakers with a firm basis for making sound environmental policy decisions related to substances that deplete the ozone layer (e.g., the Montreal Protocol on Substances that Deplete the Ozone Layer adopted in 1987).

In the EOS era, the corresponding challenges include prediction of El Niño events, the implications of increased

emissions of greenhouse gases for global warming, and

impacts of land-cover change on the carbon budget,

biodiversity, and agricultural productivity. Fuller discussion of these challenges is found in the EOS Science Strategy document and the EOS Science Plan (see References

at the end of this section).

A basic question that must be resolved before policy

decisions can be reached has to do with determining

whether changes now being observed throughout the

world are systematic (relatively persistent long-term

changes) or just part of normal climatic variability. If the

changes being observed are in fact systematic, are they

sufficiently significant in impact to warrant action by

policymakers? Do we know well enough whether the

observed changes are attributable to human activities? Are

appropriate technological alternatives or restrictions on

human activities available to mitigate the changes or their

impacts, and is it reasonable to impose such restrictions?

Are the consequences of imposing restrictions more damaging to our quality of life (e.g., because of major disruptions in the world’s economy) than the anticipated changes

in the global climate system?

The physical-modeling and data-gathering activities

over the planned 15 or more years of the EOS Program

are intended to make a major contribution to establishing

the distinction between natural variability in the Earth system and changes that are introduced by human activities.

The choices of intervention strategies to mitigate possible

undesirable changes or their impacts will have to be based

at least in part on the findings of ESE- and EOS-supported

scientists in the U.S. and their counterparts around the

world.

ESE offers a new perspective on the functioning of

planet Earth through coordinated, long-term, space-based

and in situ observations, and a program of interdisciplinary research addressing priority issues of Earth system

science. This Presidential Initiative is supported by Congress, which granted NASA a “new start” budget line item

for the EOS Program in 1990. Following this mandate

from the Administration and Congress, NASA has placed

itself at the forefront of Earth observing satellite technology development and data management. The improved

measurement and modeling capabilities that result directly

support the U.S. and international global change research
1999 EOS Reference Handbook The Earth Observing System • 25

programs, and reinforce the U.S. position as a world leader

in space-based remote sensing.

The successive reconfigurations of the EOS payloads

have had both benefits and pitfalls; yet, in the prevailing

budget environment, decisionmakers have had to balance

the science return against costs incurred. Any further rearrangements will require review by the EOS IWG to

determine if they represent an acceptable solution towards

satisfying the identified IPCC science and policy priorities (see Table 7). Furthermore, the potential of achieving

the international commitments assumed in the rebaselined

program must be quantified to determine the consequences

of data gaps should these collaborations not be realized.

References

EOS—Science Strategy for the Earth Observing System,

by Ghassem Asrar and Jeff Dozier, published by AIP Press,

July 1994. This publication provides a broad overview of

the EOS Program, stressing the scientific considerations

that led to the definition of the overall program as an essential element of the U.S. Global Change Research Program (USGCRP).

Science Data Plan for the EOS Data and Information System, 1994, Matthew Schwaller and Brian Krupp, editors.

Available from the EOS Library, Code 505, Goddard

Space Flight Center, Greenbelt, MD 20771. This publication describes the management approach as well as current and projected holdings of the EOS Data and Information System (EOSDIS) at the various Distributed Active Archive Centers around the United States.

The EOSDIS Data Products Handbook, Volume 1, provides high-level descriptions of the data sets that will be

produced from instruments on the Tropical Rainfall Measuring Mission (TRMM) and Terra satellites. It highlights

the significance, evolution, and application of the data

products at a level intended for the general science public

as well as for researchers. It is available from the Global

Change Data Center, Code 902, Goddard Space Flight

Center, Greenbelt, MD 20771.

Earth Observing System Output Data Products and Input

Requirements, Version 4.0, May 1996. Available from the

Earth Science Data and Information System Office, Code

505, Goddard Space Flight Center, Greenbelt, MD 20771.

It lists all at-launch and post-launch data products planned

by EOS instrument teams, gives information on the characteristics of each parameter, required input data, and processing load estimates. (http://spsosun.gsfc.nasa.gov/

eosdata.html).

The EOS Contribution to National Goals (edited by E.

Barron, D. Hartmann, D. Schimel, and M. Schoeberl), is

a product of the EOS Investigators Working Group. It relates the activities, goals, and intended products of EOS

to the requirements for the scientific insights needed for

national policy making.

The EOS Science Plan, also a product of the EOS Investigators Working Group, appears in two volumes: The

Executive Summary (edited by Renny Greenstone and

M.D. King) and the Science Plan, proper (edited by M.D.

King). It is an in-depth presentation of the studies being

conducted by the investigators who form the scientific

core of EOS. The nature of the scientific problems is described; the plans for meeting these problems through

acquisition of in situ and remote-sensing observations and

through analyses are given; and there are expositions of

the products that are anticipated as a result of the analyses. Both the “National Goals” document and the EOS

Science Plan, as well as a CD-ROM version of the EOS

Science Plan, are available through the EOS Project Science Office (EOSPSO).

The World Wide Web (WWW) is an excellent electronic

source of EOS information. The following documents are

currently available on the Web (http://eos.nasa.gov/) and

others will be made available as they are published:

The Earth Observer is a bimonthly newsletter of the

EOSPSO. It gives current reports on the status of various elements of the EOS Program.

Payload Panel Reports are a key source of understanding the recommendations that have been made by this

key group of EOS scientists for devising the payloads

of the various EOS spacecraft missions that will best

meet scientific and budgetary requirements of the Program.

Algorithm Theoretical Basis Documents (ATBDs) are

being developed for every EOS instrument standard

product, although some ATBDs address more than one

product, and some products are addressed by more than

one ATBD. ATBDs typically provide the theoretical

basis—both the physical theory and the mathematical

procedures and possible assumptions being applied—

for the calculations that have to be made to convert the

radiances acquired by the instruments to geophysical

quantities. The geophysical quantities are then available to the scientific community for studies of the various characteristics of the Earth system.

The EOS Directory lists the addresses, affiliations,

phone numbers, and electronic mail addresses, as well

as assignments of EOS-related personnel. It is searchable at the URL listed below and is not available in

printed form.

EOS Project Science Office URL

http://eos.nasa.gov/
1999 EOS Reference Handbook EOS Data and Information System • 27

More than any other factor, the commitment to make Earth

science data easily available to a wide community of users is critical to the success of NASA’s Earth Science

Enterprise. The EOS Data and Information System (EOSDIS) is being developed, with an initial version called

Version 0 operating now to meet that commitment.

At present, EOSDIS manages data from NASA’s past

and current Earth science research satellites and field

measurement programs, providing data archiving, distribution, and information management services. During the

EOS era that started with the launch of the TRMM satellite in 1997, EOSDIS will command and control satellites and instruments, and will generate useful products

from orbital observations. EOSDIS will also generate data

sets made by assimilation of satellite and in situ observations into global climate models. Several steps are being

taken to increase flexibility in EOSDIS by distributing

the responsibility for provision of its various services. In

the near-term, the data assimilation products, the data

products from the EOS instruments on TRMM, from some

of the Terra instruments, and from SAGE III will be generated either at the Principal Investigators’ computing facilities or under their direct control. An adaptive approach

will be used during the EOS PM-1 era to determine the

best assignment of responsibility for product generation

considering technical advantages, cost, and schedule. An

experiment is now underway with a set of competitively

selected “Working Prototype Earth Science Information

Partners (WP-ESIPs)” to examine the feasibility of providing data services through a federation of ESIPs. Such

a federation could provide an additional measure of flexibility in distributing the responsibilities during the EOS

CHEM era.

Services Provided by EOSDIS

EOSDIS is a comprehensive data and information system designed to perform a wide variety of functions in

support of a heterogeneous national and international user

community. To this end, EOSDIS provides a spectrum of

services: some services are intended for a diversity of

casual users, some are intended only for a select cadre of

research scientists chosen by NASA’s peer-reviewed competitions, and many fall somewhere in between these extremes. The entities providing these services may vary

over time as a result of implementing the adaptive approach and the WP-ESIP federation experiment. The primary services provided by EOSDIS are summarized below:

User Support – The vast majority of people who interact

with EOSDIS will do so via the EOSDIS Distributed

Active Archive Centers (DAACs). The functions of the

DAACs are described in more detail in a following section, and details about each DAAC are provided in a subsequent section. The DAACs have User Support Services

to assist users in data acquisition, search, access, and usage. While most of the interaction by users with EOSDIS

is through human-computer interfaces, occasional consultation will be needed with the User Support Services

staff for assistance with specialized questions regarding

the data or the system. EOSDIS expects to provide support services to users from the public and private sectors,

including research scientists, educators, students, users

in public agencies responsible for operational applications

such as weather forecasts and environmental monitoring,

policymakers, and the public in general (see Table 8 for a

listing of DAAC contact information).

Data Archive, Management, and Distribution – A list

of current and projected EOSDIS data holdings is available in the EOSDIS Science Data Plan (see References at

the end of this section). Overall, this list includes data

products derived from the satellite missions and scientific campaigns, plus other related data and information.

In the EOS era, EOSDIS will store all the standard and

special products computed from the EOS instruments

during the mission life, and distribute requested subsets

to users either electronically (via networks) or on appropriate media. In addition, EOSDIS will store and distribute data from non-EOS sources that are needed for EOS

standard product generation. Also, product generation algorithms, software, documentation, calibration data, engineering, and other ancillary data will be stored and provided to users upon request. Sufficient information will

be stored about the system configuration history to be able

to regenerate products in case of accidental or catastrophic

loss. Access to the current suite of EOSDIS data holdings

may be obtained via the DAACs.

EOS Data and Information

System (EOSDIS)
28 • EOS Data and Information System 1999 EOS Reference Handbook

Table 8. EOS Distributed Active Archive Centers DAAC & Discipline Address User Support Office Contact Information E-mail: asf@eos.nasa.gov, uso@asf.alaska.edu Tel: 907-474-6166 Fax: 907-474-5195 URL: http://www.asf.alaska.edu/ E-mail: edc@eos.nasa.gov Tel: 605-594-6116 Fax: 605-594-6963 URL: http://edcwww.cr.usgs.gov/landdaac/ E-mail: gsfc@eos.nasa.gov Tel: 301-614-5224 Fax: 301-614-5268 URL: http://daac.gsfc.nasa.gov/

E-mail: jpl@eos.nasa.gov, podaac@podaac.jpl.nasa.govTel: 626-744-5508 Fax: 818-393-2718URL: http://podaac.jpl.nasa.gov/

E-mail: larc@eos.nasa.govTel: 757-864-8656 Fax: 757-864-8807URL: http://eosweb.larc.nasa.gov/

E-mail: nsidc@eos.nasa.gov, nsidc@kryos.colorado.eduTel: 303-492-6199 Fax: 303-492-2468URL: http://www-nsidc.colorado.edu

E-mail: ornl@eos.nasa.gov, ornldaac@ornl.govTel: 423-241-3952 Fax: 423-574-4665URL: http://www-eosdis.ornl.gov

E-mail: ciesin.info@ceisin.orgTel: 914-365-8988 Fax: 914-365-8922URL: http://sedac.ciesin.org, http://www.ciesin.org

ASFSea Ice, Polar Processes, Synthetic Aperture Radar Imagery (SAR)

EDCLand Processes

GSFCUpper Atmosphere, Global Biosphere, Atmospheric Dynamics

JPLPhysical Oceanography

LaRCRadiation Budget, Clouds, Aerosols, Tropospheric ChemistryNSIDC

Snow and Ice, Cryosphere and ClimateORNLBiogeochemical Dynamics

SEDACHuman Impact on Global Change

Alaska SAR Facility, User ServicesPO Box 757320University of AlaskaFairbanks, AK 99775-7320United States Geological SurveyEROS Data CenterSioux Falls, SD 57198NASA/Goddard Space Flight CenterCode 902.2Greenbelt, MD 20771Jet Propulsion LaboratoryM/S Raytheon-2994800 Oak Grove DrivePasadena, CA 91109NASA/Langley Research CenterMail Stop 157D2 South Wright StreetHampton, VA 23681-2199National Snow and Ice Data CenterCIRES, Campus Box 449University of ColoradoBoulder, CO 80309-0449Oak Ridge National Laboratory (ORNL)Environmental Sciences DivisionPO Box 2008, MS 6407, Bldg. 1507Oak Ridge, TN 37831-6407Socioeconomic Data and Applications CenterColumbia Univ./Lamont-Doherty Earth ObservatoryP.O. Box 1000, 61 Rt. 9WPalisades, NY 10964
1999 EOS Reference Handbook EOS Data and Information System • 29

Information Management – EOSDIS provides convenient mechanisms for locating and accessing (either electronically or via orders for data on media) products of

interest. The ‘look and feel’ of the system is intuitive and

uniform across the multiple nodes from which EOSDIS

will be accessed. EOSDIS will facilitate collaborative

science by providing extensible sets of tools and capabilities such that investigators may provide access to special products (or research products) from their own computing facilities. EOSDIS has a currently operational EOS

Data Gateway that provides “one-stop-shopping” access

to the data holdings at all the EOSDIS DAACs and participating data centers from other U.S. and international

agencies. The services of the V0 IMS can be accessed on

the World Wide Web at http://eos.nasa.gov/imswelcome.

The V0 IMS permits users to access EOSDIS archives,

browse data holdings, select data products or their subsets (for products where the capability is available), and

place data orders. In addition, specialized services at each

of the EOSDIS DAACs can be accessed via their individual interfaces. The latest information about the features of, and access to, Version 0, and links to information about individual DAACs, is available through the

following World Wide Web location: http://eos.nasa.gov/

v0ims.

Product Generation – Beginning with the TRMM launch

in 1997, EOSDIS has started supporting data product generation from EOS instrument observations. Algorithms

and software for EOS data products are generated by EOS

investigators as a part of their scientific studies. Specifications for standard products are reviewed by NASA and

the EOS Investigators Working Group (IWG) to ensure

completeness and consistency to satisfy the goals of the

EOS mission. The physical, chemical, and biological bases

for these products and soundness of approach for their

generation are peer reviewed independently by non-EOS

Earth scientists prior to the launch of each instrument.

Priorities for the processing and reprocessing needed to

generate standard products depend on scientific requirements, technical considerations, and cost. Such priorities

are determined by the EOS Project Scientists based on

recommendations from the IWG and the national and international Earth science community.

Spacecraft Command and Control – EOSDIS will perform spacecraft and instrument planning and scheduling,

and command and control. These functions include processing data acquisition requests, coordination of multiinstrument observations, ensuring that the commands generated are valid and within resource constraints, monitoring and maintenance of the health and safety of spacecraft and instruments, engineering analysis of spacecraft

data, and maintaining history of spacecraft and instrument

operations. EOSDIS will also provide appropriate interfaces to ensure command and control of International

Partners’ instruments onboard EOS spacecraft, and EOS

instruments onboard non-EOS spacecraft.

Data Capture and Telemetry Processing – In the EOS

era, EOSDIS will capture data from all EOS spacecraft

and process them to remove telemetry errors, eliminate

any artifacts, and create Level 0 data products that are

“raw” data as measured by the instruments (see the end

of this section for data level definitions). Several of the

EOS instruments are designated as prototype operational

environmental monitoring instruments. The data from

those instruments will be made available to NOAA within

three hours of observation to support operational weather

forecasts. For EOS instruments flying on non-EOS spacecraft, the EOS instrument data are captured by the respective ground systems and received by EOSDIS for

higher-level data processing, archiving, and distribution.

EOSDIS Components

NASA is implementing EOSDIS using a distributed, open

system architecture. This permits allocation of EOSDIS

elements to various locations to take best advantage of

different institutional capabilities and science expertise.

EOSDIS consists of six major components—Distributed

Active Archive Centers, Science Investigator-led Processing Systems, the EOSDIS Core System, Networks, EOS

Data and Operations System, and EOS Polar Ground Stations. These components and their relationship to other

elements are illustrated in Figure 5.

The following paragraphs provide details of each of

the major components. The sequence of presentation does

not imply prioritized ranking. Each component is essential in the successful implementation of EOSDIS.

Distributed Active Archive Centers (DAACs) – Seven

DAACs representing a wide range of Earth science disciplines have been selected by NASA to carry out the responsibilities for processing, archiving, and distributing

EOS and related data, and for providing a full range of

user support. An eighth DAAC acts as a link between the

EOS Program and the socio-economic and educational

user community. The geographic distribution of the

DAACs is illustrated in Figure 6. These institutions are

custodians of EOS mission data, and ensure that data will

be easily accessible to users. Acting in concert, DAACs

provide reliable, robust services to users whose needs may

cross traditional discipline boundaries, while continuing

to support the particular needs of their respective discipline communities. DAAC assignments were based primarily on the current distribution of scientific expertise,

institutional heritage, and capability. The DAACs are currently serving a broad user community using the capabilities of Version 0 EOSDIS (see subsection below) developed collaboratively with the Earth Science Data and
30 • EOS Data and Information System 1999 EOS Reference Handbook

Instrument Support

Terminals (IST)

(Instrument PIs’ sites)

Global Change Data 

Information System (GCDIS)

Agencies and

International Data Centers

SCFs

(Investigators’ sites) USERS

EOS Operations

Center (EOC)

(Greenbelt, MD)

International

Partner

Operations

Center(s)

System Monitoring

& Coordination

(Greenbelt, MD)

Quality Control

Scientific Computing

 Facilities (SCFs)

(Investigators’ sites)

DAACs

• Product

 Generation

EOS Spacecraft

White Sands Complex

(White Sands, NM)

EOS Polar Ground Stations

(Svalbard, Norway &

Poker Flat, AK)

EOS Data and

Operations System

 (White Sands, NM,

Greenbelt, MD, Svalbard, Norway

& Poker Flat, AK)

Non-EOS ESE

Satellites and

Research Projects

• Data Archiving

 and Distribution

• Information

 Management

• User Support

Commands Data

Commands Data

Data

Data

EOSDIS Internal Networks

• Product

 Generation

SIPSs

EOSDIS External Networks

Figure 5. EOSDIS Architecture
1999 EOS Reference Handbook EOS Data and Information System • 31

Information System (ESDIS) Project. As future versions

of EOSDIS are developed, the DAACs will continue to

provide their services to the user community using capabilities of the Science Data Processing Segment of the

EOSDIS Core System (see subsection below) and may

develop unique capabilities to augment them. Each DAAC

has a working group of users to provide advice on priorities for scientific data, levels of service, and the needed

capabilities. The DAACs actively participate in the design, implementation, and operation of EOSDIS.

Science Investigator-led Processing Systems (SIPSs) –

In addition to the DAACs, there are other facilities at

which EOS standard products are produced. These facilities are under the direct control of the instrument Principal Investigators/Team Leaders or their designees and are

referred to as Science Investigator-led Processing Systems. The SIPSs are generally, but not necessarily, collocated with the PI’s/TL’s Scientific Computing Facilities.

Under the recently adopted “adaptive approach” to data

processing, the production of standard data products is

allocated among DAACs (using the EOSDIS Core System) and SIPSs based on cost-benefit analyses. Products

produced at the SIPSs using investigator-provided systems and software will be sent to appropriate DAACs for

archival and distribution.

EOSDIS Core System (ECS) – ECS provides the “core”

common capabilities and infrastructure required for performing planning and scheduling, command and control,

product generation, information management, data archiving and distribution, and user access to data held by

EOSDIS. ECS consists of three segments described below: the Science Data Processing Segment, the Flight

Operations Segment, and the Communications and System Management Segment.

Science Data Processing Segment (SDPS) – SDPS supports product generation, data archiving and distribution, and information management. The SDPS hardware and software, developed as a part of ECS, will

reside and operate at the DAACs. SDPS supports the

integration and testing of software for product generation algorithms developed by the EOS investigators. It

provides for planning of data product generation, taking into account interdependencies among them, and

the distribution of computational resources. It provides

for ingest and storage (temporary or permanent, depending on data type) of data sets needed from other data

centers for supporting the generation of standard data

products. It generates standard products in a timely

manner using the investigator-provided software. It

supports the extraction of appropriate subsets of stanASF

Sea Ice and Polar 

Processes Imagery

EDC

Land Processes 

Imagery

CIESIN

Socio-Economic

Applications

ORNL

Ground-Based Data Relating

to Biogeochemical Dynamics

GSFC

Upper Atmosphere,

Atmospheric Dynamics,

and Global Biosphere

LaRC

Radiation Budget,

Aerosols, and

Tropospheric Chemistry

JPL

Ocean Circulation and 

Air-Sea Interaction

NSIDC

Cryosphere

(non-SAR)

Figure 6. Geographic Distribution of EOSDIS DAACs
32 • EOS Data and Information System 1999 EOS Reference Handbook

dard data products to assist in scientific quality control

by the respective investigators. It supports reprocessing as required.

Flight Operations Segment (FOS) – FOS controls all

of the EOS spacecraft, provides mission planning and

scheduling, and monitors health and safety of the spacecraft and instruments. It provides tools to coordinate

observations from multiple instruments and develop

conflict-free schedules, validate commands to assure

safety, accommodate unplanned schedule changes, develop and provide mission timelines, and develop and

implement contingency plans. It interacts with the various elements of the ground systems and space network

as necessary to send commands to the EOS spacecraft

and to receive health and safety data from the spacecraft. It interacts with the International Partners’ instrument control centers for exchange of planning and command and control information. The FOS is presently

being implemented using a combination of a commercial mission control system and custom software to

constitute the EOS Mission Operations System

(EMOS).

Communications and System Management Segment

(CSMS) – CSMS provides the communications, networking, and system management functions needed by

the SDPS and FOS. It provides the capabilities for the

DAACs to perform local system management functions

and the capabilities for cross-DAAC coordination and

monitoring to ensure autonomous, yet coordinated, operation of SDPS. It provides for monitoring and maintaining status information about EOSDIS. It provides

common services such as request brokering, client/

server communications, electronic mail, bulletin boards,

local-area and wide-area networks, system security, accounting, user registration, and report generation.

EOS Data and Operations System (EDOS) – EDOS

transmits commands to the EOS spacecraft, captures science and engineering data from the spacecraft and instruments, processes telemetry to generate Level 0 products,

and maintains a backup archive of Level 0 products. It

removes telemetry artifacts, creates sets of non-overlapping raw data as sensed by the individual instruments over

specific time intervals, and sends them to the appropriate

DAACs for generation of higher level products. In the

case of a data loss at any of the DAACs, the data can be

recovered from the backup archive within EDOS. In the

case of loss of a part of the backup Level 0 data within

EDOS, the corresponding data can be recovered from the

appropriate DAAC.

EOS Networks – Effective access to EOSDIS depends

on network connectivity between users and data sources.

Existing and evolving network capabilities in the U.S.

and abroad will be used to satisfy the connectivity needs.

These capabilities include the NASA Integrated Services

Network (NISN), its connections to the National Science

Foundation (NSF) Internet, and the NASA Research and

Education Network (NREN) as it develops. Connectivity

to the EOS investigators’ scientific computing facilities

(SCFs) is being established, based on existing connectivity and need. The SCFs that are involved in the quality

control of standard data products will be provided the

appropriate connectivity and bandwidth to ensure timely

data transfers to meet their requirements. The DAACs,

ECS, and EDOS are connected through the EOS Backbone Network (EBNet) to assure security, timeliness, and

predictable response. The EBNet is a dedicated EOS resource that interconnects the DAACs to support interDAAC data flows for generation of interdependent EOS

products and to provide secure, reliable communications

to uplink commands to the EOS spacecraft and to move

Level 0 instrument data to the DAACs.

EOS Polar Ground Stations – The EOS Polar Ground

Stations (EPGS) provide X-band capabilities for receiving science data dumps and S-band Tracking, Telemetry

and Commanding (TT&C) capabilities for Landsat 7,

EOS, and other ESE spacecraft. There are two polar

ground stations, one in Svalbard, Norway and the other

in Poker Flat, Alaska. These stations include several major architectural components: the radio-frequency subsystem, base-band data-processing subsystem, monitor

and control subsystem, and commercial telecommunication subsystem. The stations also house ground-system

interface facilities that are a part of EDOS.

EOSDIS Architecture

Since EOSDIS will be NASA’s central Earth science data

system for at least the next two decades, it must evolve to

accommodate changes in technology, user requirements,

and user interactions with data and data systems. To reach

this end, EOSDIS planning has been significantly influenced by reviews from the EOSDIS Panel, the National

Research Council’s (NRC) Panel to Review EOSDIS

plans, the NRC Committee on Global Change Research

(CGCR), and the NRC Board on Sustainable Development (BSD). Some of the key science goals in the design

of the system have been the need to support data search

and access, dynamic product life cycle and extensible

product sets, interactive investigations, information-rich

logical data collections, integration of independently developed investigators’ tools and software, user-to-user collaboration, distributed administration and control, and site

autonomy.

To reach its joint goals for science support and evolution, EOSDIS is designed as a logically distributed system. It will have sufficient modularity and standard interfaces to enable migration and/or replacement of compo-
1999 EOS Reference Handbook EOS Data and Information System • 33

nents. It will be built with a selection of subsystems and

services tailored to particular data types and other specific needs. It will permit autonomy for service providers

and the required amount of coordination among them.

A basic feature of the EOSDIS architecture is its reliance on the “client-server” model. A client is an individual or group that requests a service. A server provides

the requested service. Some servers, called “agents”, may

call upon other servers while processing a client’s request.

The EOSDIS architecture permits easy introduction of

new technologies and addition of servers that may provide subsets of the services offered by EOSDIS. Such

servers are not necessarily designed, built, or provided

by the EOS Program. It is important to note, however,

that non-EOS data servers will still be able to interact

with EOSDIS.

Some of the key features of the distributed EOSDIS

architecture are provided below. Greater detail on the

EOSDIS architecture can be found in the references at

the end of this section.

Directory Services – Each component of ECS advertises

the availability of its services through the ECS Advertising Service. This is the mechanism that ECS uses for its

internal subsystems to inform each other of their respective services. The Global Change Master Directory (see

http://gcmd.gsfc.nasa.gov/) will be used by EOSDIS to

advertise its data holdings at the directory level.

Service Classes – The services and data offered by a given

system component are accessed via defined “service interfaces.” The services are grouped into “service classes.”

and each service class has a defined interface that can be

accessed locally or remotely.

Application Programming Interfaces (APIs) – For the

interoperation of software components with each other,

each of the services defines an API called the Client API.

Programs call the Client API to obtain a service. The

CSMS provides services needed for the software components to communicate with each other. Both the definitions of service classes and APIs provide modularity in

the system.

Data Collections and Data Servers – The Earth science

data are organized in collections of related data. Each collection is managed by a data server. The data servers can

be tailored to the data types, thus permitting different designs and organizations of data, depending, for example,

on whether the data are multispectral images or atmospheric soundings. The physical location of the data collections is transparent to users.

Data Production – The functions in the system used for

product generation are treated like any other service. The

site that offers the service advertises it and can be found

regardless of its location. Distributed planning permits

making optimal use of distributed computing resources.

The design also permits flexibility in decisions on whether

a product should be produced routinely or on-demand,

and whether it should be produced at a DAAC or SIPS.

Data Ingest – The data ingest service is distributed such

that data can be ingested routinely or ad hoc. The ingest

services can be found through the advertising service and

contacted via the CSMS without regard to their location.

Data Search and Access – The search and access services are found through the advertising service. Users can

issue search and access requests directly to the data servers or use a distributed search service to find data from

multiple data collections and combine the results. The

distributed information management across multiple sites

and the local information management for a given site

are provided as separate services to provide sites with

autonomy in making changes to their local components.

EOSDIS Evolution

User needs for EOSDIS will become more clearly understood as researchers work with, and respond to, early versions of the system; user needs will undoubtedly change

over time. New information systems technology will

emerge continually, including new database and information management technology applicable to Earth science

data, faster processors, and more-capable networks. To

succeed over its lifetime, EOSDIS must respond to

change; its design and the implementation process must

foster change while supporting ongoing operations and

user services. Development and prototyping will continue

throughout the life of the system. EOSDIS evolution begins with V0, and will continue with subsequent versions

as described below. Also, as indicated in the opening section of this chapter, the allocation of responsibilities for

EOSDIS functions will evolve over time to lead to a moredistributed system.

EOSDIS V0 – A working prototype with some operational elements, this initial version of EOSDIS interconnects existing Earth science data systems via electronic

networks, interoperable catalogs, and common data distribution procedures to provide better access to existing

and pre-EOS data. Starting with existing, heterogeneous

Earth science data systems, V0 has been developed to

evolve toward the full EOSDIS by taking maximum advantage of existing experience and by ensuring that no

disruption in current user services occurs. Through the

interconnection of the existing systems, V0 serves as a

functional prototype of selected key EOSDIS services.

As a prototype, it does not have all the capabilities, fault

tolerance, or reliability of the later versions; however,

EOSDIS V0 supports use by the scientific community in
34 • EOS Data and Information System 1999 EOS Reference Handbook

day-to-day research activities. Such use tests existing services to determine the additional or alternative capabilities required of the full EOSDIS. Development of V0

began in 1991 as a collaborative effort between the Earth

Science Data and Information System (ESDIS) Project,

all the DAACs* and the NOAA Satellite Active Archive

(SAA). V0 became operational in August 1994. Since then

V0 has been serving a user community of over tens of

thousands of users, supporting over 900 datasets in a growing archive presently over 125 Tbytes, and each month

fills data orders to provide over 10 Tbytes of data to users. The current DAAC usage statistics can be found at

the World Wide Web location – http://eos.nasa.gov/eosdis/

daacstats.

The operational experience with V0 has been invaluable in the evolution of the V0 IMS and the local systems

within the DAACs. It has also provided very significant

lessons for the development of components within ECS

to be used for the future versions of EOSDIS. Version 0

will continue to operate until the data from Version 0 are

migrated into a subsequent version of the system, and the

Version 0 hardware components become obsolete. During this period, the two versions of the system will

interoperate.

EOSDIS V1 – Version 1, consisting of extensions of the

Version 0 at the Goddard and Langley DAACs, has been

providing full support for TRMM since its launch in November 1997. The Langley TRMM Information System

(LaTIS) provides the capability for product generation,

archiving, and distribution of the standard products from

CERES instrument data. The Goddard DAAC’s TRMM

Support System (TSS) supports archiving and distribution of all products from TRMM except those from the

CERES and LIS instruments. The products from the LIS

instrument are generated and archived at, and distributed

from, the LIS Principal Investigator’s Computing Facility at the Global Hydrology Resource Center in Huntsville, Alabama.

EOSDIS V2.0 – Version 2.0, now planned to be operational in July 1999, will provide all the launch-critical

functions needed to support Terra. These functions include: Spacecraft command and control, data capture and

back-up archive, production of at-launch standard products and support for their quality assessment at the SCFs,

and their archiving and distribution to users. A subset of

capabilities critical to Landsat 7 has been available since

March 1999. An incremental release will be made in late

1999 with an increased set of capabilities prioritized in

consultation with the user community.

Subsequent versions of EOSDIS will supplement capacity and services as required by EOS spacecraft

launches. EOSDIS capabilities will evolve, based on continuing evaluation by the research community, and the

system will be enhanced as the need arises, inserting the

latest technologies appropriate to meeting the users’ requirements. Also, the allocation of responsibilities for

EOSDIS functions will evolve over time to lead to a moredistributed system.

By the end of the EOS mission, plans call for the

data held by EOSDIS to be transferred to the control of

long-term archival agencies that have vested interest and

responsibility for management and distribution of such

data. Examples include, but are not limited to, NOAA

and the U.S. Geological Survey (USGS). The transfer is

planned to occur gradually, starting approximately 3 years

after the launch of each spacecraft. EOSDIS will ensure

provision of seamless access to the full stream of data for

users, although data pricing policies may differ.

Key EOSDIS Terminology

Standard Data Products – Data products that are generated as part of a research investigation using EOS data,

are of wide research utility, are routinely generated, and

in general are produced for spatially and/or temporally

extensive subsets of the data, are to be considered standard data products. All EOS instruments must have standard Level 1 data products, and most will have standard

Level 2 data products. Some EOS Interdisciplinary Science Investigations will also generate standard data products. Specifications for the set of standard data products

to be generated will be reviewed continually by the EOS

IWG and NASA Headquarters to ensure completeness and

consistency in providing a comprehensive science data

output for the EOS mission. Standard data products will

be produced at the DAACs or SIPSs.

Special Data Products – Data products that are generated as part of a research investigation using EOS data,

and that are produced for a limited region or time period,

or products that are not accepted as standard by the EOS

IWG and NASA Headquarters, are referred to as special

data products. Special data products will normally be generated at the investigators’ SCFs. Upon review and approval by independent peer review, EOS IWG, and NASA

Headquarters, special products may be reclassified later

as standard products, in which case the algorithms and

processing may migrate to the DAACs or SIPSs and be

placed under the appropriate configuration controls.

Level Definitions – The various levels of data referred to

in this document are identical to those defined by the

EOSDIS Data Panel in its report, and are consistent with

the Committee on Data Management, Archiving, and

Computing (CODMAC) definitions. For some instruIncluding the previous DAAC at the Marshall Space Flight

Center, which has since been closed. Some of its functions

have been taken over by the Global Hydrology Resource Center, other DAACs, and the NOAA SAA.

*
1999 EOS Reference Handbook EOS Data and Information System • 35

ments, there will be no Level 1B product that is distinct

from the Level 1A product. In these cases, the reference

to Level 1B data can be assumed to refer to Level 1A

data. Brief definitions follow:

• Level 0 - Reconstructed, unprocessed instrument/payload data at full resolution; any and all communications artifacts (e.g., synchronization frames, communications headers, duplicate data removed).

• Level 1A - Reconstructed, unprocessed instrument data

at full resolution, time-referenced, and annotated with

ancillary information, including radiometric and geometric calibration coefficients and georeferencing parameters (e.g., platform ephemeris computed and appended but not applied to the Level 0 data).

• Level 1B - Level 1A data that have been processed to

sensor units (not all instruments will have a Level 1B

equivalent).

• Level 2 - Derived geophysical variables at the same

resolution and location as the Level 1 source data.

• Level 3 - Derived geophysical variables mapped on

uniform space-time grid scales, usually with some

completeness and consistency.

• Level 4 - Model output or results from analyses of

lower level data (e.g., variables derived from multiple

measurements).

References

Asrar, G., and H.K. Ramapriyan, 1995: Data and Information System for Mission to Planet Earth. Remote Sensing Reviews, 13, 1-25.

National Research Council, 1994: Panel to Review EOSDIS Plans: Final Report, National Academy Press, Washington D.C.

National Research Council, 1995: A Review of the U.S.

Global Change Research Program and NASA’s Mission

to Planet Earth/Earth Observing System, National Academy Press, Washington D.C.

Price, R.D., M.D. King, J.T. Dalton, K.S.Pedelty, P.E.

Ardanuy, and M.K. Hobish, 1994: Earth Science Data for

all: EOS and the EOS Data and Information System. Photogrammetric Engineering and Remote Sensing, 60, 277-

285.

Schwaller, M.R., B. Krupp, and W. North, 1996: Science

Data Plan for EOSDIS, Document Version 4. (See URL:

http://spsosun.gsfc.nasa.gov/spso/sdp/sdphomepage.html

for updates.)

EOSDIS URL

http://eos.nasa.gov/eosdis
1999 EOS Reference Handbook Data and Information Policy • 37

NASA Earth Science Enterprise Statement on Data Management

facture, assembly, operation, use, repair, testing, maintenance, or modification of a product, such as a data collection system (e.g., a satellite, aircraft, or ground system).

Principles

This Statement elaborates on Executive Branch and other

legal guidance for data management by the Earth Science

Enterprise. The following eleven statements summarize

the main principles drawn from that guidance.

1. NASA shall plan and follow data acquisition policies that ensure the collection of long-term data sets

that will satisfy the research requirements of the Earth

Science Enterprise.

2. NASA is committed to the full and open sharing of

Earth Science data obtained from U.S. Governmentfunded and -owned systems with all users as soon as

such data become available. All Earth System Enterprise missions, projects, and grant proposals shall include data management plans to facilitate implementation of this principle.

3. For data from government-owned or -funded systems,

NASA will enforce a principle of non-discriminatory

access so that all users within the same data-use category will be treated equally. Preferential treatment

for U.S. government users and their affiliates will be

allowed only where expressly permitted by law.

4. NASA shall make data from the Earth Science Enterprise available at a reasonable price to facilitate

access and encourage use. Data from NASA and its

U.S. government partners shall be priced at the cost

of dissemination or, in cases where such pricing

would unduly inhibit use, below that cost. For data

from industry and foreign partners in the Earth Science Enterprise, pricing and access policies shall be

established by negotiation between NASA and the

relevant Earth Science Enterprise provider and system operator. NASA will seek to ensure pricing and

Data and Information

Policy

Preamble

The Earth Science Enterprise (formerly Mission to Planet

Earth) was established to use the advanced technology of

the National Aeronautics and Space Administration

(NASA) to understand how the land, oceans, atmosphere,

ice caps, and life forms interact as a system in influencing climate change. To accomplish this, NASA is flying a

series of Earth Observation System (EOS) satellites that

will take 24 different measurement suites important to

Earth Science research. Additional data will be taken from

smaller, more narrowly focused satellite missions. The

unprecedented volume of data expected from these missions will be collected, processed, and distributed by

NASA’s EOS Data and Information System (EOSDIS).

It is the intent of the Enterprise to promote open access to its data by the general public, including the academic and industry communities. This is a fundamental

feature of the program. Allowing open and timely availability to Enterprise data is expected to accelerate the

progress of climate-change research. As a consequence,

more information will be available to policymakers to

make critical decisions relating to environmental quality,

land-use management, and other key policy areas. In addition, this approach should also help promote the development of practical applications and commercial products and services derived from Enterprise-related data and

technology.

This Statement on Data Management (Statement) is

intended to guide the management of scientific data from

the Enterprise. The principles set forth in this Statement

are intended to advance the goals, mission, and vision of

the Enterprise and encourage consistent treatment of data

management issues across the Enterprise. They are consistent with existing statutes, federal executive orders, and

NASA’s own established policies.

For the purposes of this Statement, the term “data”

shall mean the research data generated or acquired by the

Earth Science Enterprise to meet Enterprise goals as outlined in the NASA Strategic Plan. This term shall not include so-called technical data, i.e., specific information

required for the design, development, production, manu-
38 • Data and Information Policy 1999 EOS Reference Handbook

access policies consistent with the principles in this

Statement.

5. All data required for long-term global change research

shall be archived. Data archives shall include easily

accessible information about the data holdings, including quality assessments, supporting relevant information, and guidance for locating and obtaining

data.

6. Where cost-effective, NASA shall make purchases

of commercial data to meet the scientific objectives

of the Earth Science Enterprise. Data purchase arrangements should, at a minimum, permit appropriate use, distribution, and duplication of the data for

Earth Science Enterprise purposes by all researchers

affiliated with the Earth Science Enterprise. NASA

may purchase data on behalf of, and through, other

federal agencies for research and investigation purposes.

7. For each cooperative activity with industry, domestic or foreign, NASA shall seek agreement on all

major data-management and distribution issues during the project-definition phase. The respective contributions of the parties to the activity shall be considered in allocating rights and control over results

from the activity. NASA shall seek to ensure meaningful use of the data for Earth Science Enterprise

purposes by all researchers affiliated with the Enterprise.

8. NASA shall engage in ongoing cooperation with other

federal agencies, particularly those involved with

space-based activities or Earth Science research, to

increase the effectiveness and reduce the cost of the

Earth Science Enterprise. This interagency cooperation shall include: sharing of data from satellites and

other sources, mutual validation and calibration of

data, and consolidation of duplicative capabilities and

functions.

9. NASA shall, in compliance with applicable federal

law and policy, negotiate and implement arrangements with its international partners, with an emphasis on meeting the Nation’s own data acquisition, distribution, and archival needs.

10. NASA may allow for exceptions to the guidance contained in this Statement on a case-by-case basis where

permitted by law and in furtherance of the public interest.

11. NASA shall review and, if warranted, update this

Statement as part of the biennial review of the Earth

System Enterprise.

Statement of Principles and Explanation

1. NASA shall plan and follow data acquisition policies

that ensure the collection of long-term data sets that

will satisfy the research requirements of the Earth Science Enterprise.

The success of the Earth Science Enterprise depends on

data acquisition practices that will enable the collection

of a comprehensive global, long-term data set to address

the research requirements of the Earth Science Enterprise.

NASA adheres to the following principles regarding data

acquisition:

• Data from satellites and other data sources will be

acquired according to priorities recommended by

Earth Science Enterprise participants and confirmed

by the Associate Administrator for the Earth Science

Enterprise.

• Where site-specific (rather than global) observations

are made, data acquisitions will be conducted on a

demand basis. In these cases, data will only be taken

where there is: a) an identified user who has requested

and will analyze the data or b) recognition of a future

Earth Science Enterprise need for the data.

• The level of processing and preprocessing will be

dictated by the scientific requirements of the Earth

Science Enterprise, using peer-reviewed algorithms.

2. NASA is committed to the full and open sharing of

Earth Science Data obtained from U.S. Governmentfunded and -owned sensors with all users as soon as

such data become available. All Earth System Enterprise missions, projects, and grant proposals shall include data-management plans to facilitate implementation of this principle.

NASA’s Earth Science Enterprise is a bold effort to apply

advanced satellite and computing technologies to answer

fundamental questions about how the land, seas, air, and

life interact as a system and how human activity impacts

our environment. To meet this challenge, there must be

full and open sharing of the data from the Earth Science

Enterprise with the research community, private industry, academia, and the general public. The greater the availability of the data, the more quickly and effectively the

user community can utilize the information to address

basic Earth Science questions and provide the basis for

developing innovative practical applications to benefit the

general public.

Under most circumstances, the full suite of government-owned data sets within the Earth Science Enterprise

shall be made available to all users, with no user or group
1999 EOS Reference Handbook Data and Information Policy • 39

of users receiving a period of exclusive access. Access

will not be limited to the scientists, managers, or principal investigators working within the Earth Science Enterprise, but will be extended to the full scientific community and the general public. This principle applies to

all Earth Science Enterprise activities, including satellite

missions, field campaigns, and grants.

There may be practical impediments to providing

timely access to Earth Science Enterprise data held by

certain user groups, particularly data used in smaller

projects at the principal investigator level. These projects

may lack the time, staff, and resources to ensure the earliest public availability of their data product. Nevertheless, even in such difficult cases, NASA is committed to

providing the earliest feasible data distribution, provided

that the requester pays for the marginal cost of dissemination. Further, NASA shall require, in advance, data-management plans for all Earth Science Enterprise missions,

projects, and grant proposals to help assure that sufficient

resources are available for data management at all Earth

Science Enterprise levels.

3. For data from government-owned or -funded systems,

NASA will enforce a principle of non-discriminatory

access so that all users within the same data-use category will be treated equally. Preferential treatment

for U.S. government users and their affiliates will be

allowed only where expressly permitted by law.

NASA is committed to providing access on a non-discriminatory basis to all types of scientific data from the

Earth Science Enterprise, neither favoring or disfavoring

any user or class of users. Non-discriminatory access shall

be a requirement for any mission in which NASA resources are invested. That principle is already specifically

mandated for unenhanced data from government satellite

systems by the Land Remote Sensing Policy Act of 1992,

15 U.S.C. §5601 et seq., which specifically requires that

such data be made available to all users on a non-discriminatory basis. Section 501(a) of that Act states:

Except as provided in subsection (b) of this section,

any unenhanced data generated by the Landsat system or

any land remote-sensing system funded and owned by

the U.S. Government shall be made available to all users

without preference, bias, or any other special arrangement

[except on the basis of national security concerns] regarding delivery, format, pricing, or technical considerations

which would favor one customer or class of customers

over another.

However, subsection (b) of Section 501 does allow

for preferential treatment for the U.S. government and its

affiliated users provided that the data from these government satellite systems are used for non-commercial purposes.

For the purposes of this Statement, the term “nondiscriminatory basis” shall mean that all users in a clearly

defined data-use category can obtain data on the same

terms and conditions, and the categories are defined in a

such a way that potential users will be included in each

category.

4. NASA shall make data from the Earth Science Enterprise available at a reasonable price to facilitate access and encourage use. Data from NASA and its U.S.

government partners shall be priced at the cost of dissemination or, in cases where such pricing would inhibit use, below that cost. For data from industry and

foreign partners in the Earth Science Enterprise, pricing and access policies shall be established by negotiation between NASA and the relevant Earth Science

Enterprise provider and system operator. NASA will

seek to ensure pricing and access policies consistent

with the principles in this Statement.

Cost can be one of the greatest barriers to broad access to

data by the general scientific community, as well as the

public and private sectors. For that reason, making data

available at a reasonable cost is necessary to facilitate

scientific and other uses of the agency’s Earth Science

data. Accordingly, within the limits of current law, NASA

will endeavor to make data available at a price that does

not unduly inhibit its use.

For all data from NASA and other U.S. government

sources, the data will be made available, without restriction, at not more than the cost of dissemination, without

regard to the intended use of the data. Applicable federal

law and policy allow the federal government to charge

less than the cost of dissemination if the true cost inhibits

use of the data. NASA may, under special circumstances

as determined by the Associate Administrator or his designee, provide data to users at a nominal cost or no cost

where at-cost pricing would inhibit use. NASA appreciates that below-cost pricing may, in some cases, have the

potential to impair the ability of federal agencies to defray their operational costs and encourage users to request

more data than they actually need. Therefore, in deciding

whether to permit below-cost pricing in particular cases

or situations, the Associate Administrator shall carefully

weigh the benefits of the discount pricing to the user community against the potential costs to affected federal agencies.

It should be emphasized that, since data must be distributed on a non-discriminatory basis, all data products

must be available to all persons in the same data-use category at the same price. However, this requirement does

not preclude traditional pricing arrangements, such as volume discounts, so long as these arrangements are offered

on a non-discriminatory basis.

For data acquired from industry and foreign partners

in Earth Science Enterprise activities, a pricing and access policy will be negotiated with the relevant data provider and system operator. NASA will seek to ensure con-
40 • Data and Information Policy 1999 EOS Reference Handbook

sistency in negotiated pricing and access policies. In that

regard, pricing of data from commercial and international

partners shall be guided by the applicable provisions of

this Statement concerning commercial data purchases,

cooperative activities with industry, and international cooperation.

5. All data required for long-term global-change research

shall be archived. Data archives shall include easily

accessible information about the data holdings, including quality assessments, supporting relevant information, and guidance for locating and obtaining

data.

The archiving of long-term sets of global climate data is

critical for the meaningful study of Earth science and the

understanding of important environmental and climate

questions. Archives must provide easily accessible information about data holdings, including descriptive

metadata, quality assessments, supporting ancillary information, and assistance in locating and obtaining the data.

Each Earth Science Enterprise data set shall be subject to peer review to determine its merit for long-term

archiving. In the event that long-term archiving is deemed

appropriate, NASA shall seek guidance from Government

agency partners to determine if such requirements can be

most effectively met through interagency cooperation.

Consideration for long-term archiving shall include:

a) all data acquired by, or in support of, Earth Science

Enterprise-funded research projects; b) all data acquired

systematically by Earth Science Enterprise-funded missions for the purpose of documenting long term variability; and c) all accessible data concerning natural disasters

and other extraordinary events identified by the Earth

Science Enterprise (e.g., volcanic eruptions, floods, and

forest fires).

The Earth Science Enterprise shall not normally

archive data taken systematically for the purpose of documenting long-term variability if those data are already

being archived by a partnering agency such that long-term

access by NASA is assured. This principle shall apply to

data from NASA missions as well as joint missions undertaken with another agency or institution, either domestic or foreign. However, NASA may decide to archive

such data if it receives a specific request and, upon agency

review of the request against NASA’s mission, that request is granted. Further, should the archiving institution

decide to close its archive, the Earth Science Enterprise

may consider the acquisition of all or part of the archived

data, but shall not make such acquisition unless it is costeffective and satisfies NASA’s scientific requirements.

6. Where cost-effective, NASA shall make purchases of

commercial data to meet the scientific objectives of

the Earth Science Enterprise. Data purchase arrangements should, at a minimum, permit appropriate use,

distribution, and duplication of the data for Earth Science Enterprise purposes by all researchers affiliated

with the Earth Science Enterprise. NASA may purchase

data on behalf of, and through, other federal agencies

for research and investigation purposes.

NASA’s Commercial Strategy for the Enterprise states

that the agency shall “seek cost-effective science data

opportunities that meet the science objectives of the Earth

Science Enterprise.” In implementing this goal, NASA

shall—

• establish rights to distribute proprietary science data

purchased from commercial sources (rather than acquired through Earth Science Enterprise capabilities)

according to terms mutually acceptable to NASA and

the commercial sources coming as close to NASA’s

goal of non-discriminatory access as possible

• seek out data purchase arrangements with commercial sources where NASA is not the dominant customer over the long term

• act as a data purchasing agent for other federal agencies for research and investigation purposes and encourage other agencies to serve as purchasing agents

for NASA for such purposes

These principles will serve the scientific goals of the

agency and the federal government, as well as the public

interest. In the long run, such commercial data purchases

could potentially reduce agency costs by precluding the

need to design, develop, and launch spacecraft to collect

needed Earth science data from space and streamlining

data acquisition procedures and procurement processes.

Eventually, the evolution of a vigorous commercial space

data industry may enable the collection and access of more

Earth Science data than is gathered today, with benefits

for NASA and other potential customers derived from

more-competitive pricing and broader data selection.

In entering into data purchase arrangements, NASA

shall negotiate data purchase arrangements which, at a

minimum, permit appropriate use, distribution, and duplication by Earth Science Enterprise researchers for science purposes. Such researchers include: a) researchers

affiliated with the Earth Science Enterprise through interagency data exchanges, grants, and other formal mechanisms and b) researchers in the international community

with whom NASA has formal data- exchange arrangements or informal understandings. NASA shall also seek
1999 EOS Reference Handbook Data and Information Policy • 41

to negotiate terms that would allow the release of data to

users outside the Earth Science Enterprise researcher community, particularly for scientific, educational, and other

non-commercial uses, at the cost of dissemination. NASA

shall seek agreement with the data provider on the degree

to which the public will be allowed access to data via the

Internet.

The government has a duty to facilitate access to

publicly funded data—the more the federal investment,

the greater is the government’s duty to preserve or retain

broad access to data. Where the U.S. taxpayers, through

the federal government, have made a considerable investment in the observing system or the data product, unreasonable restrictions on use or availability by federal government agencies or their affiliates will not be accepted.

7. For each cooperative activity with industry, domestic

or foreign, NASA shall seek agreement on all major

data management and distribution issues during the

project definition phase. The respective contributions

of the parties to the activity shall be considered in allocating rights and control over results from the activity. NASA shall seek to ensure meaningful use of the

data for Earth Science Enterprise purposes by all researchers affiliated with the Enterprise.

The Enterprise regularly engages in cooperative activities with industry partners, domestic and foreign, which

may take many forms. From the perspective of the Earth

Science Enterprise, the ultimate goal of such cooperation

is to obtain cost-effective, scientifically meaningful data

to help meet Enterprise objectives. Therefore, the management and distribution of data from such cooperative

projects must be a central issue in the project definition

phase, and agreement on these matters should be achieved

before the projects are undertaken.

With these interests in mind, NASA shall adhere to

the following principles regarding data from joint missions and projects with industry:

All matters pertaining to data management, particularly data rights and data distribution responsibilities, shall

be resolved between NASA and the industry partner prior

to undertaking the cooperative NASA-industry activity.

NASA shall endeavor to negotiate agreements with the

industry partner to assure as broad an access to data from

the cooperative activity as possible. NASA shall define

the distribution, use, and archiving requirements for each

mission in advance and ensure that the agreement with

the commercial partner meets those needs. The respective contributions of the partners should be taken into

account in allocating rights and control to the results of

the cooperative activity. In cases where data are provided

on different terms for commercial and non-commercial

use, NASA should encourage the commercial partner to

be responsible for meeting the needs for commercial use

and should focus agency resources on meeting the research

and applications community requirements associated with

the Earth Science Enterprise’s mission. NASA shall assure meaningful use of data from the cooperative activity

for Earth Science Enterprise purposes by all researchers

affiliated with the Earth Science Enterprise. This includes

access to raw data as part of the scientific peer review

process.

8. NASA shall engage in ongoing cooperation with other

federal agencies, particularly those involved with

space-based activities or Earth Science research, to

increase the effectiveness and reduce the cost of the

Earth Science Enterprise. This interagency cooperation shall include: sharing of data from satellites and

other sources, mutual validation and calibration of

data, and consolidation of duplicative capabilities and

functions.

NASA continues to join with other federal agencies in

cooperative activities that advance the goals of the Earth

Science Enterprise. To maximize the benefit of this cooperation, NASA seeks input from cooperating agencies

when determining requirements and priorities for data

acquisition. In advancing the interests of the Earth Science Enterprise, NASA provides its federal agency partners with access to Earth Science Enterprise data. Further, NASA supports interoperability of systems and

compatibility of standards to facilitate data sharing and

exchanges. Finally, NASA cooperates with other federal

agencies in developing the most cost-effective policies

for long-term data archiving.

9. NASA shall, in compliance with applicable federal law

and policy, negotiate and implement arrangements

with its international partners, with an emphasis on

meeting the Nation’s own data acquisition, distribution, and archival needs.

Cooperative activities with international partners often

present unique circumstances because of the different laws

and policies that govern each country. The management

of the data resulting from international cooperative

projects is ultimately determined by respective project

participants, whose goals, policies, and constraints may

be quite different. Nevertheless, in negotiating with its

foreign partners, NASA will seek to reach agreements and

understandings that are in harmony with applicable federal law and policy, as well as the principles contained in

this Statement, and meet the needs of the agency.

When entering into any international project, NASA

must ensure that its own data acquisition, distribution,

and archival needs are defined and met by the terms of

the agreement. In general, international agreements in-
42 • Data and Information Policy 1999 EOS Reference Handbook

volve no exchange of funds, with each party making inkind contributions of products or services. The benefits

to NASA from these arrangements may come in several

forms, but typically access to valuable scientific data is

one of the primary incentives for agency involvement.

Accordingly, it is critical that these agreements explicitly

address data policy, specifically each party’s rights and

responsibilities for data acquisition (including tasking and

operations), distribution, and archiving.

All international agreements should clearly address

basic questions regarding the rights and responsibilities

of the parties with respect to:

• Data acquisition and tasking. If data acquisition is

not global and continuous, who decides when the instruments are on, and where the data are transmitted

to the ground and collected? Who pays for the operational activities?

• Data distribution and use. Who may access the data,

on what terms, through what facilities, using what

standards? Whose consent is required, if any, for access?

• Data archival. What data will be archived and for

how long, at whose expense, in what facilities, and

under what conditions? Who has access, and on what

terms, to data in the long-term archive? How are data

eventually disposed of?

Given the investment of federal government resources in

cooperative missions, NASA should endeavor to ensure

that all data are available to all users under defined conditions (i.e., any user should be able to determine what

data exist and to access them in a reasonable manner,

whether directly or through a third-party distributor). This

principle should ensure nondiscriminatory access in the

sense that no user is denied access to data (except for

reasons of national security or public safety). In general,

for missions involving significant NASA investment,

NASA shall insist that a long-term archive for mission

data be defined and that provisions are made for its funding.

As a minimum requirement for any mission, NASAaffiliated users should be able to obtain and use data from

cooperative missions. Their rights should be defined

broadly enough to include applications demonstrations

as well as more basic research investigations, and should

not be limited to NASA-funded investigations, since

NASA conducts cooperative science with foreign scientists and with investigators funded by other U.S. Government agencies such as the National Science Foundation.

The relevant Earth Science Enterprise and project science

leaders need to be part of the agreement and negotiating

process to ensure that specific terms are included in the

international agreements to promote the realization of

mission objectives. Furthermore, access to data should

be made as broad and inexpensive as possible to facilitate maximum utilization by the scientific community.

10. NASA may allow for exceptions to the guidance contained in this Statement on a case-by-case basis where

permitted by law and in furtherance of the public interest.

The guidance in this Statement with regard to open, nondiscriminatory public access to Earth Science Enterprise

data is fundamental to the mission of the Enterprise. Nevertheless, NASA recognizes that, to the extent permitted

by law, it may be in the public interest for the Associate

Administrator to grant exceptions from the principles in

this Statement on a case-by-case basis. Past experience

suggests most cases in which exceptions might be entertained would likely involve either: a) data acquisitions

from commercial sources or joint missions with industry

or b) international partnerships. In these categories of

cases, it is sometimes determined that the departures from

agency policy are outweighed by the value of the data,

foreign policy, or public policy considerations.

With regard to acquiring data from commercial

sources, it may be necessary to accept seller-imposed restrictions on the use and distribution of acquired data that

would not be appropriate for government-generated data.

For example, in one past case, a commercial provider contracted to sell remote-sensing data to NASA on the condition that: a) the data be used exclusively for research

purposes and b) the data be provided to NASA on a twoto-four week delay (to protect commercial sales of realtime data) except where there is a compelling research

requirement for real-time use by specified users.

Data acquired through data exchanges or joint missions with foreign partners may also require acceptance

of restrictions on data use and distribution in conflict with

NASA policy. In international arrangements, where the

non-U.S. party has made a substantial investment in the

joint activity, that party may have more negotiating leverage to insist on a restrictive data policy than NASA

desires. In such situations, if, on balance, the activity still

advances NASA’s mission goals, a decision could be made

to proceed nonetheless. To that end, past agency practice

can be instructive in reviewing individual cases. For instance, in one joint satellite mission involving NASA and

a foreign space agency, the governing Memorandum of

Understanding gave designated mission investigators a

period of three months of exclusive access to the satellite

data. Following the period of exclusive access, the data

would be placed in an archive and made available to the

general public at no more than the cost of filling the user

request.

In every case where an exception is requested, NASA

will attempt to adhere to the principles in this Statement

as closely as possible and will balance the right of the

public to open non-discriminatory access to scientific in-
1999 EOS Reference Handbook Data and Information Policy • 43

formation from federal agencies against the asserted interests of the parties requesting the exception.

11. NASA shall review and, if warranted, update this

Statement as part of the biennial review of the Earth

System Enterprise.

NASA will regularly review and, if warranted, update this

Statement as part of NASA’s comprehensive biennial review of the Earth System Enterprise. Review of this Statement will examine whether its principles require revision

to reflect changes in applicable law, Administration policy,

NASA policy, or relevant facts and circumstances. The

review shall also examine possible revisions to this Statement that might improve the Earth Science Enterprise’s

data management and its ability to carry out its goals and

missions. The Associate Administrator must approve any

revisions to the Statement.

References

• The National Aeronautics and Space Act of 1958, as

amended, 42 U.S.C. §2451, et seq.

• The Land Remote Sensing Policy Act of 1992, 15

U.S.C. §5601, et seq.

• The Paperwork Reduction Act, 44 U.S.C. §3501, et

seq.

• The Freedom of Information Act, as amended, 5 U.S.C.

§552 (1994), amended by P.L. 104-231.

• OMB Circular A-130 (February 8, 1996)

• National Space Policy (NSTC-8, September 19, 1996)

• Presidential Directive (NSPD-7), Space-Based Global

Change Observation (May 28, 1992)

• Statements on Data Management for Global Change

Research (Office of Science and Technology Policy,

July 1991)

• Mission to Planet Earth Commercial Strategy (March

1997)

• IEOS Data Exchange Principles
1999 EOS Reference Handbook Pathfinder Data Sets • 45

finder effort involves NASA, Environmental Protection

Agency (EPA), and USGS.

Also in 1992, NASA’s Scanning Multichannel Microwave

Radiometer (SMMR) data set was added as the first

NASA-only Pathfinder.

All initial Pathfinder data sets involved space-based observations, and were subject to the following requirements:

1) stable calibration of the raw data should be attainable;

2) when data from multiple copies of instruments are involved, consistent calibration among instruments in a

series should be possible; and

3) archiving may include transferring the data to a more

accessible medium.

One or more Science Working Groups (SWGs) were

formed for each of the identified interagency data sets to

provide recommendations for specific Pathfinder activities. SWG reports to the involved partner agencies consist of the following:

• Determination of the scientific needs for Pathfinder

data and how these needs translate into specific products.

• Identification of community-consensus algorithms

for generating Pathfinder products and determination

of the data required to generate these products.

• Recommendation on how these products are to be

generated, validated, stored, and maintained.

• Identification of the data services required by users

of Pathfinder data (including catalog and browse

functions, metadata, and data access).

Initial Pathfinder reprocessing of the above data sets was

completed using community-consensus algorithms as recommended by the applicable designated SWGs or a similar process. The resultant data sets were then made available at responsible DAACs, and through the EOSDIS

Version 0.

Pathfinder Data Sets

The Pathfinder data set concept was initiated very early

in the EOS Program by NASA Headquarters in answer to

the question “What can be done now to further global

change research?” Pathfinders were intended to provide

unprecedented access to consistent, large remote-sensing

data sets applicable to global change research prior to the

availability of data from the EOS satellites. From these

long time series of global and/or regional data sets, higher

level geophysical products were or could be derived in

support of U.S. Global Change Research Program

(USGCRP) objectives.

The main goal of the Pathfinder Program is to make

research-quality global change data sets easily available

to the Earth science community. In addition, experience

gained in processing/reprocessing, archiving, and distributing standard scientific data products was expected to

prove a boon as well. As scientific understanding developed and product retrieval algorithms were improved, it

was thought that the data sets might require additional

reprocessing, which would be provided by this program.

Phase 1: 1990-1994

In October 1990, NOAA and NASA signed an agreement

establishing three joint NASA/NOAA Pathfinders to be

generated from existing NOAA data sets, as follow:

• Advanced Very High Resolution Radiometer

(AVHRR) Global Area Coverage (GAC) data held

by NOAA.

• Television and Infrared Observation Satellite

(TIROS) Operational Vertical Sounder (TOVS) data

held jointly by NOAA and NASA.

• Geostationary Operational Environmental Satellite

(GOES) data held by the University of Wisconsin

under contract with NOAA.

In 1991, the Special Sensor Microwave/Imager (SSM/I)

data set was added as a NASA/NOAA Pathfinder. SSM/I

data are currently archived by NOAA under a Shared Processing Agreement with the Navy and the Air Force.

Landsat Multispectral Scanner (MSS) and Thematic

Mapper (TM) data held primarily by USGS/EDC were

added to the Pathfinder activity in 1992. The Landsat Path-
46 • Pathfinder Data Sets 1999 EOS Reference Handbook

Phase 2: 1995-2000

A NASA Pathfinder Research Announcement was issued

in December 1994 in order to continue, rationalize, and

strengthen ESE’s support of data product generation activities. Interagency cooperation and international coordination were encouraged. Proposals received in March

1995 were evaluated through a scientific and technical

peer review, and also were reviewed for scientific and

programmatic relevance to the research interests of

NASA’s ESE and the USGCRP. The continuation of the

Pathfinder program reflected the ESE view that data quality and availability are key to successful Earth system

science.

The Pathfinder NRA included a call for algorithm

development proposals as well as product generation proposals. ESE used the NRA as a mechanism to fill a perceived enterprise development gap between research

analysis with satellite data and a robust completed algorithm, including delivery of the completed science application software.

The second phase of the Pathfinder program underlined the importance of building long-time-series data sets,

and, in particular, of developing the concept of obtaining

measurement continuity through a change of primary instrumentation. The NRA narrative laid out the instrument

follow-on relationships of initial Pathfinder data sets and

data sets from other then-available instruments with thenupcoming NASA EOS and other ESE missions.

The second phase of Pathfinder Data Sets continues

the ongoing series of multidisciplinary AVHRR, TOVS,

GOES, and SMMR-SSM/I products. Second-phase

projects are also implementing transitional continuity in

algorithms and/or data sets for AVHRR and MODIS, and

SMMR-SSM/I and TRMM. Ocean heights are provided

from the multiple satellite-borne altimetry series from

SeaSat through TOPEX/Poseidon. The long-standing International Satellite Cloud Climatology Project (ISCCP)

won support, and a new initiative providing Antarctic mapping from Radarsat. Landsat land-cover initiatives have

also been continued through the land-cover program. The

Pathfinder Phase 2 will continue through fiscal year 2000

in order to make possible continuity of precursor data sets

with the Landsat 7, Terra, and EOS PM instrument data

sets.

Beyond the Year 2000

Pathfinder Data Sets currently comprise the backbone of

available large volume, consistent satellite records. Innovative research using these data sets continues to appear

in the peer-reviewed literature. The ESE Research Division is currently (as of this printing) exploring launching

an updated extra-mission-specific data program beyond

the year 2000, perhaps newly named.
1999 EOS Reference Handbook Earth Science Information Partners and the Working Prototype Federation • 47

evolve processes to make Earth system science data easy

to preserve, locate, access, and use for all beneficial applications, including research, education, and commercial, many of which may cross Federation membership.

Through twelve Type 2 and twelve Type 3 WP-ESIP

projects selected under two Cooperative Agreement Notices in December 1997, ESE, with the community, is exploring new and innovative approaches to ESE’s data and

information system and services in support of Earth system science, and is endeavoring to contribute to the implementation of an increased functionality for environmental data and information search, access, order, and retrieval

within the National Information Infrastructure. The evaluation of the federation concept has been initiated beginning with this limited set of prototype projects operating

in a federated, rather than a centrally-managed architecture. This future-oriented strategy is just becoming possible because of the tremendous pace of information technology innovation, and can be seen as comparable to the

move toward Principal Investigator-driven spacecraft.

The Type 2 ESIPs concept is, in a way, a further development of the evolution of the Pathfinder Data Sets

concept, with the additional feature of providing the stewardship for the near-term storage, distribution, and user

services portion of the data-product management cycle.

The present Type 2 WP-ESIPs also have the objective of

enhancing innovation and creativity in the provision of

environmental information services, and of identifying

and testing new or emerging information technologies,

techniques and/or approaches which offer promise of significantly reducing the future costs of ESE’s data and information system and services. It is hoped that marrying

these science and technology objectives within the Type

2 WP-ESIPs will promote very close teamwork and interactions between scientists and system designers and

implementers, resulting in highly effective science data

centers.

Type 3 ESIPs will be responsible for extending the

benefits of NASA Earth science data and information beyond basic research to a broader user community including private industry, value-added companies, state and

local governments, and non-profit organizations. NASA

required that all for-profit organizations must cost-share

to at least the 50% level. Successful Type 3 ESIP organizations are expected to become financially self-sustaining by the end of their nominally 5-year projects. The

participation of Type 3 WP-ESIPs in the Working ProtoEarth Science Information Partners

and the Working Prototype Federation

Scientists of the future will be both producers and users

of data—from their desktops. This long-term vision is

perhaps the impetus for the 1995 National Research Council (NRC) idea of Federation.

The move to interdisciplinary Earth science interests

is expected to lead increasingly to innovative, multi-sensor and multi-source product generation for both science

and applications. A model to facilitate best the public availability of data and information from these geographically

dispersed providers, including intermediate availability

of multi-source products to higher-level data producers,

is needed to effect the emergence of an Environmental

Information Economy. The Environmental Information

Economy can be defined as the collective enhancements

needed within the National Information Infrastructure to

render it capable of providing for the routine exchange of

environmental data and information. This may imply a

concerted agreement and evolution process within the

community of environmental information providers and

users.

ESE embarked upon the data and information system-related Working Prototype Federation in response to

the NRC recommendation that the Agency shift appropriate data and information functions to a federation of

competitively selected Earth Science Information Partners (ESIPs), a concept which NASA endorses.

NASA concluded that ESIPs can best be described

as belonging to three types. Type 1 ESIPs are responsible

for standard data and information products whose production, publishing/distribution, and associated user services require considerable emphasis on reliability and

disciplined adherence to schedules. Type 2 ESIPs are responsible for data and information products and services

in support of Earth system science (other than those provided by the Type 1 ESIPs) that are developmental or

research in nature, where emphasis on flexibility and creativity is key to meeting the advancing research needs.

Type 3 ESIPs are those providing data and information

products and services to users beyond the global change

research community who enter into joint endeavor agreements with OES.

NASA and the NRC agreed in 1996 that the appropriate way to initiate a federation of ESIPs was through

an evolutionary, prototyping process. ESE’s response was

to invest in a Working Prototype Federation (WP-Federation) of Working Prototype ESIPs (WP-ESIPs). The

objective of the WP-Federation is to experiment with and
48 • Earth Science Information Partners and the Working Prototype Federation 1999 EOS Reference Handbook

type Federation will test the flexibility and extensibility

of such a system.

ESE has resolved to make peer-review and competition a more-recurrent feature in all our projects, including our data centers’ activities. Because it is expected that

ESE will be moving to a more-distributed and flexible

data system approach, it is both timely and useful to examine where the best levels within the organization are

for making different types of salient decisions concerning data management. By their submission of proposals,

these projects expressed an interest in prototyping how a

move to a federated environmental data system might

occur.

WP-ESIPs attended an NRC Federation Workshop

in February of 1998. At that time, the Type 2 and Type 3

WP-ESIPs voted to invite the EOSDIS Distributed Active Archive Centers to join them in the WP-Federation

as Type 1 ESIPs.

WP-ESIP projects officially got underway in April

1998. The WP-Federation convened for the first time in

May of 1998. Early activities of the WP-Federation indicate that, rather than seeking wholesale system-wide solutions, WP-ESIPs plan to self-organize in partnerships,

to develop more-custom approaches to data access and

user services for associated more-targeted user communities. Clusters of Type 1, 2, and/or 3 ESIPs will form to

share data, scientific expertise and tools relevant to a particular science or application question. Since this initiative is implemented through working prototype data centers, which are all mandated to make their services available to all on a non-discriminatory basis, it is an initiative

in which ESE’s user communities can all participate.

Type 2 WP-ESIP Projects’ Titles and Project

Leaders

• “The Distributed Oceanographic Data System: A

Framework for Access to Scientific Data in the EOS

Federation,” led by Peter Cornillon, University of

Rhode Island, Narragansett.

• “The Earth System Science Workbench: A Scaleable

Infrastructure for ESIPs,” led by James Frew, University of California, Santa Barbara.

• “Seasonal to Interannual Earth Science Information

Partner (SIESIP),” led by Menas Kafatos, George

Mason University, Fairfax, VA.

• “Progressive Mining of Remotely Sensed Data for Environmental and Public Health Applications,” led by

Chung-Sheng Li, International Business Machines,

Yorktown Heights, NY.

• “A Web-Based System for Terrestrial Environmental

Research,” led by Berrien Moore, University of New

Hampshire, Durham.

• “ESP2Net: Earth Science Partners’ Private Network,”

led by Richard Muntz, University of California, Los

Angeles.

• “Evolution of Snow Pack in the Southwestern United

States: Spatial and Temporal Variability from a Remotely Sensed and In Situ Data Set,” led by James J.

Simpson, Scripps Institute of Oceanography, University of California, San Diego.

• “Tropical Rainforest Information Center,” led by

David L. Skole, Michigan State University, East Lansing.

• “An On-Demand Data Processing and Delivery System for Climate Studies Using Passive Microwave

Data Sets,” led by Roy W. Spencer, Marshall Space

Flight Center, Huntsville, AL.

• “A Landcover Earth Science Information Partnership,”

led by John R. G. Townshend, University of Maryland, College Park.

• “GPS Environmental & Earth Science Information

System: GENESIS,” led by Thomas P. Yunck, Jet Propulsion Laboratory, Pasadena, CA.

• “Improved Ocean Radar Altimeter and Scatterometer

Data and Atmosphere-Ocean Model Simulation for

Coastal and Global Change Studies,” led by Victor

Zlotnicki, Jet Propulsion Laboratory, Pasadena, CA.

Type 3 WP-ESIP Projects’ Titles and Project

Leaders

• “Institutionalizing MTPE Data for Land and Environmental Management,” led by Thomas Burk, University of Minnesota, St. Paul.

• “California Land Science Information Partnership,”

led by Gary Darling, California Resources Agency,

Sacramento.

• “Performing a Regional Assessment and Prototyping

Internet Accessible MTPE Products for the Upper Rio

Grande Basin,” led by Stanley Morain, University of

New Mexico, Albuquerque.

• “Integrating Environmental and Legal Information

Systems,” led by Konstantinos Kalpakis, University

Space Research Association (USRA), Greenbelt, MD.

• “A Public Access Resource Center (PARC) Empowering the General Public to Use EOSDIS Phase III

Operations,” led by George Seielstad, Upper Midwest
1999 EOS Reference Handbook Earth Science Information Partners and the Working Prototype Federation • 49

Aerospace Consortium (UMAC), University of North

Dakota, Grand Forks.

• “WeatheRoute,” led by Kevin Meagher, Reading Information Technology, Inc., Reading, PA.

• “MTPE Education Series,” led by Catherine Gautier,

Planet Earth Science, Inc., Santa Barbara, CA.

• “Integration and Application of MTPE Data and Information to the San Francisco Bay Area and Monterey

Bay Region,” led by David Etter, Bay Area Shared

Information Consortium (BASIC), Mountain View,

CA.

• “Museums Teaching Planet Earth,” led by Patricia

Reiff, Rice University, Houston, TX.

• “Terrain Intelligence Products from EOS Sensor Data,”

led by Douglas Kliman, MRJ Associates, Tucson, AZ.

• “NBC News and Information: Extending MTPE Data

to the World,” led by David Jones, WRC-TV4, Washington, DC.

• “MTPE-Derived Data Products for the Fisheries,” led

by Patrick Simpson, Scientific Fishery Systems, Inc.,

Anchorage, AK.
1999 EOS Reference Handbook EOS Data Quality: Calibration/Validation • 51

Data quality for EOS is sought and checked through comprehensive calibration and validation programs. The primary objectives of these programs are to characterize and

document the accuracy and precision of EOS observations and derived geophysical and biophysical products

over all relevant temporal and spatial scales. More specifically these two programs include: 1) radiometric calibration and characterization of EOS instruments; and 2)

validation of the observations and state variables, fluxes,

and parameters derived directly from EOS observations

or in conjunction with the data assimilation method(s)

and integrated Earth system models. These programs are

guided and coordinated by the EOS Calibration and Validation Scientists residing within the EOS Project Science

Office at Goddard Space Flight Center.

Calibration Program

In order to achieve the EOS goal of understanding the

Earth as a natural system, EOS will produce global, long

time series of remote-sensing data sets from multiple instruments on multiple platforms. The correct interpretation of scientific information from these data sets requires

the ability to discriminate between satellite instrument onorbit changes and changes in the Earth physical processes

being monitored. The ability to make this discrimination

on a pre-launch, post-launch, inter-instrument, and interplatform basis crucially depends on the calibration of the

instruments with respect to a set of recognized physical

standards or processes and on the careful characterization of instrument performance at the subsystem and system levels.

In EOS, calibration is the set of operations or processes used to determine the relationship between satellite instrument output values (i.e., voltages or counts) and

corresponding known values of a standard, expressed in

Systeme Internationale (SI) units. Characterization is the

set of operations or processes used to quantitatively understand the operation of an instrument and its response

as a function of the gamut of operating and viewing conditions experienced by the instrument on-orbit. The complete calibration of an EOS instrument requires and implies that the instrument be well-characterized. EOS instrument calibration and characterization are performed

both pre-flight and on-orbit.

There are three types of radiometric calibration activities currently being conducted as part of the EOS Calibration Program: 1) laboratory calibration prior to launch,

2) in-flight calibration with onboard calibrators, and 3)

vicarious calibration during the post-launch period. The

laboratory calibration activities focus on calibration of

individual instruments with traceability to radiometric

standards accepted by the national and international metrology community and implemented by organizations

such as the U.S. National Institute of Standards and Technology (NIST). This step also includes the intercalibration

of instruments that operate in the same region of the electromagnetic spectrum and that measure similar characteristics of the Earth system. For example, transfer radiometers are being used in round-robin intercomparisons

that enable the transfer of metrology scales, maintained

at national standards laboratories, to surface-imaging instruments such as ASTER, MODIS, and MISR that will

be launched on the Terra satellite. The inflight calibration

will utilize calibration lamps, reference panels with known

reflectivity/emissivity, deep space, and ratioing radiometers. The vicarious methods include the use of bright and

dark target scenes on Earth, coincident sub-orbital flights

of well-calibrated spectroradiometers over well-characterized Earth surfaces, and the use of the Moon as a stable

reference target that will be characterized from high-spectral-and-spatial-resolution measurements made from

ground-based observatories over the libration cycle of the

Moon.

The key components of the EOS Calibration Program are:

Pre-flight EOS Instrument Calibration

• Instrument Calibration Plans

• Calibration Peer Reviews

• Radiometric Measurement Comparisons

• EOS Calibration Panel

• Artifact Round-robins

Post-launch EOS Instrument Calibration

• On-orbit Platform Maneuvers (e.g., calibration attitude

maneuvers)

• The USGS- Lunar Radiometric Measurement Program

• Level 1B Validation (e.g., vicarious calibration) Campaigns

EOS Data Quality:

Calibration and Validation
52 • EOS Data Quality: Calibration/Validation 1999 EOS Reference Handbook

Current information concerning the EOS Calibration Program is available at the following website:

http://eos.nasa.gov/calibration/calpage.html

Validation Program

The goal of the EOS Validation Program is the comprehensive assessment of all EOS science data products.

Specifically, validation is the process of assessing, by independent means, the uncertainties of the data products

derived from the measurement system outputs. These

products are derived either directly from calibrated instrument measurables or in conjunction with data assimilation and Earth system models. Achievement of this goal

requires information related to the accuracy and precision of the instrument product and the knowledge of the

scales and conditions of interest to the users of the derived geophysical and biophysical data products.

In general, validation is accomplished by direct comparisons with independently obtained correlative measurements and by intercomparisons with independently derived satellite retrievals. Correlative measurements for

direct comparisons are obtained from ground-based networks, comprehensive ground-based test sites, and field

campaigns involving detailed studies of the geophysical

and biophysical processes. Airborne measurements using specifically designed EOS instrument simulators and

community airborne instruments play an essential role in

the field campaigns. Independently derived satellite retrievals for intercomparisons are obtained from observations by instruments on the same EOS platforms or by

instruments on other EOS platforms or non-EOS platforms.

The EOS instrument science teams are responsible

for validation of the algorithms and data products they

produce. Thus, members of the instrument science teams

identify the necessary steps required to validate their respective data products on specific space and time scales

and for various phenomenological/environmental settings.

Intercomparison of similar data products developed by

different instruments based on different techniques is

planned and conducted by the respective instrument science teams. For example, cross-comparison and validation of cloud products developed by CERES, MISR, and

MODIS instruments require close collaboration among

the responsible members of those science teams. The end

users of these products, e.g., interdisciplinary investigators, participate in validation activities to ensure that uncertainties and associated statistics provided for each product meet their requirements. In addition, the interdisciplinary and four-dimensional data assimilation teams will

validate their model results, based on remotely sensed and

in situ observations. Each Level-1 through Level-3 product will have an associated uncertainty estimate; this is

expected to include both a basic error estimate for that

product (long-term radiometric spectral and spatial resolution and accuracy) and time-based indications of larger

uncertainties that result from unusual conditions such as

volcanic eruptions and major desert-dust events.

The team validation activities occur in two basic

phases: pre-launch and post-launch. Pre-launch activities

include development and verification of algorithms and

characterization of uncertainties resulting from

parameterizations and their algorithmic implementation.

Post-launch activities include refinement of algorithms

and uncertainty estimates based on near-direct comparisons with correlative measurements and selected, controlled analyses or application implementations.

The EOS Validation Scientist organizes and coordinates the project-wide validation program and defines

guidelines, policies, and milestones. To facilitate effective communications and stimulate collaborative activities, timely workshops and scientific meetings are conducted. The Validation Scientist provides coordination

with other NASA and non-NASA programs, conducts

community reviews of team validation plans, and advocates the direct and supplemental support of team validation tasks. Examples of tasks that may require supplemental support include development of airborne simulators, participation in field experiments, acquisition of correlative measurements, and enhancement of databases

such as HITRAN. When necessary, NASA Research Announcements are issued to solicit the supporting and/or

enhancing activities.

Current information concerning the EOS Validation

Program is available at the following website:

http://eos.nasa.gov/validation/valpage.html
1999 EOS Reference Handbook Educational Programs • 53

Educational Programs

While the goal of NASA’s Earth Science Enterprise (ESE)

is increased scientific understanding, an important outcome of the program is education, in its broadest form.

One of the four goals of the program, as cited in its Strategic Plan, is to “foster the development of an informed

and environmentally aware public.” Within this context,

contributions by ESE to the advancement of public knowledge about the Earth are key to measuring the success of

the program.

NASA’s Education Framework

All formal NASA education activities are part of the

NASA Education Framework. This framework includes

three components: program content, education levels, and

implementation approaches. Program content reflects the

science and engineering efforts underway within NASA

and the enabling capabilities that support them. Education levels are divided between kindergarten through

fourth grade, fifth through eighth grade, ninth through

twelfth grade, and undergraduate, community college, and

graduate levels. The implementation approach defines the

purpose of the activity. The following categories represent the various implementation approaches used in

NASA:

Teacher preparation and enhancement – Programs are designed to enhance teacher/faculty knowledge and research

skills through exposure to the NASA mission, facilities,

and resources for use in the teaching enterprise.

Curriculum support – Efforts here create, utilize, and disseminate instructional products based on NASA’s unique

mission and resources in the areas of science, mathematics, and technology.

Student support – Student support provides research experiences for students at NASA and related sites, provides

experiences and exposure to NASA’s mission, including

science, mathematics, engineering, and technology, and

provides support to train students in the areas of science,

mathematics, and engineering.

Educational technologies – These are programs and products that develop and use advanced technologies for education including, but not limited to: Internet services, CDROM databases, live or taped video, computer software,

multimedia systems, virtual reality, educational technology research and development, databases, and dissemination systems.

Systemic change – Systemic activities typically involve

collaborative efforts with a range of partners, seeking to

enhance multiple aspects of the educational process.

Earth Science Enterprise Education Strategy

In support of the NASA education initiative, the Office

of Earth Science has worked with the Education Division

to establish a focused, sustainable education strategy. The

strategy includes all education programs and activities at

all ESE field centers and NASA Headquarters. Principles,

objectives, priority elements, and an implementation plan

are part of the overall strategy to insure that ESE has a

solid education program with the ability to grow.

Overriding principles have been established to consider when working to meet specific ESE education objectives:

• Education, in the broadest sense, is the ultimate product of ESE.

• We must, through our efforts, demonstrate relevance to

society.

• We must operate and work within NASA’s strategy for

education.

• We must focus implementation of a sustainable Earth

system science education program that is consistent with

externally imposed education standards.

• Scientists must continue and increase their involvement

in education.

• Teachers must be involved in the development and decision-making aspects of education activities.

• NASA strategy and programs must be coordinated (and

perhaps integrated) with other agencies/organizations.
54 Educational Programs • 1999 EOS Reference Handbook

• Attention to equity and diversity must be a component

in all ESE education activities.

• NASA provides the first level of translation for science

information and, when appropriate, leverages resources

of external groups for further translation.

These guiding principles define our approach to achieve

the following objectives:

- Train the next generation of Earth scientists to use an

interdisciplinary, Earth system science approach.

- Continue to educate and train educators as research

evolves and capabilities change.

- Raise awareness of policymakers and citizens to enable prudent policy determination regarding global

change.

- Improve science and math literacy.

- Improve interface between educators and scientists

and secure greater support by scientists for broad education efforts.

- Explore mechanisms to leverage the development of

materials and products, where reasonable, to increase

resources availability; increase the Earth-SystemScience knowledge base; and encourage the development of an external capability to translate scientific research into usable forms for a continuum of

customers.

Prioritization of educational activities is not a clear-cut

procedure. In order to meet the above objectives, a complement of activities, using the various implementation approaches, must be performed. However, there are certain

priority elements to consider when implementing a focused, sustainable program. We must maintain support

for graduate students and the establishment of curricula

in universities that pursue an interdisciplinary Earth system science concept, in the hope of establishing an educated community in the near term to analyze data from

the EOS missions and provide accurate information on

global change to policymakers. ESE must also educate

present and future educators if its efforts are to reach a

national, diverse population of students. A further priority will be continued encouragement to use technology in

pre-college activities as technology allows for increased

hands-on, interactive learning.

In order to prioritize education activities in ESE in

concert with the strategy objectives, a peer review process has been established to involve scientists and educators in the review of all proposals for educational activities submitted to ESE. ESE has also incorporated educational requirements in recent, relevant research announcements, such as:

• NASA Research Announcement: The Establishment of

Regional Earth Science Applications Centers

(RESACS) Triana - Concept for Earth-Viewing Satellite (AO-98-OES-02), and

• NASA Research Announcement: New Investigator Program (NIP) in Earth Science (NRA-98-OES-10)

In 1998, ESE sponsored the third annual Earth science

education product review. This review provides consistent assessment criteria for NASA Earth science education products and determines which new Earth science

education products are appropriate for production and

distribution by NASA for national audiences, and whether

for broad distribution or through targeted teacher workshops during 1998/1999. The review includes panels consisting of teachers, curriculum and instructional design

specialists, teacher trainers, and Earth system scientists.

It is not intended to replace testing and evaluation that

should be built into the product’s development; rather,

this review is one of the final steps before an ESE education product goes into national distribution by NASA.

NASA Centers, grantees, contractors and other

NASA-sponsored organizations are strongly encouraged

to include their outstanding ESE education products in

this annual review, which enables Earth science education products to be distributed throughout the NASA Educators Resource Center Network (ERCN) and at national

education conferences—reaching far greater audiences

than a single Center or organization would be able to undertake alone.

Successful completion of this review is also a requirement for a listing in the NASA ESE Catalog of Education

Programs and Resources, as well as a requirement for the

product’s inclusion in the ESE Education Products Training Workshop. A key principle of NASA’s ESE Education Strategy is that ESE education activities are developed within the broader context of NASA’s overall education program and strategy. A major component of

NASA’s education program is the Educator Resource

Center Network (ERCN), formerly known as the Teacher

Resource Center Network (TRCN). This annual workshop brings together representatives from the ERCN,

Aerospace Education Services Program (AESP), and the

Teaching from Space Program. Participants receive training in NASA ESE education products and commit to conducting a minimum of three teacher workshops using

NASA ESE education products. Their workshops introduce ESE education products to thousand of teachers

across the country.

Other NASA ESE education activities that support the

ESE Education Strategy are teacher and faculty enhancement activities such as:
1999 EOS Reference Handbook Educational Programs • 55

Faculty: Remote Sensing Core Curriculum Project and

the ACTES (Associate of Arts in Community Colleges for

Training in Earth Science) Project. (In-service) – Discover Earth teacher workshop for teachers of grades 5-12

and the Classroom of the Future’s graduate courses in

Earth system science, which have been developed for K12 teachers.

Pre-service – Pre-college teacher enhancement grants,

which were awarded to 12 colleges and universities to

develop and offer Earth system science workshops for

teachers-in-training.

Sponsoring student fellowships and other research opportunities, including graduate students – Earth System

Science Fellowships (see next section).

Undergraduate students – Undergraduate student enhancement grants, which were awarded to six colleges

and universities which are developing student research

opportunities in Earth system science for undergraduate

students.

Pre-college – Global Learning and Observations to Benefit the Environment (GLOBE) Program, in which students internationally are collecting environmental measurements, and the EarthKam Project, in which students

operate an Earth-observing camera onboard the Space

Shuttle. Systemic Change, including curriculum development at precollege and university levels, including the

Earth System Science Education (ESSE) Program for

undergraduate curriculum development and the NASAsponsored U.S. Global Change Education State Team

Projects, which are conducting K-12 curriculum development activities in twenty states.

Technology-based programs – Including developing CDROMs and WWW sites for disseminating information and

data from ESE missions.

NASA’s Earth Science Enterprise: 1998 Education Catalog – Information on NASA ESE education programs and

resources for all education levels. This publication is available at:

http://www.earth.nasa.gov/education/

ESE_Ed_Catalog_98/index.html

Earth System Science Fellowships

A primary student support activity at the higher education level is the Earth System Science Fellowship Program. This is the third year that NASA is combining the

financial support for the Earth science portion of its Graduate Student Researchers Program (GSRP), supported by

the NASA Education Division, and the Graduate Student

Fellowship in Global Change Research, supported by the

Office of Earth Science, to fund both M.Sc. and Ph.D.

applicants pursuing their graduate studies in the field of

Earth system science. The NASA Education Division

awarded a total of 51 Global Change Fellowships for the

1998/1999 academic year.

The program provides support for the following scientific areas: Seasonal-to-Interannual Climate Variability and Prediction; Long-term Climate Natural Variability and Change Research; Land-Cover and Land-Use

Change Research; Atmospheric Ozone Research; and

Natural Hazards Research and Applications. Applications

will be considered for research in atmospheric chemistry

and physics, ocean biology and physics, ecosystem dynamics, hydrology, cryospheric processes, geology, and

geophysics, provided that the specific research topic is

relevant to NASA’s Earth remote-sensing science, process studies, modeling and analysis in support of the U.S.

Global Change Research Program (USGCRP). NASA discourages submission of paleo-climate related applications

to this program.

Awards are made initially for one year and may be

renewed annually, no more than two additional years for

a total of three years, based on satisfactory progress as

reflected in academic performance and evaluations by the

faculty advisor. Three years is the maximum support a

student may receive in pursuing M.Sc. and/or Ph.D.

degree(s). For example, a student who has been supported

for three years to obtain her/his M.Sc. degree cannot apply for an additional three years of Ph.D. support. However, students who are in the second or third year of their

M.Sc. program may use the balance of the three years of

support remaining to complete their M.Sc. degree and to

initiate their Ph.D. research. In either case, the maximum

period of support is three years. The amount of the award

is $22,000/annum, which may be used to defray student’s

stipend, living and educational expenses, travel expenses

to scientific conferences, tuition, and fees.

Students admitted to or already enrolled in a fulltime M.Sc. and/or Ph.D. program at accredited U.S. universities are eligible to apply. Students may enter the program at any time during their graduate work. Students

may also apply in their senior year prior to receiving their

baccalaureate degree, but must be admitted and enrolled

in a M.Sc. and/or Ph.D. program at a U.S. university at

the time of the award. An individual accepting this award

may not concurrently receive other Federal funds, including funds from other Federal fellowships, traineeships,
56 Educational Programs • 1999 EOS Reference Handbook

or employment. However, NASA may allow an applicant

receiving Fellowship Supplements from other U.S. Federal agencies to cover expenses not covered by NASA’s

educational fellowships. A notable example is the purchase of equipment, which is not permitted by NASA

Fellowships but is covered by the National Science Foundation Graduate Student Supplemental Fellowships.

United States citizens and resident aliens will be given

preference, although the program is not restricted to them.

Students with disabilities and from underrepresented minority groups are urged to apply. No applicant shall be

denied consideration or appointment as a NASA Earth

System Science Fellow on grounds of race, creed, color,

national origin, age, or sex.

Earth System Science Fellowship information packets are available each January, and must be completed by

a mid-March deadline to be considered for the following

academic year. One original and seven copies of the application package need to be forwarded to the address

below. Incomplete packages and/or those received after

the March deadline are not considered in the selection

process.

Applications are reviewed on a competitive basis

through a two-step process. The first step involves a mail

review, which weeds out deficient proposals by assessing

the caliber of student, quality of research, and relevance

to the NASA Global Change Research Program. Those

applications that pass the initial screening are then evaluated by a panel composed of members of professional

scientific societies, academic institutions, NASA Centers,

and NASA Headquarters. Results of the competition are

announced by June 30, with September 1 as the anticipated starting date of awarded fellowships.

Competition for a Graduate Student Fellowship in

Global Change Research is quite fierce. Over 234 applications were submitted this year. 51 successful candidates

were selected, with the chosen students representing 86

universities and 33 countries. To date, more than 400 fellowships have been awarded.

A student receiving support under the Global Change

Fellowship Program does not incur any formal obligation to the Government of the United States; however,

the objectives of this program will clearly be served best

if the student is encouraged to actively pursue global

change research after completion of graduate studies. By

offering the opportunity to participate in this prestigious

program, NASA hopes to attract the world’s most outstanding scientists, both in the role of graduate fellows

and faculty advisors. The ultimate goal is to increase the

number of well-trained Earth scientists in the EOS era.

For more information write to:

Earth System Science Fellowship Program

Code Y

400 Virginia Avenue SW, Suite 700

Washington, DC 20024

Earth Science Enterprise URL

http://www.earth.nasa.gov/education/index.html

Global Change Fellowship Listings

http://eos.nasa.gov/eos_homepage/directory.html
1999 EOS Reference Handbook International Cooperation • 57

International Cooperation

International Cooperation

Contributions from international partnerships are a vital

piece of NASA’s Earth Science Enterprise. In order to

tackle the global challenge of understanding the total Earth

system, neither NASA nor even the entire U.S. Government, acting through the U.S. Global Change Research

Program (USGCRP) of which NASA is a part, can do it

alone. We rely heavily on international partners who,

through space agencies and other organizations abroad,

are making financial and hardware commitments to spacebased Earth science comparable to those of NASA. These

international partnerships can typically range anywhere

from NASA’s providing an instrument for flight on another country’s satellite and launch vehicle (or vice versa)

to an exchange of scientific data resulting from independent U.S. and non-U.S. missions. The goal is to share as

much useful scientific information as possible in order to

answer as quickly as possible some of the most pressing

questions facing humanity today—questions about how

our planet is changing and what we are doing to contribute to those changes. International partnerships and data

sharing also promote efficiency by eliminating the need

for different nations to fly multiple copies of the same (or

virtually the same) scientific instrument. Furthermore,

they enhance the scientific return of research missions by

involving more trained minds in the analysis of the resulting scientific data.

A primary vehicle for promoting international cooperation among countries with space-based Earth observation research programs is the Committee on Earth Observation Satellites (CEOS). CEOS brings together the

space-faring nations of the world to coordinate their

planned Earth observation activities, promote the sharing

of data and researchers, foster the interoperability of information systems and services, and ensure the quality

and accuracy of Earth observation research data through

a focus on data calibration and validation. CEOS is also

taking a lead in addressing the space component of a

broader integrated global observing strategy (IGOS) that

will encourage coordination among space and in situ observations. Even countries without space programs can

contribute through providing access to ground-based or

other in situ data and through analysis of the results of

shared information from spacecraft. Ultimately, if the

nations of the world are to take steps to address global

change, they must have confidence in the research data.

And there is no better way to engender this confidence in

the data than through involvement in its production.

The following paragraphs offer brief synopses of

some of the major foreign contributions to NASA’s Earth

Science Enterprise (see Table 9).

Western Europe

NASA is cooperating with France’s Centre National

d’Etudes Spatiales (CNES) on Jason-1 (a follow-on ocean

radar altimetry mission to TOPEX/Poseidon), which is

scheduled for launch in 2000. NASA and CNES are also

cooperating on the Pathfinder Instruments for Cloud and

AeroSol Spaceborne Observations-Climatologie Etendue

des Nuages et des Aerosols (PICASSO-CENA) mission,

which was selected for development under NASA’s second Earth System Science Pathfinder (ESSP-2) Announcement of Opportunity (AO). PICASSO-CENA is scheduled for launch in 2003.

NASA cooperation with Germany’s German Aerospace Center (DLR) includes collection and analysis of

ocean-color data from a German instrument, the Modular

Optoelectronic Scanner (MOS), launched aboard the Indian Remote Sensing Satellite P3 (IRS-P3) in March 1996;

the Shuttle Radar Topography Mission (SRTM), scheduled for launch in 1999; the Challenging Mini-satellite

Payload (CHAMP), scheduled for launch in late 1999,

and the Gravity Recovery and Climate Experiment

(GRACE) mission, scheduled for launch in 2001.

The United Kingdom is working with NASA to provide the Resolution Dynamics Limb Sounder (HIRDLS)

as well as making crucial contributions to the Microwave

Limb Sounder (MLS), which will fly on the EOS CHEM

mission, scheduled for launch in 2002.

The Netherlands is providing the Ozone Monitoring

Instrument (OMI) for EOS CHEM. NASA arranged and

funded a launch of Denmark’s Oersted satellite, which

included a NASA-provided Global Positioning System

TurboRogue (GPS-TR) receiver. Oersted was launched

in February 1999.

 The European Space Agency (ESA) has launched

its first Earth Remote Sensing satellite (ERS-1) in 1991

and its second, ERS-2, in April 1995. NASA has agreements with ESA to receive, process, and distribute Synthetic Aperature Radar (SAR) data from both missions.
58 • International Cooperation 1999 EOS Reference Handbook

ERS-1 is no longer operational, but NASA continues to

receive SAR data from ERS-2. In 2000, ESA plans to

launch its Envisat-1 mission, which includes nine instruments to study coastal zones, oceans, ice and land surface processes, and atmospheric chemistry processes.

NASA is currently working with ESA on an arrangement

to receive data from Envisat-1.

In addition, European scientists are members of EOS

instrument science and Interdisciplinary Investigation

teams, and are supporting EOS validation activities within

Europe (see EOS Instruments and Interdisciplinary Science sections).

Russia

The Russian Space Agency is providing the spacecraft,

the 1999 launch, and operations for NASA’s Stratospheric

Aerosol and Gas Experiment III (SAGE III). Russia is

also participating in the full range of SAGE III science

team activities. The Russian Academy of Sciences is

interoperable with NASA’s EOSDIS.

Canada

NASA and the Canadian Space Agency (CSA) are continuing cooperation on the Radarsat-1 mission, which was

successfully launched in November 1995. Since its launch,

this cooperative mission has provided an archive of uniform global SAR data by means of the satellite’s multimode imaging capabilities including high-resolution satellite coverage of the Antarctic continent.

CSA is also providing MOPITT for flight on Terra,

with a reflight possible on a flight of opportunity. This

instrument will measure atmospheric carbon monoxide

and methane. CSA is also sponsoring two of the EOS Interdisciplinary Science Investigations. CSA and NASA

are also cooperating on a Canadian science small-satellite mission, SciSat, scheduled for launch in December

2001 on a NASA-provided Pegasus XL launch vehicle.

NASA and the Department of Natural Resources of

Canada (NRC) are currently leading a joint study to evaluate the interactions between the boreal forest and the atmosphere to understand their role in global change. This

study includes intensive ground, air, and space observations, and participation from a variety of U.S. and Canadian Government agencies with an interest in the environment.

Japan

Japanese contributions to NASA’s Earth science activities include NASA’s participation in the National Space

Development Agency (NASDA)’s ADEOS missions and

co-sponsorship with NASA of the TRMM mission and

possible TRMM follow-on mission. The Japanese Ministry of International Trade and Industry (MITI) is also

participating through its provision of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for the Terra platform, scheduled for launch in 1999.

NASDA is providing an Advanced Microwave Scanning

Radiometer (AMSR-E) for EOS PM, scheduled for launch

in 2000.

The objectives of the ADEOS missions include Earth

surface, atmospheric, and oceanographic remote sensing.

The U.S. supplied two instruments for flight onboard

ADEOS—a NASA Scatterometer (NSCAT) and a Total

Ozone Mapping Spectrometer (TOMS). The French contributed one instrument to the mission—the Polarization

and Directionality of Earth’s Reflectances (POLDER).

Due to technical difficulties, the ADEOS satellite ceased

operation in June 1997, ten months after launch. ADEOSII is a post-ADEOS polar-orbiting Earth observation satellite whose mission is to obtain Earth science data related to the global water cycle. ADEOS-II, which will

also carry an NSCAT follow-on instrument (SeaWinds)

and a French POLDER instrument, is due for launch in

the year 2000.

TRMM is a joint NASA/NASDA mission with a

major objective of measuring precipitation in the Earth’s

tropical regions. Japan supplied the launch vehicle and

precipitation radar for TRMM, and NASA provided a

TRMM Microwave Imager (TMI), a Visible Infrared

Scanner (VIRS), a Clouds and the Earth’s Radiant Energy System (CERES), a Lightning Imaging Sensor (LIS),

and the TRMM spacecraft. TRMM was launched on a

Japanese H-II launch vehicle in November 1997.

Finally, Japan is sponsoring one Interdiscplinary Science Investigation (see Interdisciplinary Science section).

Latin America

Argentina is developing the Scientific Applications Satellite-C (SAC-C), which is scheduled for launch in December 1999 on a NASA-provided expendable launch

vehicle and will provide important information about land

use/land cover change for forest, agricultural, desert, and

marine coastal areas in Argentina, as well as contribute to

NASA’s Earth science efforts. SAC-C will also be one of

a suite of satellites to carry a new GPS receiver, provided

by NASA, for atmospheric, oceanic, and spacecraft navigation studies.

Brazil will provide the Humidity Sounder-Brazil

(HSB) instrument for flight on NASA’s EOS PM spacecraft. The HSB is a measurement system for atmospheric

humidity and will contribute to the significant enhancement of meteorological and climatic forecasts. Brazil will

also provide the CIMEX instrument for flight on the Space

Shuttle. CIMEX is an infrared camera designed to study

geology and the environment. The Brazilian-led LargeScale Biosphere-Atmosphere Experiment in Amazonia

(LBA) is a multi-disciplinary, international research effort designed to improve our understanding of the Ama-
1999 EOS Reference Handbook International Cooperation • 59

zon and its interaction with global change. NASA also

intends to contribute significant research activities to LBA.

Finally, Brazil is sponsoring an EOS Interdisclipinary Science Investigation (see Interdisciplinary Science

section), and several countries in Latin America are supporting EOS validation activities.

India

In late 1997, India’s Departments of Space Science and

Technology signed a Memorandum of Understanding

(MOU) with NASA and NOAA that is targeted at cooperation in the areas of Earth and atmospheric sciences and

also allows for the exchange of associated scientific data.

Specific areas of scientific cooperation called out in the

MOU include, but are not limited to: weather analysis

and forecasting techniques (short-range to seasonal);

evaluation of DMSP SSM/I data for use in flood forecasting, drought monitoring, and snow-melt runoff modeling; TRMM; satellite product development and improvement; surface and precipitation parameters (ocean and

land); calibration of 1-kilometer resolution AVHRR data

received in India with global land 1-kilometer AVHRR

data and 4-kilometer GAC data from the U.S.; inter-comparison studies of SSM/I Pathfinder data for use in land

surface studies (classification, temperature, vegetation);

and activities in the atmospheric sciences/International

Geosphere-Biosphere Program. This MOU with India also

enabled the establishment of communication lines for the

exchange of Earth and environmental science data. For

the United States, the chief intent of the communication

links is to provide the U.S. Government with real-time

access to Indian geostationary satellite (INSAT) data, a

scientific objective for 15 years. The improved severe

weather forecasting ability that will be developed under

this cooperation will save lives in the entire Indian Ocean

region and will improve global data inputs to U.S. regional forecast models.

Australia and New Zealand

Australia is supporting one EOS Interdisclipinary Science

Investigation (see Interdisciplinary Science section), as

well as surface validation sites. In addition, Australia is

supporting two scientists as members of the MODIS science team. New Zealand also supports EOS validation

activities in collaboration with the University of Denver.

Africa

NASA is currently in discussions with South Africa,

Botswana, Malawi, Mozambique Namibia, Zambia, and

Zimbabwe in support of the Southern African Regional

Science Initiative 2000 (SAFARI 2000) program. This

program includes a series of ground-based and airborne

experiments throughout Southern Africa to be conducted

in the 1999 and 2000 time frame. This science initiative

will study the effects of biomass burning and industrial

and biogenic emissions on the southern African ecosystem and climate and validate these observations using

ground-based and airborne measurements. In addition,

NASA’s EOS satellites, scheduled for launch in 1999 and

2000, will provide satellite-based measurements to

complement the ground-based and airborne data collected

for SAFARI 2000; and, in turn, SAFARI 2000 will provide validation for EOS satellite data.

NASA and South Africa are also cooperating on

SUNSAT, a South African satellite that was launched on

a NASA-provided expendable launch vehicle in February 1999. SUNSAT is carrying South African studentdeveloped experiments and environmental monitoring

instruments. SUNSAT is also carrying a NASA-provided

satellite laser tracking retro-reflector and is another one

of the suite of satellites to carry a NASA-provided GPS

receiver for atmospheric, oceanic, and spacecraft navigation studies.

Major Satellite Missions in the International Earth

Observing System

Some of the major satellite missions in the International

Earth Observing System are shown in Tables 10a, 10b,

and 10c.
60 • International Cooperation 1999 EOS Reference Handbook

Project Partner Contribution Type

SAC-C Argentina Spacecraft, instrument, mission operations and data analysis (MO&DA)

Denmark Magnetic mapping payload

SOLCON Belgium Instrument on ATLAS, now flying as a Hitchhiker on the Space Shuttle

HSB Brazil EOS PM humidity sounder

CIMEX Brazil CCD Imagining Camera for Earth observation and technology demonstration

LBA Brazil NASA aircraft overflight support and in situ measurements

BOREAS Canada Satellite data collection; instruments; aircraft; PIs

MOPITT Canada Instrument on Terra spacecraft

Radarsat-1 Canada SAR instrument/spacecraft

Oersted Denmark Spacecraft; instruments; MO&DA

France

ERS-1/ERS-2 ESA Spacecraft; instruments; launch; MO&DA

TOPEX/Poseidon France Instruments; launch; ongoing MO&DA

Jason-1 France Spacecraft; instruments; validation; science; MO&DA

CHAMP Germany Spacecraft & launch

GRACE Germany ESSP mission; spacecraft and launch (a German-procured Russian launch)

SRTM Germany X-SAR instrument on Shuttle

ADEOS Japan Spacecraft; some instruments; launch

AMSR-E Japan Instrument on EOS PM

ASTER Japan Instrument on Terra spacecraft

TRMM Japan Launch; precipitation radar

JERS Japan Spacecraft; instruments; launch

OMI Netherlands Instrument on EOS CHEM

SAGE III/METEOR-3M Russia Spacecraft; launch

SUNSAT South Africa Spacecraft; instruments; MO&DA

SAFARI 2000 South Africa, Zimbabwe, NASA aircraft overflight support; surface and in situ measurements

Namibia, Botswana,

Zambia

HIRDLS UK Subsystems for instrument on EOS CHEM

MLS UK Aspects of data algorithms, validation and analyses

INSAT India Access (with NOAA) to data from meteorological sensors on Indian INSAT

satellites and in situ measurements

IRS-P3/MOS India Spacecraft and launch

Germany MOS ocean color sensor

NASA-led Space

Geodesy Program Over 80 countries VLBI/SLR/GPS system investment and operation

SCISAT * Canada Space science payload

ENVISAT * ESA Spacecraft; instruments; launch; MO&DA

PICASSO-CENA * France Platform; portions of instrument; spacecraft operations

* Potential cooperative initiatives currently under discussion

Table 9. Some of the Major Foreign Contributions to NASA’s Earth Science Enterprise
1999 EOS Reference Handbook International Cooperation • 61 VIS/IR Imagers Radiation Budget Passive Atmospheric Sounding Passive Microwave OBJECTIVES STATUS Active Microwave Tropospheric Chemistry Stratospheric Chemistry Laser Altimeter Other Operational Instruments Tropospheric Wind Lidar ACTUAL/PROPOSED INSTRUMENT CONFIGURATION 1996 - 1999 Radar Altimeter APPROVED Solid-state laser technology development is under way in support of this objective NOAA-15 833 km 98.7° Incl. 7:30 AM May 1998 AVHRR-3 AMSU-A 1/2 AMSU-B HIRS-3 SEM ARGOS S&R All Sensors TRMM 350 km 35° Incl. November 1997 VIRS CERES TMI PR TOMS/EP June 1996 SeaWiFS Radarsat-1 November 1995 C-Band SAR TOMS OrbView-2 705 km 98.2° Incl. 12:00 PM August 1997 LIS QuikScat SeaWinds 803 km 98.6° Incl. 6:00 AM June 1999 ETM+ Landsat 7 705 km 98.2° Incl. 10:00 AM April 1999 ASTER MISR MODIS CERES (2) MOPITT Terra 705 km 98.2° Incl. 10:30 AM November 1999 ACRIMSAT ACRIM III 685 km 98.13° Incl. 10:50 AM October 1999

Table 10a. Some of the Major Satellite Missions in the International Earth Observing System
62 • International Cooperation 1999 EOS Reference Handbook VIS/IR Imagers Radiation Budget Passive Atmospheric Sounding Passive Microwave OBJECTIVES STATUS Active Microwave Tropospheric Chemistry Stratospheric Chemistry Laser Altimeter Other Operational Instruments Tropospheric Wind Lidar ACTUAL/PROPOSED INSTRUMENT CONFIGURATION 1999 (continued) - 2000 Radar Altimeter APPROVED Solid-state laser technology development is under way in support of this objective SeaWinds GLI ADEOS-II POLDER 803 km 98.6° Incl. 10:30 AM November 2000 AMSR ILAS-2 JMR Jason-1 1336 km 66° Incl. May 2000 Poseidon 2 DORIS GPS EOS PM 705 km 98.2° Incl. 1:30 PM December 2000 AIRS AMSU-A HSB CERES (2) MODIS AMSR-E ENVISAT-1 800 km 98.6° Incl. 10:00 AM May 2000 RA-2 GOMOS MIPAS SCIAMACHY DORIS SCIAMACHY AATSR MERIS MWR ASAR SCARAB SAGE III METEOR 3M-1 1020 km 99.5° Incl. 9:15 AM March 2000 SAGE III NOAA-L 870 km 98.7° Incl. 2:00 PM February 2000 AVHRR-3 AMSU-A 1/2 AMSU-B HIRS-3 SBUV-2 SEM ARGOS S&R All Sensors ESSP-1/VCL 400 km 67° Incl. August 2000 MBLA GPS ALI NMP/EO-1 Hyperion 705 km 98.2° Incl. 10:00 AM December 1999

Table 10b. Some of the Major Satellite Missions in the International Earth Observing System
1999 EOS Reference Handbook International Cooperation • 63

Table 10c. Some of the Major Satellite Missions in the International Earth Observing System VIS/IR Imagers Radiation Budget Passive Atmospheric Sounding Passive Microwave OBJECTIVES STATUS Active Microwave Tropospheric Chemistry Stratospheric Chemistry

Laser Altimeter

Other

Operational 

Instruments

Tropospheric

Wind Lidar

ACTUAL/PROPOSED INSTRUMENT CONFIGURATION 2001 - 2003

Radar Altimeter

APPROVED

NOAA-M

833 km

10:00 AM

98.7° Incl.

May 2001

AVHRR-3

AMSU-A 1/2

AMSU-B

HIRS-3

SEM

ARGOS

S&R

All

Sensors

ICESat

600 km

94° Incl.

July 2001

GLAS

METOP-1

GOME

850 km

98.8° Incl.

9:00 AM

1Q/2003

AVHRR-3

IASI

HIRS-4

AMSU-A

MHS

ASCAT

ARGOS

SEM

S&R

AVHRR-3

MHS, SEM

AMSU-A

HIRS-4, S&R

ARGOS

HIRDLS

TES

OMI

EOS CHEM

705 km

98.2° Incl.

1:45 PM

December 2002

HIRDLS

TES

OMI

MLS

HIRDLS

MLS

OMI

Internatioal

Space

Station

51.6° Incl.

March 2003

SAGE III

SAGE III

ESSP-4/

CloudSat

705 km

98.08° Incl.

1:31 PM

March 2003 

CPR

PABSI

ESSP-3/

PICASSO-CENA

705 km

98.08° Incl.

1:30 PM

March 2003

LIDAR

SORCE

600 km

40° Incl.

July 2002

TIM, SIM

SOLSTICE

XPS

ESSP-2/GRACE

485 km

89° Incl.

June 2001

HAIRS

GPS

SuperStar

GPS

ABS

WFC

IIR
1999 EOS Reference Handbook Interagency Coordination • 65

Interagency Coordination

Interagency cooperation in the development and implementation of EOS continues to be extensive, especially

among those agencies with space programs and/or significant responsibilities for archiving Earth science data.

The National Space Policy revision issued September 19,

1996 requires NASA to undertake “a program of longterm observation, research and analysis of the Earth’s land,

oceans, and atmosphere and their interactions, including

continual measurements from the Earth Observing System.” The Policy also assigns related roles to the Departments of Commerce, Defense, Energy and Interior, to be

performed in cooperation with NASA. NASA collaborates with these agencies and others in a variety of bilateral, trilateral, and multilateral arrangements. These and

other agencies partner with NASA in the conduct of the

U.S. Global Change Research Program (USGCRP).

NASA’s Earth Science Enterprise comprises approximately two-thirds of the USGCRP budget. EOS and the

other programs of the Earth Science Enterprise have been

planned to benefit from, and to complement, the capabilities of its Federal agency partners. The largest agency

partners, with key roles defined in the following paragraphs, are:

• Department of Commerce/National Oceanic and Atmospheric Administration (DoC/NOAA),

• Department of Defense (DoD),

• Department of Energy (DoE), and

• Department of the Interior/U.S. Geological Survey

(DoI/USGS).

Department of Commerce

NOAA conducts U.S. civil programs for operational Earth

remote sensing. Since 1960, satellite observations of the

global environment have been provided by NOAA’s Polar-orbiting Operational Environmental Satellite (POES)

system. Coverage of the Western Hemisphere has been

provided by NOAA’s Geostationary Operational Environmental Satellite (GOES) system since 1974. The current

and future satellites of the POES and GOES systems are

an essential part of the USGCRP. These satellites provide

valuable precursor data, and will yield complementary

observations during the EOS mission lifetime. Furthermore, NOAA’s long-term data record will be used to establish baseline conditions and to detect trends.

The present POES Program maintains two operational satellites in polar orbit—one providing morning

(AM) coverage and the other afternoon (PM) coverage.

The U.S. and Europe, the latter through EUMETSAT and

ESA, have agreed in principle that Europe will take over

responsibility for the AM global coverage mission in the

2003 time frame with the launch of the first Meteorological Operational (MetOp) satellite. NOAA will provide AM

coverage through 2003, and will continue PM coverage.

Through NOAA, the U.S. will provide a suite of four primary sensors for the European AM mission. EUMETSAT

and others will reciprocate by supplying sensors and subsystems for flight on both the AM and PM satellites.

Planning for the cooperative program of global coverage by the U.S. and Europe includes arrangements to

fly the NOAA/EUMETSAT operational payload in morning orbit and EUMETSAT’s establishment of a high-latitude ground station to read out data from both the AM

and PM platforms. This latter agreement ensures that data

are downlinked each orbit, minimizing data latency and

dependence on data averaging. With one European and

two U.S. high-latitude stations, NOAA and EUMETSAT

will essentially eliminate data delays associated with the

recording of multiple or “blind” orbits. NOAA and

EUMETSAT have agreed to establish systems and procedures to ensure the timely and full exchange of operational mission data.

Long-term improvements in NOAA satellite, instrument, and space subsystem design are expected to result

from technology advances associated with the EOS Program. To this end, coordination in technology development extends to NASA’s designating some EOS instruments as “prototypes” for future operational environmental satellites. In addition, teams have been established to

look at the common requirements of research and operational programs and identify areas where further collaboration would be of mutual benefit in hardware, software,

and algorithm development. Furthermore, NASA has been

designated by the President as playing a lead role in the

identification and promotion of new technology for the

future converged National Polar-orbiting Operational

Environmental Satellite System (NPOESS), working with

DoD and NOAA in the Integrated Program Office.
66 • Interagency Coordination 1999 EOS Reference Handbook

Data products derived from POES and GOES observations are provided to users in near real-time and from

archived data sets by NOAA; in addition, Pathfinder data

sets are provided jointly by NASA and NOAA (see the

Pathfinder Data Sets section). As a participant in the EOSDIS Program, NOAA will serve as the long-term archive

for a major portion of EOS and other NASA mission oceanic and atmospheric data, and will continue to make

available in situ data from its data centers. NOAA actively participates in the Committee on Earth Observation Satellites (CEOS) and in the U.S. Subcommittee on

Global Change Research’s Global Change Data Management Working Group (DMWG), where interagency data

exchange arrangements and policies are planned and coordinated.

Department of Defense

DoD’s Defense Meteorological Satellite Program (DMSP)

maintains satellites in polar orbit to gather global environmental data. DMSP data and derived products have

been made available to non-DoD users through NOAA.

DMSP data will be available to global change researchers in standard formats via global change data networks.

DoD plans future satellites and instruments that will

provide additional Earth system observations. Missions

under consideration address ocean conditions, ozone and

trace gas distributions, ionospheric airglow, and solar energy interactions with the atmosphere. DoD participates

in planning for USGCRP and its associated data systems.

In cooperation with the other Federal agencies involved

in EOSDIS and related data systems, DoD is seeking

workable approaches to make more of its relevant data

available. Other working groups are being established to

explore potential environmental remote-sensing collaborations between NASA and DoD.

NASA and the DoD’s National Imagery and Mapping Agency (NIMA) are jointly undertaking the Shuttle

Radar Topography Mission (SRTM) to be flown in 1999.

SRTM consists of an interferometric capability added to

the Space Radar Laboratory flown twice on the Space

Shuttle in 1994. SRTM will produce the first Digital Terrain Model of the Earth’s land surface between 60°N and

54° S.

Department of Energy

DoE develops and uses remote-sensing technology in

many of its programs. The agency develops and tests climate models, and assesses the impacts associated with

incidental environmental forcing functions. For instance,

DoE has conducted a decade-long program to improve

general circulation models and to provide reliable predictions of regional climate change in response to increases in atmospheric greenhouse gases. DoE holds databases acquired from a multitude of sources as tools for

conducting its modeling and climate-prediction activities.

With respect to hardware, DoE has successfully miniaturized key components of space-based instrumentation,

which adds a great deal of flexibility to Earth remotesensing programs. Recent developments now enable the

deployment of low-mass, low-volume sensors on conventional or small satellites. Miniaturization technology contributes to the effectiveness of USGCRP by allowing early

deployment of small satellites. In an effort to exploit such

technology advances, NASA and DoE have created a Joint

Development and Demonstration Program in Advanced

Remote-Sensing Technology, which has the objective of

lowering the cost and improving the performance of remote sensors. The ultimate goal involves the development

of remote-sensing technologies and concepts for spacebased environmental applications. Four areas are currently

under investigation: Laser detection of winds, high-resolution multispectral imaging, synthetic aperture radar, and

unmanned aerospace vehicle (UAV) sensing.

The DoE’S Atmospheric Radiation Measurement

(ARM) program presents an important opportunity for

collaboration between DoE and EOS. The role of ARM

is to provide intensive ground-based measurements of

atmospheric properties at a few selected heavily instrumented sites. This DoE activity then presents a significant source of “ground truth” for calibration and validation of EOS space-based observations.

The Southern Great Plains site in Oklahoma was the

first to be occupied and has now achieved a mature operational status. A second site in the tropical Western Pacific will comprise three island stations. The first (Manus)

and second (Nauru) have been implemented with a third

to be implemented in 1999 at Christmas Island. A site in

Alaska is presently under development and supported field

experiment activity there in 1998–NSF’s Surface Heat

Budget of the Arctic (SHEBA) experiment and the Arctic

Cloud Experiment of NASA’s Radiation Sciences Program. The ARM sites have been chosen to provide a sampling of continental (Southern Great Plains) and tropical

oceanic (Tropical Western Pacific) conditions of clouds

and radiation, and the radiation environment and the influence of clouds under polar conditions (North Slope of

Alaska). These sites increasingly attract first-class experiments concerned with atmospheric processes and remote

sensing with support from a variety of U.S. agencies.

ARM is supporting a program of unmanned aircraft

(UAVs) that will serve as the platforms for relatively inexpensive instruments whose measurements will validate

the radiation modeling for the atmosphere at the various

ground-instrumented sites.

Along with the involved U.S. agencies, DoE is developing the networking capabilities to make its current

and future global change archives more conveniently accessible to users. In the EOSDIS framework, DoE has

agreed to manage the EOS biogeochemical dynamics
1999 EOS Reference Handbook Interagency Coordination • 67

database and data from coordinated field experiments.

This database will reside at the Oak Ridge National Laboratory (ORNL).

Department of the Interior

Management responsibility for the Nation’s natural ecosystem, energy and water resources, and public lands is

vested in DoI. Within DoI, the U.S. Geological Survey

(USGS) is addressing the collection, maintenance, analysis, and interpretation of in situ short- and long-term land,

water, biological, and other natural resource data and information. USGS is developing advanced information systems to provide enhanced access to existing and future

archives of Earth science data through its primary archive

for global change data—the Earth Resources Observation System (EROS) Data Center (EDC).

EDC houses the world’s largest collection of spaceand aircraft-based imagery of the Earth’s land surface,

including over 2 million images acquired from Landsat

and other satellites, and over 8 million aerial photographs.

EDC participates in the EOS Program by:

• operating the data center responsible for land processes

information,

• communicating with the EOS science and instrument

teams to ensure delivery of land-related products required for EOS investigations, and

• linking the USGS Global Land Information System

(GLIS) to the EOSDIS Information Management System (IMS).

GLIS—an on-line data directory, guide, and inventory

system—has been developed by EDC to respond to the

land data and access needs of the global change research

community.

Landsat data housed at EDC provide a 25-year

baseline of information about land surface conditions and

changes. As the operator of the National Satellite Land

Remote-Sensing Data Archive, EDC has embarked upon

a major program to convert the Landsat data archive to

next-generation durable storage media, thereby avoiding

loss of data stored on deteriorating magnetic tapes. In addition, EDC will serve as the processing, distribution, and

archival facility for Landsat 7 and ASTER data.

Landsat 7 program management was restructured for

a second time in 1999 to become a joint program between

NASA and the U.S. Geological Survey (USGS), Department of the Interior. The 1992 Land Remote Sensing

Policy Act initiated the Landsat 7 program as a joint DoD

and NASA program. A Presidential Decision Directive,

NSTC-3, dated May 5, 1994, reassigned responsibility

for the development, launch, and operation of Landsat 7

to a joint NASA, NOAA, USGS program. In 1999, the

responsibility for management of post-launch operations

was transferred from NOAA to the USGS. The program

objectives are to provide data continuity with previous

Landsat satellites, to make Landsat 7 data available to all

users at the cost of fulfilling user requests, to capture a

U.S.-held archive of Landsat 7 data providing global coverage of the Earth's continental and coastal surfaces, updated seasonally, and to develop a plan for acquiring follow-on Landsat-type data as a part of the EOS Program.

The USGS is participating with NASA and NIMA in

the SRTM mission to be flown in 1999.

Interagency Convergence

Presidential Decision Directive/NSTC-2, signed on May

5, 1994, directed the convergence of the civil and military polar-orbiting environmental programs into a single

integrated system. This consolidation was a key recommendation of the National Performance Review. The goal

of the converged program is to reduce the cost of acquiring and operating polar-orbiting operational environmental satellites, while continuing to satisfy U.S. operational

civilian and national security requirements.

Convergence of the follow-on satellite programs of

the Department of Commerce/National Oceanic and Atmospheric Administration’s (NOAA) Polar-orbiting Operational Environmental Satellite (POES) program, and

the Department of Defense’s (DoD) Defense Meteorological Satellite Program (DMSP) has already begun under the aegis of an Integrated Program Office (IPO) jointly

staffed by NOAA, DoD, and NASA personnel. As part of

the goal of reducing costs while enhancing the ability of

the converged system to meet its operational requirements,

the operational program will incorporate aspects of

NASA’s Earth Observing System where and as appropriate. The converged satellite system has been named the

National Polar-orbiting Operational Environmental Satellite System (NPOESS).

The POES satellites currently provide civilian environmental monitoring. Key aspects of the POES mission

include collecting atmospheric data to be used in conjunction with computer models for weather forecasting,

measuring global ozone levels for climate change research,

and monitoring emergency beacons for search and rescue operations. The purpose of the DMSP program is to

collect and disseminate global visible and infrared cloud

data and other specialized meteorological, oceanographic,

and solar geophysical data to provide a survivable capability in support of military operations. Some of these observations form the bases of the NASA-NOAA Pathfinder Data Set Program (see Pathfinder Data Sets section of

this Handbook).

The U.S. currently operates two NOAA POES and

two DMSP meteorological satellites in polar orbit.

Through convergence, the U.S. will transition to an onorbit architecture of three low-Earth orbiting satellites.
68 • Interagency Coordination 1999 EOS Reference Handbook

Current plans call for the on-orbit constellation to comprise two U.S. satellites as well as a third European satellite (Metop) carrying U.S. and European operational and

research instruments. The Metop series is a joint undertaking of the European Organization for the Exploitation

of Meteorological Satellites (EUMETSAT) and the European Space Agency (ESA). Significant savings will be

gained through the reduction of the required number of

U.S. satellites from four to two, the transition to a converged U.S. spacecraft, and the near-term efficiencies of

consolidating the command and control activities of the

current operational spacecraft at NOAA’s Suitland, Maryland, Satellite Operations Control Center (SOCC) in 1998.

The NPOESS program was formally approved for

entry into the design and risk-reduction phase in

March1997. Competitive Phase B contracts were awarded

on July 30, 1997 for five planned NPOESS payload sensors including a Visible and Infrared Imaging Radiometer Suite (VIIRS), Conical Microwave Imager Sounder

(CMIS), Cross Track Infrared Sounder (CRIS), Ozone

Mapper and Profiler Suite (OMPS), and a Global Positioning Sensor Occultation System (GPSOS). The IPO is

also working with NASA and other agencies to implement acquisition plans for additional sensors to include

an advanced, research quality atmospheric sounder, a total solar irradiance sensor, an Earth radiation budget sensor, and a dual-frequency altimeter. Studies are also underway to explore the development of instruments which

could satisfy both NASA’s research needs, and the IPO’s

operational needs (e.g., the IPO VIIRS instrument and

the NASA MODIS instrument).

The first NPOESS spacecraft must be ready for

launch in 2007 in order to back up the last satellites in the

DMSP and POES series. The planning launch date for

NPOESS C1 is 2009 and for NPOESS C2 is 2010, assuming no failures of the predecessor satellites. Current

plans call for early flight of selected NPOESS sensors on

DMSP and POES, to include an advanced sounder on

NOAA N ́. More information on NPOESS can be obtained

from the NPOESS web site at: http://www.laafb.mil/SMC/

PK/NPOESS/rfp.htm.

The National Science and Technology Council

The National Science and Technology Council (NSTC)

is a standing, cabinet-level body chaired by the President

and composed of the Vice President, the Assistant to the

President for Science and Technology, the cabinet secretaries and agency heads with responsibilities for significant science and technology programs, and other White

House officials. The principal purposes of the NSTC are

to define clear national goals for federal science and technology investments and ensure that science, space, and

technology policies and programs contribute effectively

to the national goals.

In 1994, NSTC committees identified R&D priorities, and the NSTC, through the Office of Science and

Technology Policy and the Office of Management and

Budget, provided federal agencies with coordinated budget guidance for Research and Development.

In recent years, there have been a number of thoughtful criticisms of the way the federal government has historically conducted environmental R&D. The piecemeal,

single-issue-by-single-issue, agency-by-agency research

programs once thought to be adequate to deal with the

environment have been widely recognized as inadequate

to deal with the complex air, land, sea, economic, and

social issues associated with regional, national, and global concerns such as ocean transport of pollutants, atmospheric deposition, climate change and ozone-layer depletion, biodiversity, and sustainable development. Ensuring economic development in concert with environmental protection makes the need for stronger integration of

social, economic, and environmental sciences critical as

all stakeholders are drawn into the process of environmental decision making. The NSTC Committee on Environment and Natural Resources (CENR) was created as a

new way to conduct coordinated, cost-effective, interdisciplinary research to address the important environmental issues of our time.

CENR has emphasized research to understand the potential consequences of long-term environmental change

and to promote the efficient use of natural resources while

sustaining ecosystems for future generations. Increased

emphasis has been placed on the integration of social sciences and assessment end points into research planning

in all of the CENR issue areas.

Efforts are being made throughout the CENR, with

coordination by the Task Force on Observations and Data

Management, to increase the efficiency with which the

vast array of monitoring and other forms of data generated within the federal system are made available. This

process will help to define better where true gaps in longterm monitoring exist and need to be filled.

The CENR consists of seven issue subcommittees

created because they represent areas of important policy

that transcend the interest of a single agency: Global

Change; Biodiversity and Ecosystem Dynamics; Resource

Use and Management; Water Resources and Coastal and

Marine Environments; Air Quality; Toxic Substances and

Hazardous and Solid Waste; and Natural Disaster Reduction.

The CENR has three crosscutting subcommittees:

Risk Assessment, Social and Economic Sciences, and Environmental Technology (a joint subcommittee of CENR

and the NSTC Committee on Civilian and Industrial Technology). The crosscutting subcommittees focus on themes

common to the areas covered by the seven issue subcommittees and provide an additional mechanism for interagency coordination. Risk assessment, for example, plays

an important role in issues such as the effects of toxic

substances, biodiversity, loss of ecosystem integrity, natural disaster reduction, and effects of global change on
1999 EOS Reference Handbook Interagency Coordination • 69

human health and ecosystem function. Social and economic sciences are critical to evaluating the impacts of

human activities on local, regional, and global environments and human responses to natural disasters and environmental change. The Task Force on Observations and

Data Management coordinates requirements and capabilities in these areas across the CENR research issues.

The CENR has identified the following five priority areas that cross all environmental R&D:

• Ecosystem research – to promote efficient use of natural resources while sustaining ecosystem integrity for

future generations.

• Observations and data management – to ensure that

the necessary measurements are made efficiently and

that the data are widely available to all stakeholders in

easily usable forms.

• Socioeconomic dimensions of environmental change –

to understand the underlying human influences on the

environment and the potential responses of society to

change.

• Environmental technology – to protect the environment

while stimulating economic growth and capturing

emerging global markets.

• Science policy tools – to provide the tools (e.g., integrated assessment and risk models) required by policymakers for informed decisions on complex environmental and societal issues.
1999 EOS Reference Handbook Mission Elements • 71

Mission Elements

Introduction

This section provides specifics on the space-based elements that

make up the International Earth Observing System (IEOS). Refer to Figures 8a and 8b on pages 86 and 87 for a schedule of

ongoing and planned U.S. and international partner Earth-observing missions. This timeline is not confined to IEOS; rather,

it provides a fairly comprehensive listing of relevant Earth remote-sensing satellites, many of which do not receive attention

in the following pages. The timeline intentionally encompasses

missions beyond the scope of IEOS to show how IEOS fits into

the larger scheme of Earth observations satellites. Given the long

planning schedule (over ten years shown), this chart should be

considered more of a planning document, accurate through the

beginning of 1999. For reference, Figure 9 on page 88 illustrates

the EOS program-level architecture.

TRMM 72

Landsat 7 72

QuikScat 75

Terra 75

ACRIMSAT 76

SAGE III Series 76

NMP/EO-1 77

Jason-1 77

ESSP Missions 77

VCL

GRACE

PICASSO-CENA

Cloudsat

ADEOS 78

ADEOS

ADEOS II

EOS PM 80

ICESat 80

EOS CHEM 81

EOS Follow-On

 Missions 81

POES Series 83

SORCE 84

NPP 84 Figure 7. Terra Platform and Payload.
72 Mission Elements • 1999 EOS Reference Handbook

http://trmm.gsfc.nasa.gov/

TRMM

The Tropical Rainfall Measuring Mission (TRMM) is a

joint U.S./Japan mission which was successfully launched

on November 27, 1997 aboard a Japanese H-II rocket.

The TRMM orbit is non-sun-synchronous at an altitude

of 350 km. The objectives of TRMM are to measure rainfall and energy (i.e., latent heat of condensation) exchange

of tropical and subtropical regions of the world. The primary rainfall instruments on TRMM are the TRMM Microwave Imager (TMI), the Precipitation Radar (PR), and

the Visible and Infrared Radiometer System (VIRS). Additionally, the TRMM satellite will carry two related EOS

instruments: The Clouds and the Earth’s Radiant Energy

System (CERES) and the Lightning Imaging Sensor (LIS).

The combination of satellite-borne passive and active sensors is beginning to provide critical information

regarding the three-dimensional distributions of precipitation and heating in the tropics. Coincident measurements

from the TRMM Microwave Imager (TMI) and the Precipitation Radar (PR) are complementary: Passive microwave radiometers measure the integrated effects of liquid and ice along the instrument viewing direction while

active microwave sensors (radars) provide specific height

information on liquid and ice within the cloud.

The Visible and Infra-Red Scanner (VIRS) on TRMM

adds cloud top temperatures and structures to complement the descriptions from the radar and radiometer. While

direct precipitation information from VIRS is less reliable than that obtained by the microwave sensors, VIRS

serves an important role as a bridge between the high quality but infrequent observations from TMI and PR with

the more-available data and longer time series data available from the geostationary VIS/IR satellite platforms.

The Clouds and the Earth’s Radiant Energy System

(CERES), and the Lightning Imaging System (LIS), while

designated as EOS instruments, still play an important

role in the TRMM mission to round out the scientific objectives. LIS, aside from mapping the global frequency

of lightning events, will play an important role in coupling the occurrence of lightning to the precipitation, thus

enhancing our overall understanding both of lightning and

of precipitation processes. CERES allows for determination of the total radiant energy balance. Together with the

latent heating derived from the precipitation, a significantly improved picture of the atmospheric energy system can emerge.

TRMM data are sent to GSFC via TDRSS and the

White Sands Receiving Station. The TRMM Data and

Information System (TDIS) at GSFC is responsible for

all science data processing and data distribution to the

TRMM algorithm development team. After an initial

checkout period, the data are sent to the Goddard DAAC

for archival and distribution to the general user community. Preliminary Level 1 data were released to the public

on June 1, 1998.

Landsat 7

Landsat 7 is the latest in a series of satellites that have

provided a continuous set of calibrated Earth science data

to both national and international users since 1972.

Landsat Chronology

The first Landsat, originally called Earth Resources Technology Satellite (ERTS-1), was developed and launched

by NASA in July 1972. Subsequent Landsat launches occurred in January 1975 and March 1978. In the meantime, a second generation of Landsat satellites was developed. Landsat 4 was launched in July 1982 and

Landsat 5 in March 1984. Landsat images are still being

received from Landsat 5. As a result, a continuous set of

Landsat remotely sensed images of the Earth’s land surface and surrounding coastal regions from mid-1972 until the present is available.

Over the past 27 years scientists have developed a

wide range of applications using Landsat data for globalchange research, regional environmental studies, national

security, and other civilian and commercial purposes. For

example, Landsat data have been used to monitor agricultural productivity, urban growth, and land-cover

change, and are used widely for oil, gas, and mineral exploration. Other science applications include monitoring

volcanoes, glacier dynamics, agricultural productivity, and

coastal conditions.

http://landsat.gsfc.nasa.gov/
1999 EOS Reference Handbook Mission Elements • 73

Authorized by Public Law 102-555 in October 1992,

Landsat 7 continues the Landsat tradition as part of

NASA’s Earth Science Enterprise. The science mission

of Landsat 7 is targeted to regional and global assessments of land-cover dynamics. For the first time, Landsat

7 will systematically acquire imagery from across the

globe using a Long-term Acquisition Plan. This will insure a data archive recording the full seasonal and interannual changes in the vegetation patterns of the planet,

while minimizing the effects of cloud cover.

While NASA’s other EOS instruments MODIS and

MISR will acquire frequent, coarse views of land-cover

change, the spatial resolution of ETM+ data from Landsat

will allow researchers to determine the actual causes of

observed landcover changes. These changes have important implications, both for local habitability and for the

global cycling of carbon, nitrogen, and water.

In 1994 President Clinton originally assigned management of the Landsat Program jointly to NASA, the

National Oceanic and Atmospheric Administration

(NOAA), and the United States Geological Survey

(USGS). However, in March 1999, this management structure was streamlined to include NASA and USGS only.

Currently, NASA is responsible for the development and

launch of the satellite and the development of the ground

system, and USGS is responsible for operating the satellite, distributing the data, and maintaining an archive of

Landsat 7 and other remotely sensed data.

With Landsat 5 recently surpassing 15 years of continuous operation on orbit, Landsat 7 will provide muchneeded continuation of land remote-sensing data critical

to understanding environmental change and will support

a broad range of other important Earth science and Earth

resource applications.

The Landsat 7 Program objectives are:

• To maintain Landsat data continuity by providing data

that are consistent in terms of data acquisition, geometry, spatial resolution, calibration, coverage characteristics, and spectral characteristics with previous

Landsat data.

• To generate and periodically refresh a global archive

of substantially cloud-free sun-lit land-mass imagery.

• To continue to make Landsat-type data available to

U.S. and international users at the cost of fulfilling

users requests, and expand the use of such data for

global change research and commercial purposes.

Landsat 7 Flight Segment

Landsat 7 was launched from Vandenberg Air Force Base

by a Delta-II Expendable Launch Vehicle on April 15,

1999. The Landsat 7 satellite consists of a spacecraft bus

and a single instrument, the Enhanced Thematic Mapper

Plus (ETM+) (see the EOS Instruments section of this

Handbook).

Like its predecessors, Landsat 7 will produce Landsat

scenes based on the World Wide Reference System, a catalogue of 57,784 land mass and coastal scenes, each 185-

km wide by 170-km long. The orbit altitude is approximately 705 km, with a sun-synchronous 98 ̊ inclination

and a descending equatorial crossing time of 10:00 a.m.

and a 16-day repeat cycle.

A state-of-the-art solid-state recorder capable of storing 380 gigabits of data (100 scenes) is used to store selected scenes from around the world for playback over

the U.S. ground station at the EROS Data Center in Sioux

Falls, South Dakota. Additional U.S. ground stations are

operated in Alaska and Svalbard, Norway. In addition,

real-time data from the ETM+ can be transmitted to cooperating international ground stations or to U.S. ground

stations on command.

Landsat 7 Ground Segment

The ground system includes the spacecraft Mission Operations Control Center, which has been built and is operational at the Goddard Space Flight Center (GSFC) in

Greenbelt, Maryland. This Landsat 7-unique facility, augmented by other existing NASA institutional facilities,

are utilized to control all spacecraft and instrument operations for at least two years after launch. Flight operations are controlled from GSFC with commands uplinked

via the Landsat Ground Station in Sioux Falls and NASA

TDRSS.

In addition to the Mission Operations Control Center, NASA has built all data processing and distribution

components of the Landsat 7 system. These components

have been integrated into the USGS EDC in South Dakota. After launch and on-orbit activation and verification of the satellite and data processing and distribution

components, the data processing, archive and distribution portions of the ground system will be turned over by

NASA to USGS for operation. NASA will continue to

operate the Mission Operations Center at Goddard Space

Flight Center on USGS’ behalf through fiscal year 2000.

Landsat 7 scientific data are being downlinked, processed, and distributed by the USGS EDC in Sioux Falls,

South Dakota. The ground system at EDC is capable of

capturing and processing 250 Landsat scenes per day and

delivering at least 100 scenes to users each day via the

EDC Distributed Active Archive Center (DAAC).

Landsat 7 data will be available for ordering within

24 hours after they have been received at EDC. Users

query metadata and browse images to determine if the

archive contains data files suitable for their use. Data requested can be delivered either electronically or in a digital format on electronic tape or CD-ROM by common

carrier.
74 Mission Elements • 1999 EOS Reference Handbook

Landsat 7 Calibration and Validation

Calibration is essential to the role of Landsat 7 in the EOS

era. In order to realize the full potential of the integrated

remote sensing systems under development by the Office

of Earth Science, Landsat 7 data must be used in concert

with data from the other satellites.

Special solar calibrators on Landsat 7 will allow much

improved ETM+ calibrations relative to the earlier Thematic Mapper (TM) and Multi-Spectral Scanner (MSS)

sensors on Landsats 4 and 5. These new full- and partialaperture solar calibrators will permit use of the sun, with

its known exo-atmospheric irradiance, as an absolute radiometric calibration source.

The data provided by the on-board solar calibrators

will be augmented by an internal calibration lamp and

occasional ground-based validation experiments. These

calibration procedures will permit the Landsat 7 data to

be radiometrically corrected to within 5 percent and to

geometrically locate the scene on the Earth to within

250 m. This level of accuracy is consistent with the radiometric requirements for the other EOS sensors, allowing easier integration with data from other EOS satellites.

Landsat 7 Level 0R Products

The primary user product is Level 0R data—an essentially raw data form that is marginally useful prior to radiometric and geometric correction. A Landsat 7 0R product contains all the ancillary data required to perform these

corrections including a Calibration Parameter File (CPF)

generated by the Landsat 7 Image Assessment System.

The Landsat 7 Processing System (LPS) spatially

reformats Earth imagery and calibration data into Level

0R data. This involves shifting pixels by integer amounts

to account for the alternating forward-reverse scanning

pattern of the ETM+ sensor, the odd-even detector arrangement within each band, and the detector offsets inherent to the focal-plane-array engineering design. All LPS

Level 0R corrections are reversible; the pixel shift parameters used are documented in the CPF.

Landsat 7 Level 1R Products

The Level 1R product is a radiometrically corrected 0R

product. Radiometric correction is performed using either gains in the Calibration Parameter File or gains computed on the fly from the Internal Calibrator (IC). The

choice is available to a user when the product is ordered.

The biases used are alway calculated from the IC data.

Image artifacts such as banding, striping, and scan-correlated shift are removed prior to radiometric correction.

Radiometric corrections are not reversible. The Level 1R

product geometry is identical to the input Level OR data.

During Level 1R product rendering, image pixels are

converted to units of absolute radiance using 32-bit floating point calculations. Pixel values are then multiplied

by 100 and converted to 16-bit integers prior to media

output. Two digits of decimal precision are thus preserved.

The 16-bit 1R product has twice the data volume of a like

0R product.

Landsat 7 Level 1G Products

The Level 1G product is a radiometrically and systematically corrected 0R image. The correction algorithms model

the spacecraft and sensor using data generated by onboard

computers during imaging events. Primary inputs are the

PCD, which includes the attitude and ephemeris profiles,

and the mirror scan correction data. Refined parameters

from the CPF are also used to improve the overall geometric fidelity of the Level 1G product.

During processing the Level 0R image data undergoes two-dimensional resampling according to user-specified parameters including output map projection, rotation

angle, pixel size, and resampling kernal. The following

seven map projections are supported:

• Universal Transverse Mercator

• Lambert Conformal Conic

• Transverse Mercator

• Polyconic

• Oblique Mercator

• Polar Stereographic

• Space Oblique Mercator

The end result is a geometrically rectified product free

from distortions related to the sensor (e.g., jitter, viewangle effects), satellite (e.g., attitude deviations from nominal), and Earth (e.g., rotation, curvature).

The systematic Level 1G correction process does not

employ ground control or relief models to attain absolute

geodetic accuracy. Residual error in the systematic Level

1G product will be appoximately 250 meters (1 sigma) in

flat areas at sea level. Precision correction employs ground

control points to reduce geodetic error of the output product to approximately 30 meters. This accuracy is attained

in areas where relief is moderate.

Terrain-correction processing, employing both

ground control points and digital elevation models, can

further reduce geodetic error of the output product to less

than 30 meters in areas where terrain relief is substational.

Users requiring higher level products of this accuracy

would be best served ordering Level 0R data for in-house

processing or contacting a value-added service organization with such capabilities.

Landsat 7 Data Product Formats

Landsat 7 Level 0R and 1R data products are packaged in

Hierarchical Data Format (HDF)—an open standard selected by NASA for Earth Observing System (EOS) data
1999 EOS Reference Handbook Mission Elements • 75

products. HDF is a self-describing format that allows an

application to interpret the structure and contents of a file

without outside information. HDF allows Landsat 0R and

1R products to be shared across different computer platforms without modification and is supported by a publicdomain software library consisting of access tools and

various utilities.

Product users are directed to the Landsat 7 0R Distribution Product Data Format Control Book, Volume 5

(PDF) for details regarding the HDF design used for the

0R product. Included are references to NCSA-authored

documentation. New users should begin with “Getting

Started with HDF” while the HDF User’s Guide and HDF

Reference Manual are excellent resources for the HDF

programmer.

The HDF Level 0R and Level 1R formats are nearly

identical. Exceptions include the united PCD and MSCD

files and an enhanced product-specific metadata file that

reflects Level 1R correction characteristics. Additional

information unique to the Level 1R product can be found

in the ESDIS Level 1 Product Generation System Output

Files DFCB.

Level 1G data products are available in HDF, FAST,

and GeoTIFF formats. The Level 1G HDF product is also

described in the Landsat 7 0R Distribution Product Data

Format Control Book, Volume 5 (PDF) and the ESDIS

Level 1 Product Generation System Output Files DFCB.

A derivative of the Fast Format (Fast-L7) used by

Space Imaging, formerly EOSAT, for Landsat (FAST-B)

and Indian Remote Sensing products (Fast-C) was created for Landsat 7 Level 1G products. A full description

of the Fast L-7 Format can be found in the the ESDIS

Level 1 Product Generation System Output Files DFCB.

Level 1G Geographic-tagged-image file format

(GeoTIFF) is based on Adobe’s TIFF—a self-describing

format developed to exchange raster images such as

clipart, logotypes, and scanned images between applications and computer platforms. For detailed information

regarding the Landsat 7 GeoTIFF format please refer to

the the ESDIS Level 1 Product Generation system Output Files DFCB. For GeoTIFF details, please refer to the

GeoTIFF Format Specification.

QuikScat Mission

QuikScat is a rapid response mission designed to acquire

global radar backscatter and ocean surface wind speed

and direction data using the SeaWinds scatterometer instrument. Flight of QuikScat minimizes the gap in broadswath vector wind data caused by the loss of the ADEOS

spacecraft and its NASA Scatterometer (NSCAT) in June,

1997. A second SeaWinds instrument will fly on the

ADEOS-II mission, planned for launch in late 2000. The

QuikScat spacecraft was built by Ball Aerospace and the

mission was ready for flight in November, 1998. QuikScat

was successfully launched on June 19, 1999 onboard a

Titan-II launch vehicle (the mission was delayed for 7

months owing to a series of Titan launch failures).

QuikSCAT is in a sun-synchronous (803 km altitude) orbit. Following initial validation, SeaWinds/QuikScat will

provide ocean vector wind data with an accuracy and resolution equivalent to NSCAT. The broad-swath measurements will allow nearly 90% of the global oceans to be

covered on a daily basis. QuikScat is planned to operate

continuously for at least two years, thereby acquiring

unique vector wind data and providing at least a 6 month

overlap with the ADEOS-II/SeaWinds mission.

Terra

Planned for launch in 1999, the Terra flight includes five

instruments to be placed into a polar, sun-synchronous,

705-km orbit by an Intermediate Expendable Launch Vehicle (IELV) Atlas IIAS. The launch will take place from

the U.S. Air Force Western Space and Missile Center

http://winds.jpl.nasa.gov/missions/

quikscat/quikindex.html

http://terra.nasa.gov/
76 Mission Elements • 1999 EOS Reference Handbook

(WSMC). The payload consists of ASTER, CERES (dual

scanner), MISR, MODIS, and MOPITT.

Terra will have a descending equatorial crossing time

of 10:30 a.m., when daily cloud cover is typically at a

minimum over land such that surface features can be more

easily observed. The instrument complement is intended

to obtain information about the physical and radiative

properties of clouds and aerosols (ASTER, CERES,

MISR, MODIS); air-land and air-sea exchanges of energy, carbon, and water (ASTER, MISR, MODIS); measurements of important trace gases (MOPITT); and volcanology (ASTER, MISR, MODIS). CERES, MISR, and

MODIS are provided by the U.S., MOPITT is provided

by Canada, and ASTER is provided by Japan. The Terra

spacecraft design (see Figure 7 on pg. 71) will support an

instrument mass of 1,155 kg, an average power for spacecraft and instruments of 2.5 kW (3.5 kW peak), and an

average data rate of 18 Mbps (109 Mbps peak). Onboard

solid-state recorders will collect at least one orbit’s data

for playback through TDRSS, even though a playback on

each orbit is planned.

Follow-on missions are planned to continue the key

measurements to be made by Terra. The objective is to

benefit from technological advances being made in the

small-satellite arena to reduce the overall life-cycle cost

of the program, while maintaining the commitment to provide continuity of critical observations made by the Terra

mission.

The Terra spacecraft will also include the Direct Access System (DAS), which is composed of the Direct Playback (DP) subsystem, the Direct Broadcast (DB) subsystem, and the Direct Downlink (DDL) subsystem. Terra

data will be recorded and played back via TDRSS, and

DAS will provide a backup option for direct transmittal

of onboard data to ground receiving stations via an Xband transmitter (DP subsystem) should the satellite lose

its TDRSS link. DAS will also support transmission of

data to ground stations of qualified EOS users around the

world who require direct data reception. These users fall

into three categories:

• EOS team participants and interdisciplinary scientists

who require real-time data to conduct or validate field

observations, to plan aircraft campaigns, or to observe

rapidly changing conditions in the field;

• International meteorological and environmental agencies that require real-time measurements of the atmosphere, storm and flood status, water temperature, and

vegetation stress; and

• International partners who require receipt of data from

their high-volume EOS instruments at their own analysis centers for engineering quality checks and scientific studies.

The DB subsystem will broadcast MODIS data at 13

Mbps. At this rate, properly equipped ground stations can

receive, process, and display the swath data as the EOS

spacecraft passes within range.

ACRIMSAT

The ACRIMSAT spacecraft

is scheduled for launch in

October 1999 carrying the

Active Cavity Radiometer

Irradiance Monitor

(ACRIM) III. The intent of

the experiment is to monitor the Total Solar Irradiance

(TSI) with maximum precision and provide an important link in the long-term TSI

database. The ACRIM III experiment will provide all solar-maximum TSI results in solar cycle 23.

The science objectives of the mission are to extend

the TSI database accumulated by Nimbus7/ERB, SMM/

ACRIM I, UARS/ACRIM II, and SOHO/VIRGO and to

contribute data to the U.S. Global Change Research Program to understand solar influences on climate.

SAGE III Series

A SAGE III instrument will be placed into a high-inclination orbit on a Russian Meteor 3M-1 spacecraft in 1999

and into a mid-inclination orbit (51.6 ̊) on the International Space Station (ISS) in 2003. Plans are underway to

identify a flight platform for this mission. A combination

of high- and low-inclination orbits is required to optimize

collection of occultation data at all latitudes. SAGE III

http://acrim.jpl.nasa.gov/

http://aesd.larc.nasa.gov/GL/GLE/

text/sage.html
1999 EOS Reference Handbook Mission Elements • 77

will make long-term trend measurements of aerosols,

ozone, water vapor, and clouds from the middle troposphere through the stratosphere—important parameters

for radiative and atmospheric chemistry models.

NMP/EO-1

Earth Observing-1

(EO-1), planned

for launch in late

1999, is the first of

the NMP Earth science technology

missions. One of

the key objectives

of this mission is to ensure the continuity of future Landsat

data. EO-1 will validate advanced technologies contributing to the reduction in cost of Landsat follow-on missions. EO-1 will fly at an altitude of 705 km at an inclination of 98.2 ̊ in a sun-synchronous orbit with an equatorial crossing of nominally 10:01 a.m. EO-1 orbit will be a

sun-synchronous orbit at the same altitude but slightly

offset from that of Landsat 7, such that the EO-1 spacecraft will fly over the same ground track as Landsat 7 but

approximately one minute behind. This mission will provide paired scene comparisons between the EO-1 Advanced Land Imager (ALI) and the Landsat 7 Enhanced

Thematic Mapper Plus (ETM+) imager. ALI employs a

pushbroom data acquisition method and has multispectral capabilities ranging from 0.4 to 2.5 μm. In addition

to ALI, EO-1 carries Hyperion, a hyperspectral scanner.

The required mission life is one year, with possible extended operation.

Jason-1

The global sea-surface topography measurements currently being provided by the TOPEX/Poseidon mission

are of unparalleled accuracy and are providing a critically

needed ability to monitor accurately the global ocean circulation at a temporal resolution of 10 days. These data

provide new opportunities for monitoring ocean phenomena and developing models to predict long-term global

change.

The need for continuing these measurements has been

jointly recognized by NASA and CNES, with the result

of a follow-on cooperative mission called Jason-1. Jason-1

is intended to be the first in a series of semi-operational

satellites for oceanographic applications and research. Jason-1 will be flown in the same 66o inclination non-sunsynchronous orbit as TOPEX/Poseidon, flying in formation with TOPEX for the first 6 months (or as long as

TOPEX lasts). The primary instrument on Jason-1 will

be the CNES solid-state altimeter, a dual-frequency altimeter, Poseidon-2, based on the currently flying Poseidon altimeter. The altimeter instrument suite includes the

Jason Microwave Radiometer, a new technology radiometer utilizing MMIC technology and reduced in mass from

the TOPEX radiometer by an order of magnitude. The

Precision Orbit Determination package includes the GPS

Receiver, DORIS, and a Laser Retroreflector Array. The

instruments will be integrated with the new PROTEUS

smallsat spacecraft from CNES/Aerospatiale, and

launched in 2000.

ESSP Missions

The Earth System Science Pathfinder (ESSP) program

provides a new Office of Earth Science (OES) capability

for addressing global-change research. It provides a periodic “window of opportunity” to accommodate new scientific priorities and infuse new scientific participation

into the OES program. The ESSP program will consist of

small, quick-turnaround, low-cost missions launched on

a yearly basis. Four missions have been selected from

proposals submitted in response to the two ESSP Announcements of Opportunity: Vegetation Canopy Lidar

(VCL), Gravity Recovery and Climate Experiment

(GRACE), Pathfinder Instruments For Cloud And Aerosol Spaceborne Observations-Climatologie Etendue des

Nuages et des Aerosols (PICASSO-CENA), and Cloudsat

with an advanced cloud-profiling radar.

http://eo1.gsfc.nasa.gov/

http://topex-www.jpl.nasa.gov/jason1/

http://essp.gsfc.nasa.gov/
78 Mission Elements • 1999 EOS Reference Handbook

VCL

VCL will characterize the three-dimensional structure of

the Earth by using a multi-beam laser to measure vegetation-canopy height and vertical distribution, and groundsurface topographic elevations to within one meter. These

data will be used for two main science objectives:

• Landcover characterization for terrestrial ecosystem

modeling, monitoring and prediction, and climate modeling and prediction; and

• global reference data sets of topographic spot heights

and transects.

GRACE

GRACE, to be

launched in July

2001, will produce

a new model of the

Earth’s gravity

field with unprecedented accuracy every 12-to-15 days for 5 years. GRACE

unravels global climatic issues by:

• Measuring the meanderings of ocean bottom currents;

• enabling a better understanding of ocean surface currents and ocean heat transport;

• watching the mass of the oceans change;

• watching the varying size of ice sheets and glaciers;

and

• monitoring soil moisture and the state of major aquifiers.

PICASSO-CENA

PICASSOCENA, which

is to be

launched in

March 2003,

will employ

light detection

and ranging

(lidar) instrumentation to profile the vertical distribution of clouds and

aerosols, while another instrument will simultaneously

image the infrared (heat) emission of the atmosphere. During the daylight half of its orbit, PICASSO-CENA will

measure the reflected sunlight in an oxygen absorption

band and take images of the atmosphere with a wide-field

camera. PICASSO-CENA, together with EOS satellites,

will establish the scientific basis for understanding the

dynamics and energetics of the Earth’s atmosphere in support of short-term weather and long-term climate forecasts.

Cloudsat

Cloudsat, which

will fly in 2003, is

a mission focused

on understanding

the role of optically

thick clouds on the

Earth’s radiation

budget. It will use

an advanced cloud-profiling radar to provide information

on the vertical structure of highly dynamic tropical cloud

systems. This new radar will enable measurements of

cloud properties for the first time on a global basis, revolutionizing our understanding of cloud-related issues.

ADEOS Missions

Japan launched the polar-orbiting ADEOS mission in

August 1996. It was designed for a 3-year mission lifetime. Early termination of ADEOS in June 1997 resulted

from solar-array failure. ADEOS II is expected to be

launched in December 2000. The objectives of ADEOS

include Earth surface, atmospheric, and oceanographic

remote sensing. ADEOS II will be launched into a sunsynchronous, 98.6° inclination orbit with an 800-km altitude, and an equatorial crossing time of 10:30 a.m. The
1999 EOS Reference Handbook Mission Elements • 79

ADEOS satellite had a ground-track repeat cycle of 41

days, providing global OCTS coverage every 3 days and

daily coverage (sampled) for AVNIR.

ADEOS

ADEOS, launched

in 1996, flew the

following instruments:

• AVNIR – Five

visible/near-infrared bands (0.42-0.89 μm); 16- or 8-m

resolution; 80-km swath; ±40° across-track pointing;

stereo capability; observation of sunlight reflected by

the Earth’s surface (developed by NASDA).

• ILAS – Infrared occultation device; one visible band at

0.753-0.784 μm, and one infrared band at 6.21-11.77

(16-cm-1 resolution); 2-km IFOV; observations from

10-60 km, approximately 2-km vertical resolution; retrieval of stratospheric ozone and related species at high

latitudes (provided by Japan’s Environmental Agency).

• IMG – Nadir-looking Fourier transform infrared spectrometer; range 3.3-14.0 μm, with a spectral resolution

of 0.1 cm-1; ~8 km2 foot print; vertical resolution ~2-6

km depending on species; observation of carbon dioxide, methane, and other greenhouse gases (provided by

MITI).

• NSCAT – 14 GHz (Ku band) scatterometer; resolution

of 25 km; two 600-km swaths; used for retrieval of wind

speed and direction over the oceans (provided by

NASA).

• OCTS – Six visible bands centered on 0.412, 0.443,

0.490, 0.520, 0.565, and 0.670 μm, 20-nm bandwidth,

S/N = 450-500; two near-infrared bands centered on

0.765 and 0.865 μm, 40-nm bandwidth, S/N = 450-500;

four thermal-infrared bands centered on 3.7, 8.5, 11.0,

and 12.0 μm, 330- to 1,000-nm bandwidth, NEDT 0.15

to 0.20 K at 300 K; 700-m resolution; 1,400-km swath;

±20° along-track tilting; measurement of ocean color

and sea-surface temperature (developed by NASDA).

• POLDER – Views ±55° (cross- and along-track); 7×6-

km nadir footprint; nine bands in the visible and nearinfrared, 0.443 to 0.910 μm with 10- to 20-nm bandwidth; all-polarization measurements in three of the nine

bands (provided by CNES).

• RIS – 0.5-m diameter corner-cube retro-reflector to derive column density of ozone and trace species from

laser absorption measurements. A ground station in the

Kanto area transmitted and received laser pulses in the

wavelength region from 0.4 to 14 μm (provided by

Japan’s Environmental Agency).

• TOMS – Six wavelength bands in the region from

0.3086-0.360 μm, with 1-nm bandpass; IFOV 92 km at

nadir; cross-track scan 108° (37.3° steps); retrieved

daily global ozone (provided by NASA).

ADEOS-II

ADEOS II, to be launched

in December 2000, will be

the main Japanese contribution to IEOS, since the

prior ADEOS mission falls

more within the framework

of ESE Phase I than the

EOS era (see Earth Science

Enterprise section of this

Handbook). The basic design of ADEOS II is under way.

It will have orbital specifications similar to those of the

ADEOS mission. AMSR-E and GLI will be the core facility instruments, to be complemented by ILAS-2,

POLDER, and SeaWinds.

• AMSR-E – Advanced Microwave Scanning Radiometer designed to observe atmospheric and oceanic water vapor profiles, precipitation, water vapor distribution, cloud water, sea surface temperature, sea ice, and

sea surface wind speed; employs six frequencies in the

6 to 90 GHz range, with vertical and horizontal polarization, to secure a temperature resolution of 0.2-to-1

K, at 1 K (goal) radiometric accuracy; instrument design employs a 2-m antenna aperture.

• GLI – Imaging spectrometer for global monitoring of

biological and physical processes in the spectral range

from the ultraviolet to the thermal infrared; 36 bands,

with a bandwidth of 10 nm to 1 μm and a signal-tonoise ratio of less than 1,000; 1,600-km swath; instantaneous field-of-view of less than 1 km (some bands

are 250 m); instrument design based on OCTS

(ADEOS) and MODIS heritage.

• ILAS-II – Consists of two channels additional to those

on ILAS

http://echo.gsfc.nasa.gov/adeos/adeos.html

http://yyy.tksc.nasda.go.jp/Home/Projects/ADEOS-II/

index_e.html
80 Mission Elements • 1999 EOS Reference Handbook

• POLDER – Views ±55° (cross- and along-track); 7×6-

km nadir footprint; nine bands in the visible and nearinfrared, 0.443 to 0.910 μm with 10- to 20-nm bandwidth; all-polarization measurements in three of the nine

bands (provided by CNES).

• SeaWinds – The SeaWinds scatterometer will provide

high accuracy wind speed and direction measurements

over at least 90% of the ice-free global oceans every 2

days. SeaWinds will provide a continuing set of long

term wind data for studies of ocean circulation, climate,

air-sea interaction and weather forecasting. SeaWinds

is a follow-on to the NASA Scatterometer (NSCAT)

which is a sensor on ADEOS and will, like NSCAT,

provide measurements of ocean surface winds in all

weather and cloud conditions. SeaWinds improves on

NSCAT by using scan-beam rather than fan-beam technology. For more information about SeaWinds see the

Instruments Section.

EOS PM

Current plans call for EOS PM to be launched on December 21, 2000. This satellite will include six instruments to

be placed into a polar, sun-synchronous, 705-km orbit.

The EOS PM instrument complement will be integrated

onto the EOS common spacecraft described earlier, with

the spacecraft boosted into orbit by a Medium Expendable Launch Vehicle (MELV) launched from WSMC. The

payload consists of AIRS, AMSU-A, HSB, CERES,

AMSR-E, and MODIS. The EOS PM spacecraft will have

an afternoon equatorial crossing time to enhance collection of meteorological data by the atmospheric sounders

onboard. The instrument complement is designed to provide information on cloud formation, precipitation, water vapor, air temperature, and radiative properties (AIRS,

AMSU-A, HSB, CERES, MODIS) and sea-ice concentration and temperature, sea-surface temperature, snow

cover, and soil moisture (AMSR-E, MODIS). AIRS,

AMSU-A, CERES, and MODIS are provided by the U.S.;

HSB and AMSR-E will be provided by the Brazilian Space

Agency and NASDA, respectively. The EOS PM spacecraft will include the Direct Broadcast (DB)and Direct

Playback (DP) capabilities of DAS (see the Terra writeup), with the DB subsystem transmitting all instrument

data.

The EOS PM spacecraft design will support an instrument mass of 1,100 kg, average power for the instruments of 1,200 W (1,630 W peak), and an average data

rate of 7.7 Mbps (12.5 Mbps peak).

As with Terra, follow-on missions are planned to continue the key measurements to be made by EOS PM. In

addition, discussions are underway with the Integrated

Program Office (IPO) to identify common observational

capabilities between EOS PM and the National Polar-orbiting Operational Environmental Satellite System

(NPOESS). To the extent that such common capabilities

can be identified, the EOS PM follow-on mission may be

modified; however, the continuity of basic observations

beyond the EOS PM mission remains a major priority of

NASA.

ICESat

The EOS ICESat mission will fly the Geoscience Laser

Altimeter System (GLAS) instrument. GLAS is a solidstate neodymium:yttrium-aluminum-garnet (Nd:YAG)

laser altimeter, including integral star trackers and GPS

for precise altitude and orbit determinations. The GLAS

science objectives are ice-topography and mass-balance

measurements. In addition, the GLAS instrument, with a

minor modification to double the laser frequency to produce visible pulses as well as near-infrared pulses, will

provide cloud property information not otherwise available from passive sensors, especially the high ice clouds

common over polar areas. Finally, the third science objective of the ICESat mission will be to provide a landtopography data set by processing the altimeter data

throughout its orbit, in addition to the polar coverage over

ice sheets.

The planned launch date for ICESat was advanced

one year during the Biennial Review when the implementation approach for the mission took advantage of the

Rapid Spacecraft Procurement initiative. Using the commercial spacecraft bus, ICESat’s launch readiness date is

now mid-2001.

http://eos-pm.gsfc.nasa.gov/

http://icesat.gsfc.nasa.gov/
1999 EOS Reference Handbook Mission Elements • 81

EOS CHEM

The EOS Chemistry mission, planned for a December

2002 launch, consists of four instruments on a common

spacecraft that will be launched into a 705 km, 98.2o inclination, polar sun-synchronous orbit. The mission is designed for a 5-year life with a goal of 6 years of operation. The spacecraft will have an ascending-node equatorial crossing time of 1:45 p.m. The objective of the EOS

Chemistry mission is to study the chemistry and dynamics of the Earth’s atmosphere, with emphasis on the upper troposphere and lower stratosphere (5-20 km). The

mission will measure ozone, aerosols, and several key

atmospheric constituents that play an important role in

atmospheric chemistry, air quality, and climate. This mission will help in understanding the chemical and pollutant transport phenomena that are essential ingredients in

evaluating the environmental policies and international

agreements on chlorofluorocarbon (CFC) phase out.

The Chemistry satellite is based on the EOS Common Spacecraft, the same platform hosting the PM mission. The spacecraft total weight is 2967 kg, of which

1200 kg is the instrument weight. The spacecraft is modular in design and is easily adaptable to the mission-specific needs.

The High Resolution Dynamics Limb Sounder

(HIRDLS) is an infrared limb-scanning radiometer designed to sound the upper troposphere, stratosphere, and

mesosphere to determine temperature; the concentrations

of O3, H2O, CH4, N2O, NO2, HNO3, N2O5, CFC11,

CFC12, ClONO2, and aerosols; and the locations of polar stratospheric clouds and cloud tops. HIRDLS is a joint

venture between NASA and the U.K. Natural Environment Research Council. The U.S. portion of the instrument is being built by the University of Colorado with

Lockheed Martin as the system integration contractor.

The Microwave Limb Sounder (MLS) is designed to

measure the stratospheric temperature and numerous

chemical species (i.e., O3, H2O, ClO, HCl, OH, HO2, N2O,

CO, HOCl, BrO and HNO3). The scientific priorities and

objectives of the MLS investigation are to study and monitor the chemistry of the lower stratosphere and upper troposphere. In the middle and upper stratosphere, MLS

monitors ozone chemistry by measuring radicals, reservoirs, and source gases in chemical cycles that destroy

ozone. SO2 is also measured by the MLS instrument to

assess the effects of volcanoes. The instrument is designed

and built by JPL.

The Tropospheric Emission Spectrometer (TES) is a

high-resolution infrared-imaging Fourier transform spectrometer that has the capability to make both limb and

nadir observations. TES is a pointable instrument and can

access any target within 45 degrees of the local vertical,

or produce regional transects up to 1700-km in length

without any gaps in coverage. TES employs both the natural thermal emission of the surface and atmosphere and

reflected sunlight, thereby providing day-night coverage

anywhere on the globe. Observations from TES will further understanding of long-term variations in the quantity, distribution, and mixing of minor gases in the troposphere, including sources, sinks, troposphere-stratosphere

exchange, and the resulting effects on climate and the biosphere. TES will provide global maps of carbon monoxide and its photochemical precursors. TES is also being

designed and built by JPL.

The fourth instrument is primarily dedicated to the

measurement of ozone. The Ozone Monitoring Instrument

(OMI) will complement the measurements made by the

other EOS Chemistry instruments. OMI is an ultraviolet

grating spectrometer specifically designed for the global

mapping of ozone. This instrument will continue the

TOMS ozone data record begun in 1978, but will employ

new technology. In addition to global total-ozone mapping, the instrument will be capable of deriving surface

UVB radiation and aerosol data over land and oceans on

a global scale. The instrument will also detect column

amounts of NO2 that will be highly complementary to the

other EOS Chemistry instruments. OMI will be furnished

by the Netherland’s agency for aerospace programs

(NIVR), with major contributions from Finland.

EOS Follow-On

Missions

During FY 1997, the Earth Science Enterprise completed

its first Biennial Review. The intent of this review was to

reassess the Enterprise’s strategic direction in response

to improved scientific understanding, evolving technology, new opportunities in the commercial, international,

and interagency arenas, and budget constraints.

Our understanding of global climate change has

evolved, and will continue to evolve. The measurement

sets currently defined as part of the EOS Program are appropriate for addressing the science questions as we understand them today. However, it is likely that as new

information emerges, changing science priorities will result in additions and/or deletions to our desired measurehttp://eos-chem.gsfc.nasa.gov/
82 Mission Elements • 1999 EOS Reference Handbook

ment set. In addition, technology continues to evolve,

making possible a transition to smaller, more-focused

science missions. Opportunities for partnerships with other

U.S. and international agencies as well as with the private sector will continue to grow, particularly as other

nations continue to develop their own space programs and

the commercial remote-sensing market continues to expand.

In order to respond effectively to these changes, we

are modifying our technology and implementation strategies for the follow-on missions (beyond Terra, PM-1,

and Chemistry). Key characteristics of the new paradigm

include enhanced scientist-technologist interaction, ongoing evaluation of our measurement strategies, evolution to smaller, more-focused missions, seeking new

partnering opportunities, and learning from past experience before committing to a follow-on measurement set.

The first step in defining the follow-on missions was

the convening of a Science Workshop for the Land Cover

and Land-Use science theme, which was held in May

1998. This workshop defined the measurement strategies

for acquiring global spaceborne data needed to support

this theme in 2004 and beyond (after the end of the Terra

mission). This Workshop was held in anticipation of the

release of a Request for Information (RFI) that was subsequently issued to the scientific community in May 1998.

This RFI resulted in 100 mission concepts that were reviewed by six discipline panels that prioritized them from

the perspective of scientific research or application requirements:

• Atmospheric Chemistry

• Atmospheric Climate Physics & General Circulation

• Global Water Cycle, Hydrology, & Mesoscale Weather

• Oceanography & Polar Research

• Land Cover, Land Use, & Terrestrial Ecosystems

• Geodynamics, Geology, & Natural Hazards

Twenty-three high-priority mission concepts were

identified among the proposed measurement ideas, and

passed to an industrial contractor for study and cost estimation. These mission concepts were subsequently subdivided into three distinct flight mission programs: (i)

Systematic EOS measurement program, consisting of

consistent measurements of critical Earth system parameters over the time period needed to achieve the science

objective, (ii) Earth Probe program, consisting of original and conclusive information on specific Earth system

processes of major significance for global change research

or phenomena heretofore inaccessible to global observation, and (iii) New Millennium Program, consisting of

demonstration missions involving innovative techniques

that allow the reduction in cost of existing measurements

or testing of new capabilities that have the potential of

enabling new science, if successful.

Following the discipline panel review, ten systematic measurement concepts were consolidated into a nominal EOS Follow-On Mission Scenario, and seven exploratory research concepts were taken as illustrative examples

of the Earth System Science Pathfinder/Earth Probe program.

The results of this process were subsequently reviewed at a workshop held in Easton, Maryland in August 1998. This workshop refined and enhanced the definition of follow-on missions, which are being further

scoped at the present time.

A whole spectrum of implementation options is possible, ranging from the traditional mode of missions integrated by NASA Project Managers, to purchases of commercial remote-sensing data, to science missions managed and developed entirely by individual Principal Investigators. In this last option (which was endorsed by

the Biennial Review panel), the PI would be responsible

for implementing the complete mission. Limited oversight, “light-touch” management principles would be applied, and standard industry procedures and practices

would be encouraged.

Alternatively, the PI could be responsible for just the

instrument development. This development would proceed independent of the eventual spacecraft or mission

assignment (thus avoiding having the mission schedule

driven by the slowest instrument development). A streamlined Project Office would be created late in the instrument development cycle and would oversee the build of

the flight model instrument(s), procurement of the spacecraft bus (through a recently established “catalog” procurement mechanism), and procurement of launch services.

A Science Implementation Plan, which will specify

the long-term science measurement priorities for the EOS

program, is being developed by the Office of Earth Science at Headquarters. Prior to the finalization of this plan,

a strawman set of follow-on missions and their cost estimates has been developed, based on the RFI process and

Easton workshop described above. This EOS follow-on

budget profile assumes that new technology development

efforts can be applied to minimize instrument costs and

that the application of rapid spacecraft procurements from

established spacecraft production lines can be used to create a flexible collection of small missions to fulfill the

objectives of the Implementation Plan. While a strawman

flight schedule was created, the actual flight schedule

(which will later form the program’s commitment) will

depend upon the outcome of the Science Implementation

Plan’s measurement priorities.
1999 EOS Reference Handbook Mission Elements • 83

POES Series

NOAA’s primary agency directive is to provide daily global data for operational forecasts and warnings, with very

high reliability. NOAA normally has two POES spacecraft in operation at the same time, one in a morning and

one in an afternoon orbit; each is replaced upon failure or

significant degradation of one of its primary sensors or

subsystems. Over 120 countries depend on the data from

the POES direct broadcast.

The present two-satellite POES system will continue

through 2002. The core instruments for the POES missions are AVHRR-3 and HIRS-3—an imager and an infrared sounder, respectively. POES spacecraft are also

equipped with the ARGOS data collection system, S&R,

and SEM. POES satellites in afternoon orbit (i.e., NOAA14, L, N/N ́) also carry SBUV. The stratospheric and microwave pair of sounders previously in use (i.e., SSU and

MSU) have recently been upgraded, beginning with

NOAA-15; NOAA-15 through -M will employ the

AMSU-A1/2 and AMSU-B sounder pair. NOAA-N/N ́

will carry an MHS instrument instead of the AMSU-B.

The United States and Europe have agreed in principle that Europe will take over responsibility for the

morning satellite of the POES global-coverage mission

in the 2002 time frame. Planning for this cooperative program includes flight of the NOAA/EUMETSAT operational meteorological payload aboard the Metop series.

Also, EUMETSAT will establish a high-latitude European

ground station to read out data from both the European

and U.S. (NOAA) satellites. Full exchange of data, in a

timely manner consistent with operational objectives, will

be conducted between NOAA and EUMETSAT. Current

plans are for these two agencies to provide morning

(EUMETSAT) and afternoon (NOAA) polar-satellite global coverage, with each using the same basic instrument

complements. The U.S. will provide the AMSU-A1/2,

AVHRR-3, HIRS-3, and SEM instruments to be flown

on Metop-1; EUMETSAT will provide the AMSU-B instruments for NOAA’s POES series; France will provide

the ARGOS systems for both the NOAA and EUMETSAT

missions; and Canada and France will jointly provide the

S&R systems for both NOAA and European polar missions. Each meteorological agency may add other instruments suitable to its particular orbit time and needs.

Direct broadcast of POES data will continue, with

European polar satellites also providing direct data broadcast services. In addition, data from potential operational

instruments on the EOS satellites will be accessed and

disseminated by NOAA.

The establishment and use of a high-latitude European ground station under the cooperative NOAAEUMETSAT agreement will eliminate blind orbits in coverage by polar-orbiting meteorological satellites. This

enhanced ground network will eliminate orbits wherein

the satellite fails to pass within line-of-sight for data transmission to its ground station. Both NOAA and

EUMETSAT’s meteorological payloads will be able to

downlink a full orbit’s worth of data at full resolution each

orbit. As such, there will no longer be a need for lowresolution Global Area Coverage (GAC) data to conserve

POES onboard data storage capacity. All POES data in

the cooperative program will be full-resolution Local Area

Coverage (LAC) data. The low-resolution, analog Automatic Picture Transmission (APT) as well as the Direct

Sounding Broadcast (DSB) of the current NOAA system

will be replaced with Low-Resolution Picture Transmission (LRPT) broadcasts. The High-Resolution Picture

Transmission (HRPT) data rate will be changed from 667

kbps to 3.5 Mbps, and the HRPT frequency will be

changed to 1704.5 MHz.

NOAA-15/L/M/N/N ́ Instruments

• ARGOS – Relays messages from data collection platforms at 401.0 and 136.77 MHz; receives platform and

buoy transmissions on 401.65 MHz; monitors over

4,000 platforms worldwide; outputs data via VHF link

and stores them on tape.

• AMSU-A1/2 – 15 channels (23-90 GHz) to measure

temperature profiles from ground level to 45 km, with

45-km nadir resolution (14-bit resolution); scan line

time of 8 sec includes full aperture calibration.

• AVHRR-3 – Six spectral channels (five full-time) at

0.58-0.68 μm, 0.72-1.0 μm, 1.58-1.64 μm (sun-side

readout)/3.55-3.93 μm (dark-side readout), 10.3-11.3

μm, and 11.5-12.5 μm, with an image resolution of 1-4

km (effective 11-bit resolution); infrared calibration capability, but no visible calibration.

• AMSU-B (NOAA-15 thru -M only) – Measures precipitation and water vapor profiles with two channels

at 89 and 157 GHz and three channels at 183.31 GHz

(±1, 3, and 7 GHz); scan line time is 8/3 sec; 15-km

nadir resolution (14-bit resolution) and full-aperture

calibration capability.

• HIRS-3 – 20 channels at 0.2-15 μm to cover the ground

to the troposphere, with 21-km nadir resolution (12-bit

resolution), a scan line time of 6.4 sec, and full aperture calibration.

• SBUV-2 (NOAA-L thru N/N ́ only) – 12 spectral channels to measure from 0.252-0.322 μm, with a 1-nm

bandpass; 256-sec spectral scan; 11.33° × 11.33° instantaneous field-of-view; 14-bit resolution; diffuserhttp://poes2.gsfc.nasa.gov/
84 Mission Elements • 1999 EOS Reference Handbook

plate calibration accomplished with an onboard spectral reflectance/transmittance measurement system;

operates only on the day side of the orbit, and performs

spectral calibration on the night side.

• S&R – Receives beacon signals at 121.5, 243, and

406.05 MHz (-154 dBm signal detection level); transmits in real-time at 1544.5 MHz to ground stations

around the world.

• SEM – Monitors particles and fields to measure and

predict solar events.

• MHS (NOAA-N, N ́ only) – 5-channel, self-calibrating microwave scanning radiometer. The channels in

the frequency range 89 to 183 GHz provide a humidity

profiling capability.

SORCE

The SOlar Radiation

and Climate Experiment (SORCE) consists of a small, freeflying satellite carrying four instruments to

measure solar radiation incident at the top

of the Earth’s atmosphere. It is scheduled

for launch in mid2002, carrying the Total Irradiance Monitor (TIM), Spectral Irradiance Monitor (SIM), Solar Stellar Irradiance

Comparison Experiment (SOLSTICE), and the XUV Photometer System (XPS).

Solar irradiance is the dominant energy source in the

Earth’s atmosphere, establishing much of the atmosphere’s

chemistry and dynamics, and becomes the dominant term

in the global energy balance and an essential determinant

of atmospheric stability and convection. The SORCE measurements will provide the requisite understanding of one

of the primary climate system variables. SORCE will provide daily measurements of total solar irradiance (TSI)

and spectral solar irradiance from 1 nm to 2000 nm and,

in the case of the ultraviolet measurements, will maintain

calibration by comparison to bright, early-type stars. SIM

will measure spectral irradiance from 200 nm to 2000 nm

with a resolution varying from 1 nm to 35 nm, SOLSTICE

will measure spectral irradiance from 115 nm to 300 nm

with a resolution of 1 nm, and XPS will measure six broadband samples from 1 nm to 31 nm and at Lyman α (121.6

nm).

NPOESS PREPARATORY

PROJECT (NPP)

NPP is a proposed joint space-flight mission of the NASA

Earth Science Enterprise and the National Polar-orbiting

Operational Environmental Satellite System (NPOESS)

Integrated Program Office (IPO). The two main objectives of this proposed mission are to provide risk reduction for NPOESS through pseudo-operational demonstration and validation of instruments and algorithms prior to

the first NPOESS flight, and to provide NASA and the

broad Earth-science community with the continuation of

calibrated, validated, and geo-located global imaging and

sounding observations beyond the Earth Observing System (EOS) Terra and PM missions. In this manner, the

proposed mission bridges between the EOS Terra and PM

missions, and the NPOESS mission, supporting the transition of selected long-term systematic Earth-science measurements from EOS to operational systems.

NPP, planned for launch in 2005 with a mission duration of 5 years, is being formulated using an end-to-end

mission-life-cycle methodology. Three instruments are

planned for NPP: Visible Infrared Imaging Radiometer

Suite (VIIRS) (including augmentations to support additional research observations and capabilities) provided by

the IPO, Cross-track Infrared Sounder (CrIS) provided

by the IPO, and Advanced Technology Microwave

Sounder (ATMS) provided by NASA. The ATMS instrument will combine the passive-microwave observation

capabilities of three heritage instruments (AMSU A1/A2

and MHS) into a single instrument of approximately the

size of one of the three heritage instruments, using advanced microwave-receiver electronics technologies.

The spacecraft for NPP, provided by NASA, will accommodate the three instruments, provide direct-toground transmission of stored mission instrument data,

and also provide direct broadcast of real-time instrument

data. Spacecraft flight operations and the spacecraft operations control center, provided by IPO, will provide the

operations of the spacecraft and instruments, including

on-orbit instrument-calibration activities.

The ground stations for NPP, provided by IPO, will

receive stored mission-instrument data, and route this data

to the continental United States using IPO-provided communications networks for processing. The planned

NPOESS Interface Data Processing Segment (IDPS), provided by IPO, will provide pseudo-operational processhttp://lasp.colorado.edu/sorce
1999 EOS Reference Handbook Mission Elements • 85

ing of NPP instrument data for use by the operational

community to assess NPP instrument and operational algorithm performance. Additional ground-processing capability, to provide additional support to the research community, will also be available for the generation of additional research products, such as calibration/validation

products and higher level products. Short- and long-term

archival and distribution capabilities to support research

funded through the Announcement of Opportunity process will also be provided.

The proposed NPP mission is currently in the formulation phase, and, should NASA and IPO agree to proceed to implementation, would enter into the implementation phase in 2001. The ATMS instrument, being the

subject of a separate NASA-IPO agreement, will proceed

to implementation in 2000 in order to support delivery to

the NPP mission in 2004.
86 Mission Elements • 1999 EOS Reference Handbook

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

SSBUV

ATLAS

NASA

Shuttle

Earth 

Observing

System

Earth

Probes 

and 

Related Earth

Science

NOAA

Japan

DoD

France

Space

Imaging

METOP

Landsat 7

POES

DMSP

GMS

Landsat 51

RESEARCH

METEOSAT

SPOT

TOMS, NSCAT/

ADEOS 4,9

ADEOS II /SeaWinds4

OPERATIONAL

NASA/USGS

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

ESA/

EUMETSAT

SRTM

GOES

LAGEOS-2 2

Meteor/TOMS 3

TOMS/EP

TOPEX/Poseidon 5

Jason-1 5

OrbView-2/SeaWiFS 6

TRMM 7

QuikScat/SeaWinds

Terra

Approved, Under 

Development, or

Operating Mission

Extended Mission

1 Will continue indefinitely

2 Joint with Italy 

3 Russian Satellite

4 Japanese Satellite

5 Joint with France 

6 OSC Data Purchase

7 Joint with Japan 

Continues beyond

2003

MSG

2003

LITE

SLA (2 more planned)

UARS

ACRIM

2003

8 NASA Launch 

9 Premature End of Operation 

10 Shuttle Mission

QuikTOMS

Meteor 3M 3/SAGE III

ERBS

Missions

Figure 8a. U.S. and International Partner Earth-Observing Missions
1999 EOS Reference Handbook Mission Elements • 87

VCL

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Earth 

Observing

System

(cont.)

DoE

ESA

Japan

Canada

ISS/SAGE III

SORCE

RESEARCH

Approved, Under 

Development, or

Operating Mission

Extended Mission

EOS CHEM

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

MSX

MTI

ERS-1

JERS-1

ADEOS 9

ALOS

GEOSAT Follow-On

DoD

ERS-2

Mos 1b

RESEARCH

Continues beyond

2003

Radarsat 1,8

GRACE

2003

New

Millennium

Program

(NMP)

Earth

System

Science

Pathfinder

(ESSP)

Program

EOS PM

ICESat

PICASSO-CENA

CloudSat

2003

ENVISAT-1

ADEOS II

Radarsat-2

1 Will continue indefinitely

2 Joint with Italy 

3 Russian Satellite

4 Japanese Satellite

5 Joint with France 

6 OSC Data Purchase

7 Joint with Japan 

8 NASA Launch 

9 Premature End of Operation 

10 Shuttle Mission

NMP/EO-1 (ALI)

Figure 8b. U.S. and International Partner Earth-Observing Missions
88 Mission Elements • 1999 EOS Reference Handbook

Figure 9. EOS Program Level Architecture

User Community

EOS Investigators

Earth Science Researchers Worldwide

Global Change Impact Studies

Educators and Students

EOSDIS

1620 GB/Day Processed Data Level I, II, III

Data Products

Level IV Data 

Products

International

Space

Station

SORCE

500 GB/Day Raw Data

28 GB/Day Raw Data

ICESat

ACRIMSAT

Landsat 7 EOS CHEM 

Jason-1

Other NASA

Missions and 

Instruments

International Data Purchase Terra 

ERBS

UARS

TOPEX /

 Poseidon

TRMM 

SeaWinds 

SAGE III

ESA

Canada

Japan

Russia

Brazil

Netherlands

Finland

France

U.K.

OrbView-2

EOS

PM
1999 ESE Reference Handbook EOS Instruments • 89

The EOS facility instruments were major instruments defined in

the Announcement of Opportunity (AO) for EOS as being developed and managed by various NASA Centers. The Centers were

to take charge of the engineering aspects and costs involved in the

development of the instruments. The AO invited proposals by scientists who wanted to serve as Team Leader or Team Member

(for facility instruments) of science teams that would provide oversight and guidance to the development of the facility instruments.

The science teams would be the source of the algorithms that would

lead to the products for each facility instrument. They would also

support instrument calibration and validation activities.

U.S. facility instruments that are now part of the EOS Program are AIRS (JPL), AMSU-A (GSFC), MODIS (GSFC), and

GLAS (GSFC). In addition to the U.S. facility instruments, the

Japanese partners in the Earth Science Enterprise have correspondingly provided the ASTER facility instrument (Japanese Ministry

of International Trade and Industry, MITI) and the AMSR-E facility instrument (National Space Development Agency of Japan,

NASDA). Brazilian partners (Brazilian National Institute for Space

Studies, INPE) have provided the HSB instrument. A coalition of

Finnish and Dutch partners has supplied the OMI facility instrument. The French Centre National d’Etudes Spatiales (CNES) is

providing the radar altimetry instrument, Poseidon 2.

The EOS Principal Investigator (PI) instruments were understood to be instruments that would be the responsibility of the

proposer and the proposer’s institution to develop and manage.

The selected proposers became the PIs for their own instruments

and assembled their own teams of co-investigators to provide the

algorithms for the products. The PI’s institution took responsibility for the engineering and cost aspects of the instrument’s development.

EOS Instrument Teams help define the scientific requirements

for their respective instruments and generate the algorithms that

will be used to process the data into useful data products. For indepth presentation of these algorithms, see the Algorithm Theoretical Basis Documents (ATBDs) page on the World Wide Web.

The entire document can be viewed using a PDF reader such as

Adobe Acrobat, by accessing the following location:

http://eospso.gsfc.nasa.gov/atbd/pg1.html

ACRIM III 90

AIRS•AMSU-A•HSB 93

AMSR-E 98

ASTER 102

CERES 106

EOSP 109

ETM+ 112

GLAS 114

HIRDLS 117

Jason-1 121

LIS 125

MISR 128

MLS 131

MODIS 134

MOPITT 138

OMI 141

SAGE III 143

SeaWinds 146

SORCE 149

TES 152

EOS Instruments
90 • EOS Instruments 1999 ESE Reference Handbook

ACRIMSAT

Key ACRIM III Facts

Monitors Total Solar Irradiance (TSI) with stateof-the-art precision and accuracy

Dedicated small-satellite/ACRIM III Instrument

combination (ACRIMSAT)

Redundant satellite design for 85% probability

of 5-year mission success

Launch scheduled for late 1999 as Pegasus

secondary payload

Heritage: ACRIM I (SMM) and ACRIM II (UARS)

Uses Active Cavity Radiometer type IV sensors

Three-fold sensor redundancy: one monitors TSI,

others used in phased mode to calibrate

degradation of monitoring sensor

Solar irradiance uncertainty ~ 0.1%; long-term

precision ~ 5 ppm per year

Sampling interval ~ 2 minutes

Science objectives of EOS/ACRIM III experiment

are in the fields of climatology and solar

physics

Sustained changes in the total solar irradiance (TSI) of as little as

a few tenths of one percent per century could be primary causal

factors for significant climate change. It is clear from paleo-climate research that solar-irradiance-driven climate changes have

occurred in the past. There is compelling evidence that some of

these may have been at least partially driven by intrinsic solar

variability. A precise, long-term record of TSI is required to provide empirical evidence of the sun’s role in climate change and to

separate its effect from other climate forcings such as greenhouse

warming. The same record, together with other solar observations,

will also yield an improved understanding of the physics of the

sun and the causes of luminosity variations, and could eventually

lead to a predictive capability for solar-driven climate change.

The National Research Council recently published its findings regarding research priorities for Solar Influences on Global

Change, one of the seven science elements of the U.S. Global

Change Research Program. Their recommendations include

“monitoring total and spectral solar irradiance from an uninterrupted, overlapping series of spacecraft radiometers employing

in-flight sensitivity tracking” as this element’s highest priority and

most urgent activity. The EOS/ACRIM III experiment is designed

to be a cost-effective, small-satellite approach to meeting that priority during the first phase of the Earth Observation System program (EOS) of the Earth Science Enterprise (ESE).

The sun is a variable star. Its luminosity has been found to

vary by 0.1 percent over a solar cycle in phase with the level of

solar magnetic activity. Photometric observations of many solartype stars have revealed that brightness variations correlated with

magnetic activity like the sun’s are a common phenomenon. Many

demonstrate higher variability than the sun, leading to speculation that the sun’s variability may have been greater in the past

and may be greater again in the future. This would clearly have

significant implications for climate change.

A precision TSI database, with resolution adequate to relate

centuries of systematic TSI variation to climate change, must be

compiled from the results of many flight experiments. With a nominal lifetime of 5 years per experiment, their contiguous results

must be related with the maximum precision accessible to current

technology, on the order of 10 ppm. This far exceeds the capability of current “ambient temperature” flight instrumentation to define the “absolute uncertainty” of the TSI (>1000 ppm) and even

that of cryogenic instrumentation currently under development

(>100 ppm). Modeling TSI, using ground-based observations of

proxy solar emission features, is orders of magnitude less precise.

The single approach capable of providing the required precision for the long-term TSI database with current measurement

technology employs an “overlap strategy” in which successive

ambient temperature TSI satellite experiments are compared in

flight, transferring their operational precision to the database. The

ACRIM III Active Cavity Radiometer Irradiance Monitor

http://acrim.jpl.nasa.gov/

ACRIMSAT URL
1999 ESE Reference Handbook EOS Instruments • 91

current generation of ambient temperature ACRIM flight

instrumentation has demonstrated a capability of providing annual precision ~ 5 ppm of the TSI.

The EOS/ACRIM III experiment was selected to provide the TSI database during the EOS mission. Observations during the first 5-year phase of EOS will be provided by an ACRIM III instrument, a miniaturized version of the technology flown successfully on NASA’s

Solar Maximum Mission, Upper Atmosphere Research

Satellite, Spacelab 1, and ATLAS missions. ACRIM III

will be flown on a dedicated small satellite, placed into

orbit as a secondary payload aboard a Pegasus launch

vehicle. The resulting ‘ACRIMSAT’ will be spin stabilized with the instrument’s solar-viewing axis aligned

with the sun-center within 0.25 deg. using magnetic torquers. The on-orbit operation and data down-linking will

be accomplished using a dedicated ground station supplied by the satellite manufacturer.

The objective of an early launch of ACRIMSAT is

the comparison of overlapping EOS/ACRIM III results

with results from the UARS/ACRIM II and SOHO/

VIRGO experiments. Results for the second phase of EOS

will be made by an experiment to be selected from responses to AO-97-MTPE-01. This launch, scheduled for

late 2001, combines the TSI database maintenance function with a new technology initiative designed to develop

a prototype instrument for both total and limited spectral

solar monitoring on an operational basis in the National

Polar-orbiting Operational Environmental Satellite System (NPOESS) program. Additional EOS TSI experiments will be required to bridge the gap between the second EOS phase and the launch of the first NPOESS satellite (2009).

Principal Investigator

Richard C. Willson

Richard C. Willson holds a doctoral degree in Atmospheric Sciences from the University of California-Los

Angeles, and B.S. and M.S. degrees in Physics from the

University of Colorado. He is a Senior Research Scientist in the employ of Columbia University’s Center for

Climate Systems Research. His work in this field, which

began at the University of Colorado and continued at the

Jet Propulsion Laboratory and Columbia University, has

been in the area of development of state-of-the-art solarirradiance measurement techniques for both total and

spectral irradiance. He developed prism, grating, and interference spectroscopy instrumentation for spectral observations in both laboratory and flight environments.

He developed the Active Cavity Radiometer instrumentation for total irradiance observations and has conducted

ACRIM III Parameters

Three ACR type IV sensors, individual shutters, differential

 operation

Phased use of sensors for degradation calibration

Monitor total solar irradiance: 5 ppm/year precision, 99.9%

 accuracy

Mass: 12 kg

Duty cycle: 55 minutes on sun each orbit

Power: 8 W (average)

Data rate: < 1 kbps

Thermal control by: Host spacecraft and instrument

 heater

Thermal operating range: 10-30°C

FOV: ±2.5°

Requires pointing to be provided by spacecraft

Solar Pointing: Spin stabilization about axis of

 symmetry

Pointing requirement: +/- 0.25 deg

flight experiments on balloons, sounding rockets, the

Space Shuttle, and satellite platforms. He has served as

the Principal Investigator for the Solar Maximum Mission ACRIM I, Space Shuttle Spacelab I and Atmospheric

Laboratory for Applications and Science (ATLAS)

ACRIM’s, Upper Atmosphere Research Satellite

(UARS) ACRIM II and EOS/ACRIM III experiments.

Co-Investigators

James Hansen - NASA/GISS

Hugh Hudson - University of California, San Diego

Alex Mordvinov - Institute of Solar-Terrestrial Phsyics,

Russia
92 • EOS Instruments 1999 ESE Reference Handbook

ACRIM III Data Products

Product Name

Total Solar Irradiance 0.1% :: 0.0005%

Accuracy

Absolute :: Relative

2 minutes

Temporal

Resolution

Horizontal

Resolution :: Coverage

Vertical

Resolution :: Coverage

N/A :: Top of Atmosphere

References

Willson, R.C., 1997: Total solar irradiance trend during

solar cycles 21 and 22. Science, 277, 1963-1965

Board on Global Change, National Research Council,

1994: Solar Influences on Global Change. National Academy Press, Washington, DC.

Willson, R.C., 1993: Irradiance observations of SMM,

Spacelab 1, UARS and ATLAS experiments. The Sun as

a Variable Star, J. Pap, C. Fröhlich, H. Hudson, and S.

Solanki, Eds., Cambridge University Press, 54-62.

Willson, R.C., and H.S. Hudson, 1991: The sun’s luminosity over a complete solar cycle. Nature, 351, 42-44.

Willson, R.C., 1979: Active cavity radiometer type IV. J.

Applied Optics, 18, 179-188.
1999 ESE Reference Handbook EOS Instruments • 93

Advanced Microwave Sounding

Unit

Selected for flight on EOS PM

Heritage: MSU

Microwave radiometer

Provides atmospheric temperature measurements from the

surface up to 40 km

Onboard NOAA-K/L/M

Phase C/D start December 1992

Instrument Delivery: December 1998

Prime Contractor: Aerojet General Corporation

Responsible Center: NASA/Goddard Space Flight Center

Key AMSU-A Facts

Humidity Sounder for Brazil

Key HSB Facts

Selected for flight on EOS PM

Heritage: AMSU-B

Microwave radiometer

Provides atmospheric water vapor profile measurements

Phase C/D start March 1997

Instrument Delivery: August 1999

Prime Contractor: Matra Marconi

Responsible Center: Brazilian National Institute for Space

Studies (INPE)

Key AIRS Facts

Selected for flight on EOS PM

Heritage: AMTS study

Infrared sounder

Measures the Earth’s outgoing radiation at 0.4 to

1.0 μm and 3.7 to 15.4 μm

Phase C/D start March 1991

Instrument Delivery: June 1999

Prime Contractor: Lockheed Martin

Responsible Center: Jet Propulsion Laboratory

Atmospheric Infrared Sounder

AIRS•AMSU-A•HSB

http://www-airs.jpl.nasa.gov/

AIRS URL
94 • EOS Instruments 1999 ESE Reference Handbook

AIRS has been selected to fly on the EOS PM satellite

with two operational microwave sounders: AMSU and

HSB. AIRS, AMSU-A, and HSB measurements will be

analyzed jointly to filter out the effects of clouds from

the IR data in order to derive clear-column air temperature profiles with high vertical resolution and accuracy,

plus high-accuracy surface temperatures. Together, these

instruments constitute an advanced sounding system,

relative to the High-Resolution Infrared Sounder/Microwave Sounding Unit (HIRS/MSU) system that currently

operates on NOAA satellites.

The data retrieved from the AIRS/AMSU-A/HSB

instrument complement will improve global modeling

efforts, numerical weather prediction, study of the global energy and water cycles, detection of the effects of

greenhouse gases, investigation of atmosphere-surface

interactions, and monitoring of climate variations and

trends. These objectives will be met through improvements in the accuracy of several weather and climate

parameters, including atmospheric temperature and water vapor, land and ocean surface temperature, cloud distribution and spectral properties, and outgoing longwave

radiation. Simultaneous observations of the atmosphere

and clouds from AIRS will allow characterization of the

spectral properties of clouds for enhanced understanding of their role in modulating the greenhouse effect;

and the increased resolution and number of infrared

sounding channels (an increase of two orders of magnitude beyond current operational sounders) will improve

the accuracy of weather forecasting.

AIRS, AMSU-A, and HSB together constitute a

single facility instrument program, so AIRS products are

often the result of joint calculations. Standard and research data products for the complement are:

Standard Products

• For the atmosphere, AIRS/AMSU-A will provide a

temperature profile, humidity profile, total precipitable water, fractional cloud cover, cloud-top height,

and cloud-top temperature.

• For the land, AIRS/AMSU-A will provide skin surface temperature, plus day and night land-surface

temperature difference. AIRS will provide outgoing

day/night longwave surface flux.

• For the ocean, AIRS/AMSU-A will provide skin surface temperature. AIRS will provide outgoing day/

night longwave surface flux.

Research Products

• For the atmosphere, AIRS/AMSU-A/HSB will provide a precipitation estimate, and tropopause and

stratopause heights. AIRS will provide outgoing

longwave spectral radiation and cloud optical thickness. AMSU-A will provide cloud thermodynamic

phase (ice/water) and cloud water content.

• For the land, AIRS/AMSU-A will provide surface

spectral emissivity, surface albedo, and net shortwave

flux.

• For the ocean, AIRS will provide net shortwave flux.

AMSU-A will provide sea-ice cover (old/new) and

surface (scalar) wind speed.

• Standard products are distinguished from research

products in that the latter will require post-launch verification.

AIRS

AIRS is designed to meet the NOAA requirement of a

high-resolution infrared (IR) sounder to fly on future

operational weather satellites.

AIRS is a high-resolution sounder covering the spectral range between 0.4 and 15.4 μm, measuring simultaneously in over 2,300 spectral channels. The spectral resolution (λ/∆λ) is 1,200. The high spectral resolution enables the separation of the contribution of unwanted spectral emissions and, in particular, provides spectrally clean

“super windows,” which are ideal for surface observations. All channels will be downlinked on a routine operational basis.

Temperature profiles will be derived in the presence

of multiple cloud layers without requiring any field-ofview to be completely clear. Humidity profiles will be

derived from channels in the 6.3-μm water vapor band

and the 11-μm windows, which are sensitive to the water vapor continuum. Determination of the surface temperature and surface spectral emissivity is essential for

obtaining low-level water vapor distribution.

Land skin surface temperature and the corresponding IR emissivity are determined simultaneously with the

retrieval of the atmospheric temperature and water profiles. Shortwave window channels are used to derive the

surface temperature and corresponding spectral emissivity, and to account for reflected solar radiation. Once the

surface temperature is determined, the longwave surface

emissivity for the 11-μm region can be determined, then

used to retrieve the water distribution near the surface.

Cloud-top heights and effective cloud amount are

determined, based on the calculated atmospheric temperature, humidity, and surface temperature, combined
1999 ESE Reference Handbook EOS Instruments • 95

AIRS Parameters

High spectral resolution, multispectral infrared sounder

 Operates with AMSU for all-weather capability

1 K temperature retrieval accuracy

0.05 emissivity accuracy

Array grating spectrometer (3.74 to 15.4 μm), with a spectral

 resolution of 1,200 (λ/∆λ)

Swath: 1,650 km

Spatial resolution: 13.5 km horizontal at nadir, 1 km vertical

Mass: 156 kg

Duty cycle: 100%

Power: 256 W

Data rate: 1.44 Mbps

Thermal control by: Redundant 60 K Stirling cycle coolers,

 heater, mini thermal bus, two-stage radiator

Thermal operating range: 20-25° C

FOV: ±49.5° cross-track

Instrument IFOV: 1.1° circular

Pointing requirements (platform + instrument, 3 σ):

Control: 360 arcsec

Knowledge: 180 arcsec

Stability: 360/60 sec

Jitter: TBD

Physical size: 139.7 × 77.5 × 76.2 cm (stowed);

139.7 × 151.2 × 76.2 cm (deployed)

with the calculated clear-column radiance and measured

radiance. The spectral dependence of the opacity of the

clouds will distinguish various cloud types (including

cirrus clouds). Ozone retrieval is performed simultaneously with the retrievals of the other parameters using

the 9.6-μm ozone band.

AIRS visible and near-IR channels between 0.4 and

1.0 μm will be used primarily to discriminate between

low-level clouds and different terrain and surface covers, including snow and ice. In addition, the visible channels will allow the determination of cloud, land, and

ocean surface parameters simultaneously with atmospheric corrections. Current implementation calls for four

channels. One broadband channel from 0.4 to 1.0 μm

will be used for the estimation of reflected shortwave

radiation, i.e., albedo. Other channels will be used for

surface properties such as ice and snow amount and vegetation index. Simultaneous observations of the atmosphere and clouds from AIRS will allow characterization of the spectral properties of clouds for enhanced

understanding of their role in modulating the greenhouse

effect, and the increased resolution and number of infrared sounding channels (an increase of two orders of

magnitude beyond current operational sounders) will

improve the accuracy of weather forecasting.

AMSU-A and HSB

AMSU-A is designed primarily to obtain profiles of

stratospheric temperature and to provide a cloud-filtering capability for tropospheric observations. HSB is designed to obtain profiles of atmospheric humidity and to

detect precipitation under clouds with 15-km (nadir) resolution. AMSU-A and HSB have a total of 19 channels:

15 are assigned to AMSU-A, each having a 3.3°

beamwidth, and four are assigned to HSB, each having

a 1.1° beamwidth. Channels 3 to 14 on AMSU-A are

situated on the low-frequency side of the oxygen resonance band (50-60 GHz) and are used for temperature

sounding. Successive channels in this band are situated

at frequencies with increasing opacity, therefore responding to radiation from increasing altitudes. Channel 1 [located on the first (weak) water vapor resonance line] is

used to obtain estimates of total column water vapor in

the atmosphere. Channel 2 (at 31 GHz) is used to indicate the presence of rain.

Channel 15 on AMSU-A, at 89 GHz, is used to indicate precipitation,using the fact that at 89 GHz ice more

strongly scatters radiation than it absorbs or emits. Channels 16 to 19 are located on the wings of the strongly

opaque water vapor resonance line at 183.3 GHz. Successive channels in this group have decreasing opacity

and consequently their data correspond to humidities at

decreasing altitudes. Channels 16 to 19 of HSB, along

with inputs from channels 1 and 2 of AMSU-A, together

with the temperature profile from AIRS/AMSU-A/HSB,

are used to obtain profiles of atmospheric humidity, i.e.,

water vapor.

Team Leader

Moustafa Chahine

Moustafa Chahine was awarded a Ph.D. in Fluid Physics from the University of California at Berkeley in 1960.

He is Chief Scientist at the Jet Propulsion Laboratory

(JPL), where he has been affiliated for 30 years. From

1978 to 1984, he was Manager of the Division of Earth

and Space Sciences at JPL; as such, he was responsible

for establishing the Division and managing the diverse

activities of its 400 researchers.

For 20 years, Dr. Chahine has been directly involved

in remote-sensing theory and experiments. His resume
96 • EOS Instruments 1999 ESE Reference Handbook

Passive microwave radiometer for humidity profiling,

 consisting of four channels: 1 at 150 GHz, 3 at

 183 GHz.

Swath: 1,650 km

Spatial resolution: 13.5 km horizontal at nadir

Mass: 66 kg

Duty cycle: 100%

Power: 85 W (average), 154 W (peak)

Data rate: 4.2 kbps

Thermal control by: Radiator

Thermal operating range: 0-40° C

FOV: ±49.5° cross-track from nadir

 (+90° to -49.5° for calibration)

Instrument IFOV: 1.1°

Pointing requirements (platform + instrument, 3 σ):

Control: 3,600 arcsec

Knowledge: 360 arcsec

Stability: 74 arcsec/sec

Jitter: TBD

Physical size: 73 × 69 × 47 cm

reflects roles as Principal Investigator, designer and developer, and analyst in remote-sensing experiments. He

developed the Physical Relaxation Method for retrieving atmospheric profiles from radiance observations.

Subsequently, he formulated a multispectral approach

using infrared and microwave data for remote sensing

in the presence of clouds. These data analysis techniques

were successfully applied in 1980 to produce the first

global distribution of the Earth surface temperature using data from the HIRS/MSU sounders.

Dr. Chahine was integrally involved in the AMTS

study, which laid the basis for the current AIRS spectrometer. Dr. Chahine served as a member of the NASA

Earth System Sciences Committee (ESSC), which developed the program leading to EOS, and currently is

Chairman of the Science Steering Group of a closely

related effort, the World Meteorological Organization’s

Global Energy and Water Cycle Experiment (GEWEX).

Dr. Chahine is a Fellow of the American Physical Society and the British Meteorological Society. In 1969, he

was awarded the NASA Medal for Exceptional Scientific Achievement and, in 1984, the NASA Outstanding

Leadership Medal.

Science Team Members

Hartmut H. Aumann - Jet Propulsion Laboratory

Alain P. Chedin - Centre National de la Recherche

Scientifique, Paris, France

Catherine Gautier - University of California, Santa

Barbara

Mitch Goldberg - NOAA/National Environmental

Satellite, Data, and Information Service

Eugenia Kalnay - NOAA/National Centers for Environmental Prediction

John F. Le Marshall - Bureau of Meteorology,

Melbourne, Australia

Larry M. McMillin - NOAA/National Environmental

Satellite, Data, and Information Service

Henry E. Revercomb - University of Wisconsin

Rolando Rizzi - University of Bologna, Italy

Philip Rosenkranz - Massachusetts Institute of

Technology

William L. Smith - NASA/Langley Research Center

David H. Staelin - Massachusetts Institute of Technology

L. Larrabee Strow - University of Maryland, Baltimore

Joel Susskind - NASA/Goddard Space Flight Center

AMSU-A Parameters

Passive microwave radiometer that measures atmospheric

 temperature

Swath: 1,650 km

Spatial resolution: 40 km horizontal at nadir

Mass: 100 kg

Duty cycle: 100%

Power: 125 W

Data rate: 3.2 kbps

Thermal control by: Heater, central thermal bus, radiator

Thermal operating range: 0-20° C

FOV: ±49.5°

Instrument IFOV: 3.3°

Pointing requirements (platform + instrument, 3 σ):

Control: 720 arcsec

Knowledge: 360 arcsec

Stability: 360 arcsec/sec

Jitter: 360 arcsec/sec

Physical size: 65.5 × 29.9 × 59.2 cm (A1);

 54.6 × 64.9 × 69.7 cm (A2)

HSB Parameters
1999 ESE Reference Handbook EOS Instruments • 97

References

AIRS Science Team, 1991: The Atmospheric Infrared

Sounder (AIRS) Science and Measurement Requirements, JPL Document #D6665.

Anyamba, E., and J. Susskind, 1998: Comparison of

TOVS, Bouys, COADS, NCEP, and ECMWF Surface

Temperatures. J. Geophys. Res., 103, 10,489-10,511.

Aumann, H.H., and R.J. Pagano, 1994: Atmospheric Infrared Sounder on the Earth Observing System. Optical

Engineering, 33, No. 3, 776-784.

Crone, L.J., L.M. McMillin, and D.S. Crosby, 1996:

Constrained Regression in Satellite Meteorology. J. Appl.

Meteor., 35, 2023-2035.

Goldberg, M.D., and L.M. McMillin, 1999: Methodology for deriving deep-layer temperatures from combined

satellite infrared and microwave observations. J. Climate,

12, 5-20.

Susskind, J., C. Barnet, and J. Blaisdell, 1998: Determination of Atmospheric and Surface Parameters from

Simulated AIRS/AMSU/HSB Sounding Data: Retrieval

and Cloud Clearing Methodology. Adv. Space Res., 21,

369-384.

Rosenkranz, P.W., 1998: Water vapor microwave continuum absorption: A comparison of measurements and

models. Radio Science, 33, 919-928.

AIRS/AMSU-A/HSB Data Products

Product Name

Level-1B Radiance (AIRS)

Cloud Product

(AIRS/AMSU-A/HSB)

Humidity Product

(AIRS/HSB)

Temperature Product

(AIRS/AMSU-A)

Level-1B Radiance

(AMSU-A)

Level-1B Radiance

(HSB)

Accuracy

Absolute :: Relative

3% (190-330 K) ::

0.2 K NEdT at 250 K

TBD

20% Precipitable H2O :: N/A

Absolute 1 K :: N/A

1.5 K :: 0.5 K

1 K :: 0.6 K

Temporal

Resolution

2/day (d,n)

2/day (d,n)

2/day (d,n)

2/day (d,n)

2/day (d,n)

2/day (d,n)

Horizontal

Resolution :: Coverage

15 km :: Global

50 km :: Global

50 km :: Global

50 km :: Land, Ocean

40 km :: Global

15 km :: Global

Vertical

Resolution :: Coverage

N/A :: N/A

N/A :: Cloud

2 km :: Surface to 100 mb

1 km :: Surface to 100 mb

N/A :: N/A

N/A :: N/A

Rosenkranz, P.W., 1998: Improved rapid transmittance

algorithm for microwave sounding channels. Proc. International Geoscience and Remote Sensing Symposium

(IGARSS), Seattle, Washington, pp.728-730.

McMillin, L.M., L.J. Crone, M.D. Goldberg, and T.J.

Kleespies, 1995: Atmospheric transmittance of an absorbing gas. 4. OPTRAN: a computationally fast and accurate transmittance model for absorbing gases with fixed

and variable mixing ratios at variable viewing angles.

Applied Optics, 34, 6269-6274.

Strow, L.L., H.E. Motteler, R.G. Benson, S.E. Hannon,

and S. De Souza-Machado, 1998: Fast Computation of

Monochromatic Infrared Atmospheric Transmittances

using Compressed Look-Up Tables. J. Quantitative Spectroscopy and Radiative Transfer, 59, 481-493.

Strow, L.L., D.C. Tobin, W.W. McMillan, S.E. Hannon,

W.L. Smith, H.E. Revercomb, and R. Knuteson, 1998:

Impact of a New Water Vapor Continuum and Line Shape

Model on Observed High Resolution Infrared Radiances.

J. Quantitative Spectroscopy and Radiative Transfer, 59,

303-317.

McMillan, W.W., L.L. Strow, W.L. Smith, H.E.

Revercomb, H.L. Huang, A.M. Thompson, D.P.

McNamara, and W.F. Ryan, 1997: Remote Sensing of

Carbon Monoxide Over the Continental United States

on September 12-13, 1993. J. Geophys. Res., 102,

10,695-10,709.
98 • EOS Instruments 1999 ESE Reference Handbook

The EOS PM AMSR-E will measure geophysical parameters supporting several global change science and monitoring efforts. Of

particular importance to its success is an external calibration design, which has proved suitable in other satellite microwave instrumentation for long-term monitoring of subtle changes in temperature and other variables.

Precipitation and evaporation have extremely important roles,

through provision of water to the biosphere via precipitation and

as an air conditioning agent that removes excess heat from the

surface (via evaporation), thereby contributing toward making

Earth habitable. AMSR-E will measure rain rates over both land

and ocean. Over the ocean, the AMSR-E microwave frequencies

can probe through smaller cloud particles to measure the microwave emission from the larger raindrops. The AMSR-E will provide sensitivity to oceanic rain rates as high as 50 mm/hr (about 2

inches per hour). Over land, AMSR-E can measure the scattering

effects of large ice particles, which later melt to form raindrops.

These measurements, though less direct a measure of rainfall intensity, are converted to rain rates with the help of cloud models.

Over the ocean, in addition to rain rates, AMSR-E will provide sea surface temperatures (SST) through most types of cloud

cover, supplementing infrared-based measurements of SST that

are restricted to cloud-free areas. SST fluctuations are known to

have a profound impact on weather patterns across the globe, and

AMSR-E’s all-weather capability could provide a significant improvement in our ability to monitor SSTs and the processes controlling them.

The total integrated water vapor of the atmosphere will also

be measured over the ocean. This variable is important for the

understanding of how water is cycled through the atmosphere.

Since water vapor is the Earth’s primary greenhouse gas, and it

contributes the most to future projections of global warming, it is

critical to understand how it varies naturally in the Earth system.

Measurements by AMSR-E of ocean surface roughness can

be converted into near-surface wind speeds. These winds are an

important determinant of how much water is evaporated from the

surface of the ocean. Thus, the winds help to maintain the water

vapor content of the atmosphere while precipitation continually

removes it.

AMSR-E cloud-water estimates over the ocean will help studies of whether clouds, with their ability to reflect sunlight, increase or decrease under various conditions. This could be an

important feedback mechanism that either enhances or mitigates

global warming, depending on whether clouds increase or decrease

with warming.

Monitoring of sea-ice parameters, such as ice concentration,

type, and extent, is necessary to understand how this frozen blanket over the ocean affects the larger climate system. Sea ice has

the ability to insulate the water against heat loss to the frigid atKey AMSR-E Facts

Selected for flight on EOS PM

Heritage: SMMR (Nimbus-7 and Seasat), SSM/I

 (DMSP), AMSR (ADEOS II)

Measures precipitation rate, cloud water, water vapor,

 sea surface winds, sea surface temperature, ice,

 snow, and soil moisture

Passive microwave radiometer, twelve channels, six

 frequencies, dual polarization

All-weather measurements of geophysical parameters

 supporting several global change science and

 monitoring efforts

Responsible Agency: National Space Development

 Agency of Japan (NASDA)

AMSR-EAdvanced Microwave Scanning Radiometer

http://wwwghcc.msfc.nasa.gov/AMSR/

AMSR-E URL
1999 ESE Reference Handbook EOS Instruments • 99

mosphere above it, and at the same time the ability to

reflect sunlight that would otherwise warm the ocean.

AMSR-E measurements will allow the derivation of seaice concentrations in both polar regions, through taking

advantage of the marked contrast in microwave emissions of sea ice and liquid water.

In much the same way as AMSR-E can see large ice

particles in the upper reaches of rain systems, it also

measures the scattering effects of snow-cover depth.

These measurements are empirically related to snowcover depth and water content based upon field measurements. Like sea ice, snow cover has a large influence on

how much sunlight is reflected from the Earth. It also

acts as a blanket, keeping heat from escaping from the

underlying soil and allowing deep cold air masses to develop during the winter. It further provides an important

storage mechanism for water during the winter months,

which then affects how much surface wetness is available for vegetation and crops in the spring. AMSR-E

monitoring of snow cover will allow studies and monitoring of how snow-cover variations interplay with other

climate fluctuations.

Wet soil can be identified in the AMSR-E observations if not too much vegetation is present. AMSR-E will

provide the most useful satellite data yet for determination of how well low-frequency (6.9 GHz) microwave

observations can be used to monitor surface wetness.

Surface wetness is important for maintaining crop and

vegetation health, and its monitoring on a global basis

would allow drought-prone areas to be checked for signs

of drought.

Science Team Leaders

Roy W. Spencer

Dr. Spencer received his B.S. in Atmospheric Sciences

from the University of Michigan in 1978 and his M.S.

and Ph.D. in Meteorology from the University of Wisconsin in 1980 and 1982. He then continued at the U. of

Wisconsin through 1984 in the Space Science and Engineering Center as a research scientist. In his current position at NASA Marshall Space Flight Center (MSFC)

Dr. Spencer serves as Principal Investigator on the Global Precipitation Studies with Nimbus-7 and DMSP

SSM/I, and the Advanced Microwave Precipitation Radiometer High Altitude Studies of Precipitation Systems.

He has been a member of several science teams: the Tropical Rainfall Measuring Mission (TRMM) Space Station

Accommodations Analysis Study Team, Science Steering Group for TRMM, TOVS Pathfinder Working Group,

and NASA HQ Earth Science and Applications Advisory

Subcommittee.

Since 1992 Dr. Spencer has been the U.S. Team

Leader for the Multichannel Imaging Microwave RadiAMSR-E Parameters

External cold load reflector and a warm load for calibration

Offset parabolic reflector, 1.6 m in diameter, and rotating

drum at 40 rpm

Multiple feedhorns (6) to cover six bands from 6.9 to 89GHz

with 0.3 to 1.1 K radiometric sensitivity; vertical and

horizontal polarization

Accuracy: 1 K or better

Swath: 1445 km

Spatial resolution: 6 × 4 km (89.0 GHz), 14 × 8 km (36.5

GHz), 32 × 18 km (23.8 GHz), 27 × 16 km (18.7 GHz),

51 × 29 km (10.65 GHz), 75 × 43 km (6.925 GHz)

Incidence angle: 55 degrees

Sampling interval: 10 km for 6-36 GHz channels, 5 km

 for the 89 GHz channel

Mass: 324±15 kg

Duty cycle: 100 %

Power: 350±35 W

Data rate: 87.4 kbps avg, 125 kbps peak

Thermal control by: Passive radiator, thermostatically

 controlled heaters

Thermal operating range: -5 to 40 ̊C

FOV: Forward-looking conical scan

Pointing requirements, design value (instrument only, 3 σ):

Accuracy: 600 arcsec/axis for roll and pitch;

NA for yaw

Stability: 80 arcsec/sec/axis for roll and pitch;

NA for yaw

Knowledge: 300 arcsec/axis for roll and pitch;

NA for yaw

Physical size:

Sensor Unit: 1.95 × 1.5 × 2.2 m (stowed);

1.95 × 1.7 × 2.4 m (deployed)

Control Unit: 0.8 × 1.0 × 0.6 m

ometer (MIMR) team and the follow-on AMSR-E team.

In 1994 he became the AMSR-E Science Team leader.

He received the NASA Exceptional Scientific

Achievement Medal in 1991, the MSFC Center

Director’s Commendation in 1989, and the American Meteorological Society’s Special Award in 1996.

Akira Shibata

Dr. Akira Shibata, co-leader of the Joint AMSR Science

Team, received his B.S., M.S. and Ph.D. from Waseda

University, in the Science and Engineering Department.
100 • EOS Instruments 1999 ESE Reference Handbook

Before moving to the Meteorological Research Institute

(MRI) in 1983, he was a technical officer at the Nagasaki

Marine Observatory. At MRI he worked as a research scientist. In 1996, Dr Shibata moved to the Earth Observation Research Center as an Associate senior scientist. He

also serves as the ADEOS II AMSR Science Team leader.

Co-Investigators

Robert Adler - NASA/Goddard Space Flight Center

Donald J. Cavalieri - NASA/Goddard Space Flight Center

Alfred T.C. Chang - NASA/Goddard Space Flight Center

Josefino Comiso - NASA/Goddard Space Flight Center

Ralph Ferraro - NOAA/National Environmental Satellite,

Data, and Information Service

Christian Kummerow - NASA/Goddard Space Flight Center

Eni G. Njoku - Jet Propulsion Laboratory

Frank Wentz - Remote Sensing Systems

Thomas Wilheit - Texas A&M University

References

Cavalieri, D.J., P. Gloersen, C.L. Parkinson, J.C. Comiso,

and H.J. Zwally, 1997: Observed hemispheric asymmetry in global sea ice changes. Science, 272, 1104-1106.

Chang, A.T.C., J.L. Foster, and D.K. Hall, 1997: Effects

of forest on the snow parameters derived from microwave measurements during the BOREAS winter field

campaign. Hydrological Processes, 10, 1565-1574.

Chang, A.T.C., J.L. Foster, D.K. Hall, B.E. Goodison,

A.E. Walker, J.R. Metcalfe, and A. Harby, 1997: Snow

parameters derived from microwave measurements during the BOREAS winter field campaign. J. Geophys. Res.,

102, 29,663-29,671.

Ferraro, R.R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res.,

102, 16,715-16,735.

Hong, Y., C. Kummerow, and W.S. Olson, 1998: Separation of convective/stratiform precipitation using microwave brightness temperature. J. Appl. Meteorol., submitted.

Kummerow, C., 1998: Beamfilling errors in passive microwave rainfall retrievals. J. Appl. Meteorol., 37, 356-

370.

Markus, T., and D.J. Cavalieri, 1998: Snow depth distribution over sea ice in the southern ocean from satellite

passive microwave data, in Antarctic sea ice: Physical

processes, interactions and variability. Antarctic Research

Series, 74, 19-39, American Geophysical Union, Washington, DC, 1998.

Njoku, E., and L. Li, 1998: Retrieval of land surface parameters using passive microwave measurements at 6 to

18 GHz. IEEE Trans. Geosci. Remote Sens., in press.

Njoku, E.G., and D. Entekhabi, 1996: Passive microwave

remote sensing of soil moisture. J. Hydrology, 184, 101-

129.

Olson, W., C.D. Kummerow, and Y. Hong, 1998: Atmospheric latent heating distributions in the tropics derived

from satellite passive microwave radiometer measurements. J. Appl. Meteorol., submitted.

Roberti, L., and C. Kummerow, 1998: Monte Carlo calculations of polarized microwave radiation emerging

from cloud structures. J. Geophys. Res., submitted.

Wang, Y., J.C. Alishouse, R.R. Ferraro, and R. Song,

1998: Estimation of midlatitude rainfall parameters from

satellite microwave radiometers using the area-time integral concept. Radio Science, in press.

Wentz, F.J., and R.W. Spencer, 1998: SSM/I rain retrievals within an unified all-weather ocean algorithm. J.

Atmos. Sci., 55, 1613.

Wentz, F. J., 1998: A well-calibrated ocean algorithm for

SSM/I. J. Geophys. Res., 102, 8703.
1999 ESE Reference Handbook EOS Instruments • 101

AMSR-E Level 2 Data Products

Product Name

Brightness

Temperature

Rainfall:

Over Land

Over Ocean

Ocean Cloud Water

Ocean Water Vapor

Ocean Surface Wind Speed

Sea Surface Temperature

Sea Ice:

Concentration

Sea Ice:

Temperature

Snow Depth on Ice

Land Surface

Soil Moisture

Snow Water

Equivalent

Accuracy

Absolute :: Relative

0.2 - 0.7 K ::

2 mm/hr or 20%

1 mm/hr or 20%

0.02 mm ::

0.6 mm ::

0.9 m/s ::

≤ 0.5 K ::

≤ 5% ::

≤ 4K ::

≤ 5 cm ::

0.06g/cm3 ::

10 mm or 20% ::

Horizontal

Resolution :: Coverage

5-61 km :: Global

12 km :: Global

12 km :: Global

24 km :: Ocean

24 km :: Ocean

24 km :: Ocean

61 km :: Ocean

24 km :: Ocean

Ocean/Cryosphere

24 km :: Ocean/Cryosphere

24 km :: Ocean/Cryosphere

61 km (EASE grid)

24 km (EASE grid)

Vertical

Resolution :: Coverage

N/A ::

N/A :: Surface

N/A :: Surface

N/A :: Troposphere

Column :: Troposphere

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

Total integrated water vapor over the global oceans as retrieved from DMSP Special Sensor Microwave/Imager (SSM/I) data

during January 1998.
102 • EOS Instruments 1999 ESE Reference Handbook

ASTER is a facility instrument provided for the Terra platform by

the Japanese Ministry of International Trade and Industry (MITI).

It will provide high-spatial-resolution (15- to 90-m) multispectral

images of the Earth’s surface and clouds in order to better understand the physical processes that affect climate change. While the

Moderate-Resolution Imaging Spectroradiometer (MODIS) and

Multi-Angle Imaging Spectro-Radiometer (MISR) will monitor

many of the same variables globally and on a daily basis, ASTER

will provide data at a scale that can be directly related to detailed

physical processes. These data will bridge the gap between field

observations and data acquired by MODIS and MISR, and between process models and climate and/or forecast models. ASTER data will also be used for long-term monitoring of local and

regional changes on the Earth’s surface, which either lead to, or

are in response to, global climate change, e.g., land use, deforestation, desertification, lake and playa water-level changes, and

other changes in vegetation communities, glacial movement, and

volcanic processes.

Clouds are one of the most important variables in the global

climate system. With its high spatial resolution, broad spectral

coverage, and stereo capability, ASTER will provide essential measurements of cloud amount, type, spatial distribution, morphology, and radiative properties.

ASTER will provide radiative (brightness) temperature, and

the multispectral thermal infrared (TIR) data can be used to derive surface kinetic temperature and spectral emissivity. Radiative temperature is an element in the surface heat balance. Surface kinetic temperature can be used to determine elements of

surface process models, sensible heat flux, latent heat flux, and

ground heat conduction. Surface temperatures are also related to

thermophysical properties (such as thermal inertia), vegetation

health, soil moisture, temporal land classification, e.g., wet vs.

dry, vegetated vs. bare soil, and evapotranspiration.

ASTER will operate in three visible and near-infrared (VNIR)

channels between 0.5 and 0.9 μm, with 15-m resolution; six shortwave infrared (SWIR) channels between 1.6 and 2.43 μm, with

30-m resolution; and five TIR channels between 8 and 12 μm,

with 90-m resolution. The instrument will acquire data over a 60-

km swath whose center is pointable cross-track ±8.55° in the SWIR

and TIR, with the VNIR pointable out to ±24°. An additional VNIR

telescope (aft pointing) covers the wavelength range of Channel

3. By combining these data with those for Channel 3, stereo views

can be created, with a base-to-height ratio of 0.6. ASTER’s pointing capabilities will be such that any point on the globe will be

accessible at least once every 16 days in all 14 bands and once

every 5 days in the three VNIR channels.

SWIR

TIR

VNIR

Key ASTER Facts

Selected for flight on Terra

Heritage: JERS-1 OPS and Landsat

Imaging radiometer

Provides high-resolution images of the land

surface, water, ice, and clouds

Same-orbit stereo capability

14 multispectral bands from visible through

thermal infrared

Not scheduled for further flights other than Terra

Japan (MITI) to provide the instrument

Prime Contractor: NEC (systems integration,

VNIR, and Common Signal Processor)

Subcontractors: MELCO (SWIR and cryocooler),

Fujitsu (TIR and cryocooler), and Hitachi

(master power supply)

ASTERAdvanced Spaceborne Thermal Emission and

Reflection Radiometer

http://asterweb.jpl.nasa.gov

ASTER URL
1999 ESE Reference Handbook EOS Instruments • 103

ASTER data products will exploit combinations of

VNIR, SWIR, and TIR for cloud studies, surface mapping, soil and geologic studies, volcano monitoring, and

surface temperature, emissivity, and reflectivity determination. VNIR and SWIR bands will be used for investigation of land-use patterns and vegetation, VNIR

and TIR combinations for the study of coral reefs and

glaciers, and VNIR for digital elevation models (DEMs).

TIR channels will be used for study of evapotranspiration and land and ocean temperature. The stereoscopic

capability will yield local surface DEMs and allow observations of local topography, cloud structure, volcanic

plumes, and glacial changes.

Team Leaders

Hiroji Tsu

Anne B. Kahle

Hiroji Tsu, the ASTER Science Team Leader, received

B.S., M.S., and Ph.D. degrees from the University of

Tokyo. He joined the Geological Survey of Japan (GSJ)

as a researcher of Geophysics in1970. He moved on to

the Earth Remote Sensing Data Analysis Center

(ERSDAC) in1993, and was general manager of the R&D

Department. In 1996 he returned to GSJ as Deputy Director General.

Anne Kahle, the U.S. Science Team Leader, received

her B.S. and M.S. in Geophysics from the University of

Alaska and her Ph.D. from UCLA in Meteorology. She

worked at the RAND Corp. from 1962 as a Senior Physical Scientist and joined JPL in 1974, where she is a Senior Research Scientist.

Science Team Members

Kohei Arai - Saga University, Japan

Yoshio Awaya - Forestry and Forest Products Research

Francois Becker - Pare D'Innovation

Philip Christensen - Arizona State University

Teruya Ezaka - JAPEX Geoscience Institute, Inc.

Hiroyuki Fujisada - Electrotechnical Laboratory,

Japan

Keiichi Fukui - Meteorological Research

Kiyonari Fukue - Tokai University, Japan

Yoshikazu Fukushima - Geographical Survey Institute

Andy Gabell - CSIRO, Australia

Alan Gillespie - University of Washington

Ikahiro Hayashil - Earth Remote Sensing Data Analysis Center

Yoshiaki Honda - Chiba University

Simon Hook - Jet Propulsion Laboratory

Jonathan Huntington - CSIRO, Australia

Yoshinori Ishii - National Institute for Environmental

Studies

Takashi Ishiyama - Chiba University

Akira Iwasaki - Electrotechnical Laboratory

Motoharu Jinguuji - National Institute for Resources

and Environment

Manabu Kaku - Mitsubishi Materials Natural Resources Development Corp.

Hajime Kayanne - University of Tokyo

Hugh Kieffer - U.S. Geological Survey

Masakuni Kikuchi - Japan Resources Observation

System Organization

Motoaki Kishino - Institute of Physical and Chemical

Research, Japan

Kazuhiko Masuda - Meteorological Research Institute

Shoichi Masuda - Fujitsu Ltd.

Tsuneo Matsunaga - Tokyo Institute of Technology

Tadakuni Miyazaki - Yamanashi Institute of Environmental Sciences, Japan

Yoshinori Miyazaki - Geological Survey of Japan

Masao Moriyama - Nagasaki University

Hiroshi Murakami - Geographical Survey Institute

Takatoshi Namikawa - Japan Petroleum Exploration

Co., Ltd

Yoshiki Ninomiya - Geological Survey of Japan

Akira Ono - National Research Laboratory of Metrology

Hiromi Ono - Japan Resources Observation System

Organization

Takashi Ooka - Metal Mining Agency of Japan

Frank Palluconi - Jet Propulsion Laboratory

David Pieri - Jet Propulsion Laboratory

Shuichi Rokugawa - Tokyo University, Japan

Lawrence Rowan - U.S. Geological Survey

Genya Saito - National Institute of Agro-Environmental

Sciences
104 • EOS Instruments 1999 ESE Reference Handbook

Multispectral imager for reflected and emitted radiation

 measurements of the Earth’s surface

4% absolute radiometric accuracy in VNIR and SWIR bands

Absolute temperature accuracy is 3 K in 200-240 K range, 2 K

 in 240-270 K range, 1 K in 270-340 K range, and 2 K in

 340-370 K range for TIR bands

Swath: 60 km at nadir, swath center is pointable cross-track

 ±106 km for SWIR and TIR, and ±314 km for VNIR

Spatial resolution: VNIR (0.5-0.9 μm), 15 m [stereo (0.7-

 0.9 μm), 15 m horizontal, 25 m vertical]; SWIR (1.6-

 2.43 μm), 30 m; TIR (8-12 μm), 90 m

Mass: 421 kg

Duty cycle: 8% (VNIR and SWIR, daylight only), 16% (TIR)

Power: 463 W (average), 646 W (peak)

Data rate: 8.3 Mbps (average), 89.2 Mbps (peak)

Thermal control by: 80 K Stirling cycle coolers, heaters,

 cold plate/capillary pumped loop, and radiators

ASTER Parameters

Thermal operating range: 10-28° C

FOV (all pointing is near nadir, except VNIR both nadir and

27.6° backward from nadir): VNIR = 6.09° (nadir),

 5.19° (backward), SWIR = TIR = 4.9°

Instrument IFOV: VNIR = 21.5 μrad (nadir), 18.6 μrad

 (backward), SWIR = 42.6 μrad (nadir), TIR = 128 μrad

 (nadir)

Pointing requirements (platform+instrument, 3 σ):

Control: 1 km on ground (all axes)

Knowledge: 342 m on ground (per axes)

Stability: 2 pixels per 60 sec (roll = 8.8,

pitch = 8.8, yaw = 15 arcsec)

Jitter: 1-2 pixel per 9 sec (roll = 8.8, pitch=4.4,

yaw = 52 arcsec)

(Requirements vary with telescope)

Physical size: VNIR = 57.9 × 65.1 × 83.2 cm,

SWIR = 72.3 × 134 × 90.6 cm,

TIR = 73 × 183 × 110 cm,

CSP/VEL (electronics) = 33.4 × 54 × 31.5 cm,

MPS (electronics) = 30 × 50 × 32 cm

Shinichi Sakai - Central Research Institute of Electric

Power Industry

Fumihiro Sakuma - National Research Laboratory of

Metrology

Isao Sato - Geological Survey of Japan

Thomas Schmugge - USDA/Hydrology Laboratory

Ryouhei Tada - Teikoku Oil Co., Ltd

Tsutomu Takashima - Meteorological Research

Institute, Japan

Yozo Takayama - Meteorological Research Institute

Masayuki Tamura - National Institute for Environmental Studies

Kurt Thome - University of Arizona

Hideyuki Tonooka - Ibaraki University

Hiroji Tsu - Shikoku National Industrial Research

Institute

Satoshi Tuchida - Geological Survey of Japan

Minoru Urai - Geological Survey of Japan

Hiroshi Watanabe - ERS Data Analysis Center

Takahiro Watanabe - Japan National Oil

Ronald Welch - University of Alabama

Yasushi Yamaguchi - University of Nagoya, Japan

Tadashi Yamakawa - Mitsubishi Materials Natural

Resources Development Corp.

Yoshifumi Yasuoka - National Institute for Environmental Studies, Japan

References

Fujisada, H., and A. Ono, 1991: Overview of ASTER

Design Concept, Future European and Japanese RemoteSensing Sensors and Programs. Proceedings of the SPIE

- The International Society for Optical Engineering, 1-2

April 1991, Orlando, Florida, Vol. 1490, P. Slater, Ed.,

Society of Photo-Optical Instrumentation Engineers,

Bellingham, Washington, 244-254.

Fujisada, H., and A. Ono, 1992: Observational performance of ASTER instrument on EOS AM-1 spacecraft.

Advances in Remote Sensing of Earth’s Surface and Atmosphere, A.B. Kahle, E.J. Njoku, F.D. Palluconi, A.R.

Gillespie, S.J. Hook, C.M. Hayden, K. Tsuchiya and J.

Dozier, Eds., Pergamon Press, New York, 147-150.
1999 ESE Reference Handbook EOS Instruments • 105

ASTER Data Products

Product Name

Reconstructed,

Unprocessed

Instrument Data

Registered Radiance at

Sensor

Decorrelation Stretch

Brightness Temperature

Surface Reflectance

Surface Radiance

Surface Emissivity

Surface Kinetic Temperature

Digital Elevation Model

2-4% :: 1

N/A :: N/A

1-2 K :: 0.3 K

4% :: 1%

2% :: 1%

0,05-0.1 :: 0.005

1-4 K :: 1%

7 m (w/GCPs) ::

10 m (no GCPs)

Accuracy

 Absolute :: Relative

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

1/(16 day)

Temporal

 Resolution

Horizontal

Resolution :: Coverage

15, 30, 90 m :: Global

15, 30, 90 m :: Global

15, 30 ,90 m :: Land/Regional, Global

90 m :: Global

15, 30 m :: Land/Regional, Global

15, 30, 90 m :: Land/Regional, Global

90 m :: Local

90 m :: Local

30 :: Land/Regional, Global

Vertical

Resolution :: Coverage

N/A :: of Sensor

N/A :: of Sensor

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

1 m :: Surface
106 • EOS Instruments 1999 ESE Reference Handbook

Key CERES Facts

Selected for flight on TRMM, Terra, and EOS PM

Heritage: ERBE

Two broadband, scanning radiometers: One

cross-track mode, one rotating plane (biaxial scanning)

Measures Earth’s radiation budget and atmospheric radiation from the top of the

atmosphere to the surface

First instrument (cross-track scanning) will

essentially continue the ERBE mission and

the second (biaxially scanning) will provide

angular radiance information that will

improve accuracy of angular models used to

derive the Earth’s radiative balance

Single scanner on TRMM mission (launched

November 1997)

Dual scanners on Terra (1999), EOS PM-1

(2000), and single thereafter

Prime Contractor: TRW

Responsible Center: NASA/Langley Research

Center

The instruments of the CERES investigation will provide EOS

with accurate cloud and radiation flux measurements that are fundamental inputs to models of oceanic and atmospheric energetics,

and will also contribute to extended-range weather forecasting.

These data have been requested for international programs of the

World Climate Research Program (WCRP), including the Tropical Ocean Global Atmosphere (TOGA) campaign, World Ocean

Circulation Experiment (WOCE), Global Energy and Water Cycle

Experiment (GEWEX), and the Indian Ocean Experiment

(INDOE). Understanding the role of clouds and radiation in the

climate system is one of the highest priorities of the U.S. Global

Change Research Program.

Clouds are generally regarded as the largest source of uncertainty in understanding climate. Not only are clouds highly variable and difficult to measure, but they have competing heating

and cooling effects on the Earth-atmosphere system. Clouds cool

the Earth by modulating the large flow of incoming radiative energy from the Sun through the atmosphere, and warm the planet

by enhancing the atmospheric greenhouse effect. CERES will

measure the radiative flows at the top of the atmosphere (TOA),

and will combine these data with that from higher resolution imagers (VIRS on TRMM, MODIS on Terra/EOS PM) to produce

cloud properties and radiative fluxes through the atmosphere as

well as the radiative energy budget at the Earth’s surface. The

imagers allow determination of cloud top height, fractional area,

cloud liquid water path, droplet size, and other cloud properties

that are consistent with the radiative fluxes. CERES will provide,

for the first time, a critical tie between the measurements of the

radiation budget and synchronous measurements of cloud properties.

The CERES instruments use a scanner very similar to the

Earth Radiation Budget Experiment (ERBE) scanner to determine

top-of-atmosphere fluxes. Key developments in meeting the

CERES goal to double the accuracy of existing estimates of radiative fluxes include new models of the anisotropy of the Earth’s

reflected and emitted radiation (using the CERES bi-axial scanner) as well as improved time-sampling methodologies.

CERES will also provide improved measurements of clearsky radiative fluxes. Improvements in clear-sky fluxes require nearsimultaneous measurements of both well-calibrated cloud-imager

and broadband radiation measurements. Highly accurate clear-sky

radiative fluxes are critical in assessing the land/ocean heat budget, as well as understanding the role of clouds in the climate system.

Finally, CERES produces Level 3 data products derived by

time interpolation and integration of the Level 2 data into monthly

averages. The time interpolation process will be aided by data

from geostationary imagers. Thus, CERES will determine the

structure of the atmospheric energy budget over the life of its mission with a time resolution of three hours in its synoptic data product. For long-term climate understanding, CERES also produces

CERESClouds and the Earth’s Radiant Energy System

EOS Data Products Handbook (CERES data product descriptions):

http://eos.nasa.gov/eos_homepage/misc_html/

data_prod.html

CERES Algorithm Theoretical Basis Documents (ATBDs):

http://eos.nasa.gov/atbd/cerestables.html

CERES Validation Plan:

http://eos.nasa.gov/validation/valplans.html

CERES URLs
1999 ESE Reference Handbook EOS Instruments • 107

data products that contain monthly averages of the cloud

and radiation fields on a uniform spatial grid.

Principal Investigator

Bruce Barkstrom

Bruce Barkstrom received a B.S. in Physics from the

University of Illinois. He received an M.S. and Ph.D. in

Astronomy from Northwestern University. Following a

position as Research Associate with the National Center

for Atmospheric Research, he had a 5-year teaching assignment with George Washington University.

In 1979, Dr. Barkstrom joined the NASA Langley

Research Center. He served as the ERBE Experiment Scientist and Science Team Leader. As such, he was directly

responsible for the ERBE instrument design and calibration, as well as the ERBE data interpretation. He was

also responsible for science project management of the

ERBE team of 17 Principal and 40 Co-Investigators.

Dr. Barkstrom has received NASA medals for Exceptional Scientific Achievement (1989) and Exceptional

Achievement (1998).

Co-Investigators

Bryan A. Baum - NASA/Langley Research Center

Donald R. Cahoon, Jr. - NASA/Langley Research

Center

Robert D. Cess - State University of New York, Stony

Brook

Lin H. Chambers - NASA/Langley Research Center

Thomas P. Charlock - NASA/Langley Research Center

James A. Coakley - Oregon State University

Dominique Crommelynck - Royal Meteorological

Institute, Belgium

Leo J. Donner - NOAA/Geophysical Fluid Dynamics

Laboratory

Richard N. Green - NASA/Langley Research Center

Robert S. Kandel - Ecole Polytechnique, France

Michael D. King - NASA/Goddard Space Flight Center

David P. Kratz - NASA/Langley Research Center

Robert B. Lee III - NASA/Langley Research Center

Norman G. Loeb - Hampton University

Alvin J. Miller - NOAA/National Centers for Environmental Prediction

Patrick Minnis - NASA/Langley Research Center

Kory J. Priestly - NASA/Langley Research Center

Veerabhadran Ramanathan - Scripps Institution of

Oceanography

David A. Randall - Colorado State University

G. Louis Smith - Virginia Polytechnic Institute and

State University

Larry L. Stowe - NOAA/National Environmental

Satellite, Data, and Information Service

Ronald M. Welch - University of Alabama/Huntsville

Bruce A. Wielicki - NASA/Langley Research Center

Takmeng Wong - NASA/Langley Research Center

David F. Young - NASA/Langley Research Center

References

Barkstrom, B.R., (Ed.),1990: Long-Term Monitoring of

the Earth’s Radiation Budget, 17-18 April 1990, Orlando,

Florida—Proceedings of the SPIE - The International Society for Optical Engineering, Vol. 1299. Society of

Photo-Optical Instrumentation Engineers, Bellingham,

Washington, 265 pp.

Lee, R.B., III, B.R. Barkstrom, H.C. Bitting, D.A.H.

Crommelynck, J. Paden, D.K. Pandey, K.J. Priestley, G.L.

Smith, S. Thomas, K.L. Thornhill, and R.S. Wilson, 1998:

CERES Parameters

Three channels in each radiometer: Total radiance (0.3 to

 >100 μm); Shortwave (0.3 to 5 μm); Window (8 to 12 μm)

Swath: Limb to limb

Spatial resolution: 20 km at nadir

Mass: 50 kg per scanner

Duty cycle: 100%

Power: 47 W (average), 104 W (peak: biaxial mode) per

 scanner

Data rate: 10 kbps per scanner

Thermal control by: Heaters, radiators

Thermal operating range: 37-39° C (detectors)

FOV: ±78° cross-track, 360° azimuth

Instrument IFOV: 14 mrad

Pointing requirements (platform+instrument, 3 σ):

Control: 720 arcsec

Knowledge: 180 arcsec

Stability: 79 arcsec/6.6 sec

Physical size: 60 × 60 × 57.6 cm/unit (stowed),

60 × 60 × 70 cm/unit (deployed)
108 • EOS Instruments 1999 ESE Reference Handbook

Instrument Investigation - CERES

CERES Data Products

Product Name

Instantaneous Instrument Scans (BDS)

Instantaneous Top of Atmosphere Fluxes

(ES8)

Regionally Averaged Top of Atmosphere

Fluxes (ES9)*

Regionally and Monthly Averaged Top of

Atmosphere Fluxes (ES4)*

Monthly and Regionally Averaged Top of

Atmosphere Fluxes (ES4G)*

Single Satellite Footprint Top of Atmosphere

and Surface Fluxes and Clouds (SSF)

CERES Radiative Fluxes and Clouds (CRS)

Hourly Gridded Fluxes and Clouds (FSW)

Synoptic Gridded Fluxes and Clouds

(SYN)**

Monthly and regional Fluxes and Clouds to

Surface (AVG)**

Zonal Monthly regional Fluxes and Surface

to Clouds (ZAVG)**

Surface Radiation Budget (SRB)**

Monthly Top of Atmosphere and Surface

Radiation Budget Averages (SRBAVG)**

1-2% :: 0.005

15 W/m2

 LW;

40 W/m2 SW

15 W/m2

 LW;

40 W/m2 SW

3 W/m2 LW;

5 W/m2 SW

3 W/m2 LW;

5 W/m2 SW

5 W/m2 LW;

15 W/m2 SW;

depends on cloud parameters

Depends on cloud or flux parameters

Depends on cloud or flux parameters

Depends on cloud or flux parameters

2 W/m2 LW;

3 W/m2 SW;

variable for clouds and other fluxes

1 W/m2 LW;

2 W/m2 SW;

variable for clouds and other fluxes

Depends on cloud or flux parameters

Depends on cloud or flux parameters

Accuracy

Absolute :: Relative

N/A :: 1 hr

N/A :: 1 hr

N/A :: 1 hr

N/A :: 1 month

N/A :: 1 month

N/A :: 1 hr

N/A :: 1 hr

N/A :: 1 hr

3 hr :: N/A

1 hr :: 1 month

N/A :: 1 month

N/A :: 1 hr

N/A :: 1 month

Temporal

 Resolution :: Coverage

Horizontal

Resolution :: Coverage

20 km :: Global

20 km :: Global

2.5 × 2.5 deg

Region :: Global

2.5 × 2.5 deg

Region :: Global

2.5 × 2.5 deg

Region :: Global

20 km :: Global

20 km :: Global

1.0 × 1.0 deg :: Global

1.0 × 1.0 deg :: Global

1.0 × 1.0 deg :: Global

1.0 deg zone :: Global

1.0 × 1.0 deg :: Global

1.0 × 1.0 deg :: Global

Vertical

Resolution :: Coverage

N/A :: Top of Atmosphere

N/A :: Top of Atmosphere

N/A :: Top of Atmosphere

N/A :: Top of Atmosphere

N/A :: Top of Atmosphere

N/A :: Top of Atmosphere

4-18 levels :: Top to Surface

4-18 levels :: Top to Surface

4-18 levels :: Top to Surface

4-18 levels :: Top to Surface

4-18 levels :: Top to Surface

4-18 levels :: Top to Surface

N/A :: Top and Surface

NOTE: *Data products constructed with three-satellite CERES observations using ERBE analysis methods for retrospective climate analysis

**Data products constructed with three-satellite CERES observations using two scanners and cloud imager data (VIRS, MODIS) for improved accuracy

Prelaunch calibrations of the Clouds and the Earth's Radiant Energy System (CERES), Tropical Rainfall Measuring Mission (TRMM), and Earth Observing System

Morning Spacecraft Thermistor Bolometer Sensors. IEEE

Trans. Geosci. Remote Sens., 36, 1173-1185.

Wielicki, B.A., B.R. Barkstrom, B.A. Baum, T.P. Charlock, R.N. Green, D.P. Kratz, R.B. Lee III, P. Minnis,

G.L. Smith, T. Wong, D.F. Young, R.D. Cess, J.A. Coakley

Jr, D.A.H. Crommelynck, L. Donner, R. Kandel, M.D.

King, A.J. Miller, V. Ramanathan, D.A. Randall, L.L.

Stowe, and R.M. Welch, 1998: Clouds and the Earth's

Radiant Energy System (CERES): Algorithm overview.

IEEE Trans. Geosci. Remote Sens., 36, 1127-1141.

Wielicki, B.A., B.R. Barkstrom, E.F. Harrison, R.B. Lee

III, G.L. Smith, and J.E. Cooper, 1996: Clouds and the

Earth’s Radiant Energy System (CERES): An Earth Observing System Experiment. Bull. Amer. Meteor. Soc.,

77, 853-868.

Wielicki, B.A., R.D. Cess, M.D. King, D.A. Randall, and

E.F. Harrison, 1995: Mission to Planet Earth: Role of

Clouds and Radiation in Climate. Bull. Amer. Meteor.

Soc., 76, 2125-2153.
1999 ESE Reference Handbook EOS Instruments • 109

EOSP will provide global maps of cloud and aerosol properties

from retrievals of 12-channel radiance and polarization measurements in the visible and near-infrared (0.41 to 2.25 μm). The EOSP

will scan its 10-km nadir instantaneous field-of-view from limb

to limb in either the cross-track or along-track direction. Polarization and radiance measurements as a function of the specific scattering geometries will be used to retrieve aerosol and cloud properties including optical thickness, particle size, liquid/ice phase,

and cloud-top pressure. A primary objective is the characterization of the global aerosol distribution, its spatial and temporal variability, and the corresponding impact on climate through direct

radiative effects and indirect effects as cloud condensation nuclei.

EOSP data will also be used to provide atmospheric corrections

for clear-sky ocean and land observations and to investigate the

potential for obtaining information on vegetation and land-surface characteristics.

By measuring the polarization as well as the radiance of the

sunlight scattered by the atmosphere and surface, EOSP can exploit the much greater sensitivity of the linear polarization degree

to the particular physical characteristics of the scattering particles

or surface. For observations of cloudy regions, the relative contributions to the polarization by the scattering from the cloud particles as compared to the highly wavelength-dependent Rayleigh

scattering by the atmosphere can be used to infer the cloud-top

pressure. Because of the significant differences in the linear polarization corresponding to the spherical versus non-spherical particles with sizes on the order of those typical for clouds, EOSP

observations will permit the identification of the cloud-top particle phase as liquid water or ice. The dependence of the polarization on particle size will allow its retrieval using algorithms that

also utilize the multispectral radiance information.

For observed regions that are essentially cloud free, the objective is to retrieve aerosol characteristics. A crucial step in this

retrieval process is the discrimination of truly cloud-free scenes

from those that have optically thin, or subvisible clouds. The substantial differences in the polarization signatures for the cloud

particles in contrast to the much smaller aerosol particles will be

employed to distinguish these cases. While the optically thin conditions corresponding to cloud-free scenes present an advantage

for polarization observations owing to the higher degree of polarization associated with less multiple scattering, there is the increased complexity of the contribution by the surface to the observed polarization and radiance. The separation of surface and

aerosol contributions will rely upon techniques using both wavelength-dependent characteristics and sensitivity to observer zenith angle.

Key EOSP Facts

Heritage: Pioneer Venus CPP, Galileo PPR

Provides global aerosol distribution and cloud

properties such as optical thickness and

phase

Flights of aircraft version of instrument

continuing

Algorithm development to continue

Responsible Center: NASA/ Goddard Space

Flight Center

EOSPEarth Observing Scanning Polarimeter
110 • EOS Instruments 1999 ESE Reference Handbook

Simultaneous measurement of radiance and linear

 polarization degree in 12 spectral bands from 0.41 to

 2.25 μm

Spectral bidirectional reflectance distribution function

 accurate to 5%

Polarization accurate to 0.2%

Swath: ±65° (limb-to-limb scan)

Spatial resolution: 10 km at nadir

Mass: 19 kg

Duty cycle: 100%

Power: 14 W (normal), 22 W (peak)

Data rate: 44 kbps (orbit average), 88 kbps

 (peak, daylight only)

Thermal control by: Heaters and radiators; 185 K

 radiator for SWIR detector cold focal

 plane

Thermal operating range: 0-40°C

FOV: ±65° limb to limb

Instrument IFOV: 14.2 mrad

Pointing requirements (platform+instrument, 3 σ):

Control: 3,600 arcsec

Knowledge: 150 arcsec

Stability: 100 arcsec per 10 sec

Jitter: 100 arcsec per 10 sec

Physical size: 51 × 26 × 81 cm (stowed);

51 × 56 × 81 cm (deployed)

EOSP products will fall into three major categories: Atmospheric cloud properties, aerosol properties,

and atmospheric correction radiances to be furnished

to the other surface imagers on the EOS platform. EOSP

data products will include the following:

• Cloud-top pressure, with 30-m vertical resolution and 40-km horizontal resolution

• Cloud particle phase at cloud top, with 100-km

horizontal resolution

• Cloud particle size at cloud top, with 100-km

horizontal resolution

• Cloud optical thickness, with 40-km horizontal

resolution

• Aerosol optical thicknesses at an altitude range

of 0 to 35 km, with 40-km horizontal resolution

• Atmospheric correction radiances covering the

spectral region from 0.41 to 2.25 μm, with

40-km horizontal resolution.

Principal Investigator

Larry D. Travis

Larry D. Travis received a Ph.D. from Pennsylvania

State University in 1971. He is currently the Associate

Chief at the NASA Goddard Institute for Space Studies. His research interests include radiative transfer,

single and multiple scattering theory, theoretical interpretation of planetary polarization, and satellite platform measurements of planetary polarization. Dr.

Travis served as Principal Investigator for the Pioneer

Venus Cloud Photopolarimeter Experiment and is a CoInvestigator for the Galileo Photopolarimeter Radiometer Experiment.

Co-Investigators

F. Gerald Brown - Santa Barbara Remote Sensing

Andrew Lacis - NASA/Goddard Institute for Space

Studies

William B. Rossow - NASA/Goddard Institute for

Space Studies

Edgar E. Russell - Santa Barbara Remote Sensing

References

Brown, F.G., and E.E. Russell, 1990: Earth Observing

Scanning Polarimeter, Phase B Final Report. Contract

#NAS5-30756, DM LB870016, Santa Barbara Research

Center (December).

Mishchenko, M.I., and L.D. Travis, 1997: Satellite retrieval of aerosol properties over the ocean using polarization as well as intensity of reflected sunlight. J.

Geophys. Res., 102, 16,989-17,013.

Mishchenko, M.I., and L.D. Travis, 1997: Satellite retrieval of aerosol properties over the ocean using measurements of reflected sunlight: Effect of instrumental

errors and aerosol absorption. J. Geophys. Res., 102,

13,543-13,553.

EOSP Parameters
1999 ESE Reference Handbook EOS Instruments • 111

EOSP Data Products

Product Name

Level-1B Polarization

Level-1B Radiance

Aerosol Optical Thickness

Cloud Product

0.2% :: 0.1%

5% :: 1%

0.05 :: 10%

Accuracy

Absolute :: Relative

1/day [d]

1/day [d]

1/day [d]

1/day [d]

Temporal

 Resolution

Horizontal

 Resolution :: Coverage

10-70 km :: Global

10-70 km :: Global

40 km :: Global

40-100 km :: Global

Vertical

 Resolution :: Coverage

N/A :: N/A

N/A :: N/A

Column :: Atmosphere

30 mb, Column :: Cloud
112 • EOS Instruments 1999 ESE Reference Handbook

Landsat 7 / ETM+ URL

http://landsat.gsfc.nasa.gov/

Key ETM+ Facts

Selected for flight on Landsat 7

Heritage: Landsat 4, 5 and 6

Imaging radiometer

Provides high spatial, multispectral images of the

sunlit land surface

16-day repeat cycle

7 spectral bands from visible to thermal infrared

plus panchromatic band

Launched 15 April 1999

Prime Contractor: Raytheon SBRS

Responsible Center: NASA/Goddard Space Flight

Center

The Enhanced Thematic Mapper Plus (ETM+) has flown on the

Landsat 7 satellite as of 15 April, 1999, and provides synoptic,

repetitive, multispectral, high-resolution, digital imagery of the

Earth’s land surfaces. Since 1972, the Landsat Program has provided calibrated land-surface digital imagery to a broad user group

including the agricultural community, global change researchers,

state and local governments, commercial users, international users, and the military. The Landsat 7 mission will extend the database of the Earth’s surface into the next century.

The ETM+ instrument is an improved version of the Thematic Mapper instruments that flew on Landsat 4 and 5. Like the

earlier instruments, the ETM+ will acquire data for six visible,

near-infrared, and shortwave infrared spectral bands at a spatial

resolution of 30 meters (see Spectral Band Summary table).

The ETM+ instrument also incorporates a 15-meter resolution panchromatic band as well as improved ground resolution

for the thermal infrared band (60 m vs. 120 m). Incorporation of

in-flight full- and partial-aperture solar calibration will improve

the overall radiometric accuracy to 5 percent. The ETM+ will provide data that are sufficiently consistent in terms of acquisition

geometry, spatial resolution, spectral characteristics, and calibration with previous Landsat data to meet requirements for global

change research.

The Landsat 7 satellite operates in a circular, sun-synchronous orbit with an inclination of 98.2 ̊, and altitude of 705 km,

and a descending node equatorial crossing time of 10:00 AM plus

or minus 15 minutes. This orbit will allow Landsat 7 to precede

the Terra satellite by 30 minutes along a common ground track.

The 185 km swath of coverage provided by the ETM+ field-ofview affords a global view every 16 days.

ETM+ data will be used primarily to characterize and monitor change in land-cover and land-surface processes. The high spatial resolution and seasonal global coverage of ETM+ will allow

improved assessment of both the rates of land-cover change, and

the local processes responsible for those changes. Deforestation,

ecosystem fragmentation, agricultural productivity, glacier dynamics, coastal hazards, and volcano monitoring are all science targets for ETM+. The common orbit with Terra offers additional

opportunities for data fusion with the ASTER, MISR, and MODIS sensors.

The mission will generate and periodically refresh a global

archive with substantially cloud-free, sunlit data. To facilitate this

objective, a long-term acquisition plan has been devised to ensure

maximal global data acquisition, taking into account vegetation

seasonality, cloud cover, and instrument gain.

Data stored onboard, as well as real-time continental U.S.

data, will be downlinked to the Landsat 7 ground station located

at the EROS Data Center (EDC) in South Dakota. Data received

ETM+Enhanced Thematic Mapper Plus
1999 ESE Reference Handbook EOS Instruments • 113

at the EDC will be processed for archiving and distribution by the Land Processes DAAC. All data received at

EDC will be available at L0R (no radiometric calibration; limited geometric correction). In addition, a subset

of these scenes can be processed to Level 1 (radiometric

and geometric corrections applied).

Team Leader

Samuel N. Goward

Samuel Goward received his Ph.D. in Geography from

Indiana State University in 1979, and holds A.B. and

M.A. degrees from Boston University. Dr. Goward has

been involved with the analysis of Landsat data since

the 1970’s. More recently, Dr. Goward has focused on

the extraction of vegetation biophysics from both Landsat

and AVHRR data, and on the interactions between global land cover and climate. He is currently Chair of the

Department of Geography at the University of Maryland,

College Park.

Science Team Members

Robert Bindschadler - NASA/Goddard Space Flight

Center

Robert F. Cahalan - NASA/Goddard Space Flight

Center

Luke P. Flynn - University of Hawaii

Alexander Goetz - University of Colorado

Susan Moran - U.S. Department of Agriculture

Frank Muller-Karger - University of South Florida

Frank D. Palluconi - Jet Propulsion Laboratory

John C. Price - U.S. Department of Agriculture

John R. Schott - Rochester Institute of Technology

Center for Imaging

David L. Skole - Michigan State University

Kurtis J. Thome - University of Arizona

James E. Vogelman - Raytheon ITSS

Curtis E. Woodcock - Boston University

Landsat 7 Project

Philip Sabelhaus - Landsat 7 Project Manager

Darrel Williams - Landsat 7 Project Scientist

James Irons - Deputy Project Scientist

Whiskbroom scanning radiometer

3 VIS, 1 NIR, 2 SWIR, 1 TIR, 1 pan spectral bands 30 m

 resolution in VIS, NIR, SWIR; 60 m TIR; 15 m pan

Periodic (seasonal) global coverage of land surfaces

Swath: 185 km (±7.5°)

Mass: 425 kg

Power: 590 W (imaging), 175 W (Standby)

Duty cycle: 15% imaging

Thermal control: 90 K Radiative cooler

Pointing requirements:

Control: 60 arcsec (1 sigma)

Knowledge: 45 arcsec (1 sigma)

Jitter: 4 arcsec (1 sigma)

Physical Size:

Scanner Assembly: 196 × 114 × 66 cm

Auxiliary Electronics: 90 × 66 × 35 cm

ETM+ Parameters

Spectral

Band

Panchromatic

1 (VIS)

2 (VIS)

3 (VIS)

4 (NIR)

5 (SWIR)

6 (TIR)

7 (SWIR)

0.50-0.90

0.45-0.52

0.52-0.60

0.63-0.69

0.76-0.90

1.55-1.75

10.42-12.50

2.08-2.35

Half-Amplitude

Bandwidth

(μm)

IFOV

Size (μr)

18.5 × 21.3

42.6

42.6

42.6

42.6

42.6

85.2

42.6

Nominal Ground

Sample Size (m)

15

30

30

30

30

30

60

30

ETM+ Spectral Band Summary

References

Goward, S.N., and D.L. Williams,1997: Landsat and Earth

systems science: Development of terrestrial monitoring.

Photogrammetric Engineering & Remote Sensing, 63,

887-900.
114 • EOS Instruments 1999 ESE Reference Handbook

GLAS-related URLs

http://www.csr.utexas.edu/glas/ (Science)

http://icesat.gsfc.nasa.gov (ICESat)

http://ltpwww.gsfc.nasa.gov/eib/glas.html/ (Instrument)

http://glas.wff.nasa.gov (Data System)

GLASGeoscience Laser Altimeter System

Key GLAS Facts

GLAS is a laser altimeter to be carried on ICESat (Ice, Clouds and

land Elevation Satellite), which is scheduled to launch in July 2001.

The ICESat mission will measure ice-sheet topography and associated temporal changes, cloud and atmospheric properties, and

along-track topography over land and water. For ice-sheet applications, the laser altimeter will measure height from the spacecraft to the ice sheet, to a precision of better than 10 cm with a 66-

m surface spot size. The height measurement, coupled with knowledge of the radial orbit position, will provide the determination of

surface topography. Characteristics of the return pulse will be used

to determine surface roughness. Changes in ice-sheet thickness at

a level of a few tens of cm (anticipated to occur on a subdecadal

time scale) will provide information about ice-sheet mass balance

and will support prediction analyses of cryospheric response to

future climatic changes. The ice-sheet mass balance and contribution to sea-level change will also be determined. The accuracy of

height determinations over land will be assessed using ground slope

and roughness. The surface echoes will be digitized over a total

dynamic range of 30 m over the oceans and 80 m elsewhere.

Along-track cloud and aerosol height distributions will be

determined with a vertical resolution of 75 to 200 m. The horizontal resolution will vary from 150 m for dense clouds to 50 km for

aerosol structure and planetary boundary layer height. Unambiguous measurements of cloud height and the vertical structure of

thin clouds will support studies on the influence of clouds for radiation balance and climate feedbacks. Polar clouds and haze will

be detected and sampled with much greater sensitivity, vertical

resolution, and accuracy than can be achieved by passive sensors.

Planetary boundary layer height will be directly and accurately

measured for input into surface flux and air-sea and air-land interaction models. Direct measurements of aerosol vertical profiles

will contribute to understanding of aerosol-climate effects and

aerosol transport.

The GLAS instrument is being developed by a Goddard-led

instrumentation team, and the ICESat spacecraft will be supplied

by Ball Aerospace. GLAS uses a diode pumped, Q-switched

Nd:YAG laser with energy levels of 75 mJ (1.064 μm) and 35 mJ

(0.532 μm). Three lasers will be flown to cover the lifetime of the

mission. The pulse repetition rate is 40 pulses/sec, and the beam

divergence is approximately 0.11 mrad. The infrared pulse is used

for surface altimetry and cloud-top measurements, and the green

pulse is used for measurements of thin clouds and aerosols. The

pointing angle of the laser pulse is measured with an accuracy of

about 1.5 arcseconds. The altimeter uses a 100-cm-diameter telescope.

In the 120 days following launch, the ground track will repeat

in 8 days to provide multiple overflights of ground verification/

validation sites. The main mission will use a 183-day repeat track.

EOS Facility Instrument

Selected for ICESat (Ice, Clouds and land

Elevation Satellite) flight

Heritage: Airborne and Spaceborne Laser

Altimetry and Lidar Systems; Satellite Laser

Ranging Systems

GLAS completed PDR in January 1998

GLAS CDR in March 1999

ICESat MDR in December 1998

Nadir-pointed laser altimeter at 600-km altitude,

94° inclination

Measures ice-sheet topography and temporal

changes in topography; cloud heights,

planetary boundary heights, and aerosol

vertical structure; and land and water

topography

ICESat spacecraft delivery order signed February

1998, with Ball Aerospace, Boulder, Colorado.

NASA/Goddard Space Flight Center in-house

development of GLAS

Scheduled for launch in July 2001

3-year lifetime with 5-year goal
1999 ESE Reference Handbook EOS Instruments • 115

GLAS Parameters

Team Leader

Bob E. Schutz

Bob Schutz received a Ph.D. in 1969. Currently, he is Professor of Aerospace Engineering and Engineering Mechanics at the University of Texas-Austin, and holds the FSX

Professorship in Space Applications and Exploration. He

is also Associate Director of the Center for Space Research

and a member of the Applied Research Laboratory staff,

both of which are components of the University of TexasAustin.

Dr. Schutz is active in research pertaining to the application of satellite data to the areas of geodesy, geophysics, and oceanography. He has extensive experience in the

analysis of laser-ranging measurements from the Laser

Geodynamics Satellite (LAGEOS) and other satellites,

radar-altimeter measurements collected from Seasat and

Geosat, and measurements obtained from the Global Positioning System (GPS). He has been instrumental in the

development of software for studies in crustal motions,

sea-surface topography, orbital dynamics, variations in

Earth rotation, and temporal changes in the Earth gravity

field.

Dr. Schutz serves as the President of the American

Geophysical Union Geodesy Section and on various committees in the International Association of Geodesy.

Science Team Members

Charles R. Bentley - University of Wisconsin-Madison

Jack L. Bufton - NASA/Goddard Space Flight Center

Thomas A. Herring - Massachusetts Institute of

Technology

Jean-Bernard Minster - Scripps Institution of Oceanography

James D. Spinhirne - NASA/Goddard Space Flight

Center

Robert H. Thomas - EG&G/Wallops Flight Facility

H. Jay Zwally - NASA/Goddard Space Flight Center

References

Geoscience Laser Altimeter System GLAS: Science Requirements, Prepared by GLAS Science Team, Version

2.01, October 1997.

Uses Nd:YAG laser with 1.064- and 0.532-μm output

Primary cloud and aerosol data are extracted from the

green pulse

Height measurements: Determined from the round-trip

pulse time of the infrared pulse flight

Swath: Nadir viewing

Spatial Resolution: At 40 pulses per second, the centers

of 66-m spots are separated in the along-track

direction by 170 m for a 600-km altitude orbit; the

cross-track resolution is determined by the 183-day

ground-track repeat cycle which yields 15-km track

spacing at the equator and 2.5 km at 80° latitude. The

orbit inclination is 94°

Mass: 300 kg

Duty cycle: 100%

Power: 330 W average

Data rate: ~ 450 kbps

Thermal control by: Radiators supplemented by heaters,

heat pipes

Thermal operating range: 20° ± 5° C

Telescope FOV: Nadir only, 375 μrad and 160 μrad

(0.532 μm)

Instrument IFOV: ~66 m laser footprint at nadir

Pointing Requirements (platform + instrument):

Control (3 σ): 30 arcsec roll, 30 arcsec pitch, 1° yaw

Post-processed pointing knowledge (1σ): 1.5 arcsec (roll

and pitch axes, to be provided by instrumentmounted star trackers, gyro system and laser

reference sensor [LRS])

Post-processed position requirements: radial orbit for ice

sheet to <5 cm and along-track/cross-track position

to <20 cm (to be provided by spacecraft-mounted

GPS receiver and SLR array)

Physical size: telescope diameter is 100 cm, height is

~175 cm
116 • EOS Instruments 1999 ESE Reference Handbook

GLAS Data Products

PRODUCT NAME

Level-1A Product

Level-1B Noninstrument Correction

Aerosol Vertical

Structure

Cloud Height for

Multiple Layers

Ice Sheet Elevation

Ice Sheet Roughness

Thin Cloud/Aerosol

Optical Depth

Land Topography

Vegetation

Topography

ACCURACY

 Absolute :: Relative

20% (profile), 150 m

(Boundary Layer

Height) ::

75 m ::

130 mm (single

measurement up to

1 deg surface slope) ::

10% ::

20% ::

1-5 m ::

1-5 m ::

TEMPORAL

Resolution

continuous

1/(2-25 days)

1/(2-25 days)

2/year

2/year

1/(2-25 days)

2/year

2/year

HORIZONTAL

Resolution :: Coverage

:: Global

2-100 km :: Global

0.2 - 10 km :: Global

170 m (Along Track) ×

2.5 km avg. (Cross Track)

:: Land/Cryosphere

50 km :: Land/Cryosphere

2-100 km :: Global

170 m (Along Track)

× 15 km (equator)

(Cross Track) :: Land

170 m (Along Track)

× 15 km (equator)

(Cross Track) :: Land

VERTICAL

Resolution :: Coverage

:: Global

150 m (profile), N/A

(Boundary Layer

Height) :: Atmosphere

N/A :: Cloud

N/A :: Cryosphere

N/A :: Cryosphere

N/A :: Atmosphere

N/A :: Surface

N/A :: Surface
1999 ESE Reference Handbook EOS Instruments • 117

Key HIRDLS Facts

Selected for flight on EOS CHEM

Heritage: LRIR (Nimbus-6), LIMS and SAMS

(Nimbus-7), ISAMS and CLAES (UARS)

Observes global distribution of temperature and

concentrations of O3, H2O, CH4, N2O, NO2,

HNO3, N2O5, CFC11, CFC12, ClONO2, and

aerosols in the upper troposphere, stratosphere, and mesosphere

Scanning infrared limb sounder

21 photoconductive HgCdTe detectors cooled to

65 K; each detector has a separate band-pass

interference filter

Joint program between University of Colorado and

Oxford University

Prime Contractors: Lockheed Martin (U.S.) and

Matra-Marconi Space (U.K.)

HIRDLS is an infrared limb-scanning radiometer designed to

sound the upper troposphere, stratosphere, and mesosphere to determine: temperature; the concentrations of O3, H2O, CH4, N2O,

NO2, HNO3, N2O5, CFC11, CFC12, ClONO2, and aerosols; and

the locations of polar stratospheric clouds and cloud tops. The

goals are to provide sounding observations with horizontal and

vertical resolution superior to that previously obtained; to observe

the lower stratosphere with improved sensitivity and accuracy;

and to improve understanding of atmospheric processes through

data analysis, diagnostics, and use of two- and three-dimensional

models.

HIRDLS performs limb scans in the vertical at multiple azimuth angles, measuring infrared emissions in 21 channels ranging from 6.12 to 17.76 μm. Four channels measure the emission

by CO2. Taking advantage of the known mixing ratio of CO2, the

transmittance is calculated, and the equation of radiative transfer

is inverted to determine the vertical distribution of the Planck black

body function, from which the temperature is derived as a function of pressure. Once the temperature profile has been established,

it is used to determine the Planck function profile for the tracegas channels. The measured radiance and the Planck function profile are then used to determine the transmittance of each trace

species and its mixing-ratio distribution.

Winds and potential vorticity are determined from spatial

variations of the height of geopotential surfaces. These are determined at upper levels by integrating the temperature profiles vertically from a known reference base. HIRDLS will improve knowledge in data-sparse regions by measuring the height variations of

the reference surface with the aid of a gyro package. This level

(near the base of the stratosphere) can also be integrated downward using nadir temperature soundings to improve tropospheric

analyses.

Overall science goals of HIRDLS are to observe the global

distributions of temperature and several trace species in the stratosphere and upper troposphere at high vertical and horizontal resolution. Specific issues to be investigated include:

• Fluxes of mass and chemical constituents between the troposphere and stratosphere [stratosphere-troposphere exchange

(STE)];

• chemical processes, transport, and mixing [particularly in the

upper troposphere/lower stratosphere (UT/LS)];

• momentum, energy, heat, and potential vorticity balances of

the upper troposphere and middle atmosphere;

HIRDLSHigh Resolution Dynamics Limb Sounder

HIRDLS URL

http://web.eos.ucar.edu/hirdls/
118 • EOS Instruments 1999 ESE Reference Handbook

• geographically and seasonally unbiased long-term

climatologies and interannual variability of middleatmosphere temperature, constituents, dynamical

fields, and gravity waves;

• global distributions and interannual variations of

aerosols, cirrus, and PSCs;

• tropospheric cloud-top heights;

• tropospheric temperature and water vapor retrievals

(by providing high-resolution limb data for joint retrieval with EOS nadir sounders); and

• diagnostic studies of atmospheric dynamics, chemistry, and transport processes, down to small spatial

scales, to test and improve models of these processes.

The instrument has a long heritage extending back

to Nimbus-4, and will obtain profiles over the entire

globe, including the poles, both day and night. Complete

Earth coverage (including polar night) can be obtained

in 12 hours. High horizontal resolution is obtained with

a commandable azimuth scan that, in conjunction with a

rapid elevation scan, provides profiles up to 3,000 km

apart in an across-track swath. Vertical profiles are spaced

every 5° in latitude and longitude. Observations of the

lower stratosphere and upper troposphere are improved

through the use of special narrow and more-transparent

spectral channels. The instrument is programmable; thus,

a variety of observation modes can be used, and may be

adapted in flight to observe unpredicted geophysical

events.

Co-Principal Investigators

John Barnett

Dr. Barnett received an M.A. in Natural Sciences, with

first-class honors, from Cambridge University and a

Ph.D. in Atmospheric Physics from Oxford University.

He is currently a University Research Lecturer for the

Department of Physics at Oxford. Dr. Barnett served as

a member of data-processing teams for the suite of Nimbus instruments, as Co-Investigator for Improved Stratospheric and Mesospheric Sounder (ISAMS), and as cochairman of the COSPAR group on the Reference Middle

Atmosphere. He is the recipient of the COSPAR William Nordberg Award and the Royal Meteorological Society L. F. Richardson Award.

John Gille

John Gille received a B.S. in Physics, magna cum laude,

from Yale University, an M.A. in Physics from Cambridge University, and a Ph.D. in Geophysics from MIT.

He has served as Head of the Global Observations, Modeling, and Optical Techniques Section of NCAR. Dr. Gille

was Co-Sensor Scientist on LIMS, launched on Nimbus7, and was Principal Investigator on LRIR, which flew

on Nimbus-6. He has been involved in CLAES collaboration, with NOAA’s development of GOMR, and on several investigations analyzing satellite data. He is a Fellow of the American Meteorological Society and the

American Association for the Advancement of Science,

and was the recipient of the NCAR Technology Advancement Award and the NASA Exceptional Scientific

Achievement Medal.

Co-Investigators

David Andrews - Oxford University, United Kingdom

Linnea Avallone - University of Colorado

Byron Boville - National Center for Atmospheric

Research

Guy Brasseur - National Center for Atmospheric

Research

Michael Coffey - National Center for Atmospheric

Research

Robert S. Harwood - University of Edinburgh, United

Kingdom

James R. Holton - University of Washington

Conway B. Leovy - University of Washington

William Mankin - National Center for Atmospheric

Research

Michael E. McIntyre - University of Cambridge,

United Kingdom

Heinz G. Muller - University of Sheffield, United

Kingdom

Christopher T. Mutlow - Rutherford Appleton Laboratory, United Kingdom

Alan O’Neill - University of Reading, United Kingdom

John A. Pyle - Cambridge University, United Kingdom

Clive D. Rodgers - Oxford University, United Kingdom

Frederic Taylor - Oxford University, United Kingdom

O. Brian Toon - University of Colorado

Geraint Vaughan - University College of Wales, United

Kingdom

Robert J. Wells - Oxford University, United Kingdom

John G. Whitney - Oxford University, United Kingdom

E.J. Williamson - Oxford University, United Kingdom
1999 ESE Reference Handbook EOS Instruments • 119

References

Barnett, J.J., A.G. Darbyshire, C.L. Hepplewhite, C.W.P.

Palmer, F. Row, P. Venter s, R.E.J. Watkins, J.G. Whitney,

J.C. Gille, and B.R. Johnson, 1998: Pre-launch calibration of the HIRDLS instrument. SPIE, 3437, 137-146.

Barnett, J.J., P. Venters, and J.C. Gille, 1998: Direct Measurement of Geopotential Height by the HIRDLS Instrument. Adv. Space Res., 22, 1497-1500.

Dials M.A., J.C. Gille, J.J. Barnett, and J.G. Whitney,

1998: Description of the High Resolution Dynamics Limb

Sounder (HIRDLS) instrument. SPIE, 3437, 84-91.

Edwards, D., J. Gille, P. Bailey, and J. Barnett, 1995:

Selection of the sounding channels for the High Resolution Dynamics Limb Sounder. Appl. Optics, 34, 7006-

7017.

Gille, J., and J. Barnett, 1992: The High-Resolution Dynamics Limb Sounder (HIRDLS). An instrument for the

study of global change. The Use of EOS for Studies of

Atmospheric Physics, J. Gille and G. Visconti, Eds.,

North-Holland, 433-450.

Gille, J., J. Barnett, M. Coffey, W. Mankin, B. Johnson,

M. Dials, J. Whitney, D. Woodard, P. Arter, and W.

Rudolf, 1994: The High Resolution Dynamics Limb

Sounder (HIRDLS) for the Earth Observing System.

SPIE, 2266, 330-339.

Gille, J., and J. Barnett, 1996: Conceptual design of the

High Resolution Dynamics Limb Sounder (HIRDLS) for

the EOS Chemistry Mission. SPIE, 2830, 190-201.

Gille, J.C., and J.J. Barnett, 1996: Conceptual design of

the High Resolution Dynamics Limb Sounder (HIRDLS)

for the EOS Chemistry Mission. SPIE, 2830, 190-201.

Johnson, B.R., W.G. Mankin, and J.C. Gille, 1998: Description of the HIRDLS Radiometric Model (HIRAM).

SPIE, 3437, 147-155.

Palmer, C., and J. Whitney, 1996: The radiometric calibration budget for the High-Resolution Dynamics Limb

Sounder. J. Atmos. Ocean. Tech., 13, 336-348.

HIRDLS Parameters

Spectral range: 6 to 18 μm

Standard profile spacing: 5° longitude × 5° latitude, and

1-km vertical resolution; programmable to other

modes and resolutions

Swath: Typically six profiles across 2,000-

to-3,000-km-wide swath

Spatial resolution: Profile spacing 500 × 500 km

horizontally (equivalent to 5° long × 5° lat) × 1 km

vertically; averaging volume for each data sample 1

km vertical × 10 km across × 300 km along line-ofsight

Mass: 220 kg

Duty cycle: 100%

Power: 220 W (average), 239 W (peak)

Data rate: 65 kbps

Thermal control by: Stirling cycle cooler, heaters, sun

baffle, radiator panel

Thermal operating range: 20-30° C

Scan range: Elevation, 22.1° to 27.3° below

horizontal, Azimuth, -21° (sun side) to +43° (anti-sun

side)

Detector IFOV: 1 km vertical × 10 km horizontal

Platform pointing requirements (platform+instrument, 3 σ):

Control and Knowledge: Such that scan range will allow

all channels to observe from 0.25° below the hard

horizon to 3.25° above it

Stability: 30 arcsec/sec per axis

Jitter: 84-Hz sample spacing uniform to

 ±7 arcsec

Physical size: 154.5 × 113.5 × 130 cm
120 • EOS Instruments 1999 ESE Reference Handbook

HIRDLS Data Products

Product Name

Level-1B Product

Aerosol Extinction Coef (4 channels)

CFC-11 (CFCl3

) Conc

CFC-12 (CF2Cl2) Conc

CH4 Conc

ClONO2

Cloud Top Altitude

Geopotential Height-Gradient

H2O Conc

HNO3

 Conc

N2O Conc

N2O5 Conc

NO2

 Conc

O3 Conc

Temperature/Pressure Profile

.5-1% :: 1-8 x 10-4 Wm-2sr

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 3-15%

1 km :: 400 m

0.04 m/km :: 0.04 m/km

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 1-10%

5-10% :: 3-10%

1-2 K :: 0.4-1 K

Accuracy

Absolute :: Relative

12 msec :: Continuous

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

2/day [d,n]

Temporal

Resolution :: Coverage

Horizontal

Resolution :: Coverage

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

500 km :: Global

Vertical

Resolution :: Coverage

200 m :: 0-150 km

1 km :: 5-60 km

(given accuracies for 7-30 km)

1 km :: 5-50 km

(given accuracies for 7-30 km)

1 km :: 5-55 km

(given accuracies for 7-30 km)

1 km :: 5-65 km

(given accuracies for 7-65 km)

1 km :: 15-65 km

(given accuracies for 15-80 km)

1 km :: 5-20 km

1 km :: 5-100 km

(given accuracies for 15-80 km)

1 km :: 5-70 km

(given accuracies for 7-65 km)

1 km :: 5-50 km

(given accuracies for 10-40 km)

1 km :: 5-70 km

(given accuracies for 7-60 km)

1 km :: 10-65 km

(given accuracies for 15-45 km)

1 km :: 5-65 km

(given accuracies for 15-55 km)

1 km :: 5-85 km

(given accuracies for 7-80 km)

1 km :: 5-100 km

(given accuracies for 8-80 km)
1999 ESE Reference Handbook EOS Instruments • 121

Poseidon-2

Poseidon-2 is a nadir-looking radar altimeter that maps the

topography of the sea surface. The shape and strength of the

radar return pulse also provide measurements of ocean wave

height and wind speed, respectively. Through the mapping

of sea-surface topography, Poseidon-2 provides information

on the ocean-surface current velocity which, when combined

with ocean models, can lead to a four-dimensional description of ocean circulation. The heat and biogeochemical fluxes

carried by ocean currents hold the key to understanding the

ocean’s role in global changes in climate and biogeochemical cycles. Secondary research contributions include the

study of the variations in sea level in response to global

warming/cooling and hydrological balance; the study of

marine geophysical processes (such as crustal deformation)

from the sea-surface topography; and the monitoring of global sea state from the wave height and wind-speed measurement.

Poseidon-2 was developed by Alcatel Espace Systems

(ATES) under contract from CNES Toulouse Space Center.

A single-frequency version of this altimeter (Poseidon-1) is

being flown on TOPEX/Poseidon as an experimental instrument to allow validation of the accuracy, operation, and signal processing of a small-volume, lightweight, low-power

altimeter. It uses the same antenna as the NASA Altimeter

(ALT) aboard TOPEX/Poseidon, but operates at the single

frequency of 13.6 GHz. Both the operating principles and

the performance of the NASA and CNES altimeters are similar; however, Poseidon-1 has only one-fourth the mass, volume, and power consumption of the NASA instrument.

Moreover, the telemetry data rate is reduced by a factor of

seven because of more-extensive onboard processing.

Poseidon-2 is a version of Poseidon-1, improved by adding a second frequency at 5.3 GHz, as well as changing to

digital technology and using a new, more-powerful rad-hard

microprocessor, while keeping the same mass and size as

the single-frequency altimeter.

JMR

Altitude accuracy (as determined by the altimeter aboard

Jason-1) is affected by the variable water content of the atmosphere, mainly the troposphere. The primary JMR objective involves measuring the radiometric brightness temperature related to water vapor and liquid water in the same

field-of-view as the altimeter. In turn, these brightness temperatures are converted to path-delay information required

Jason-1

Heritage: TOPEX/Poseidon, SPOT-2, SPOT-3, SPOT-4

Precision orbit determination system

Provides orbital positioning information

Prime contractors: Dassault Electronique (onboard

instrument), CEIS Espace and SOREP (ground

beacons).

Responsible center: Centre Nationale d’Etudes

Spatiales (France)

Key DORIS Facts

Heritage: TOPEX/Poseidon, Seasat, Nimbus-7

Tri-frequency microwave radiometer

Provides total water vapor along the path viewed by the

altimeter for range correction

In-house Jet Propulsion Laboratory development

Key Jason Microwave Radiometer

(JMR) Facts

Heritage: Poseidon-1 radar altimeter

Dual-frequency radar altimeter

Maps the topography of the sea surface for calculating

ocean surface current velocity

Measures ocean wave height and wind speed

Prime contractor: Alcatel Espace

Responsible center: Centre Nationale d’Etudes Spatiales

(France)

Key Poseidon-2 Facts

* Collectively, DORIS, Poseidon-2, JMR, LRA, and TRSR

make up the instrumentation for the radar altimetry Jason-1

mission

Jason-1

POSEIDON-2 • JMR • DORIS*

Jason-1 URL

http://topex-www.jpl.nasa.gov/jason1/
122 • EOS Instruments 1999 ESE Reference Handbook

Poseidon-2 Parameters

Transmitted pulse width of 105 μsec

Pulse repetition frequency of 2100 Hz (1800 for Ku band

and 300 for C band)

Maximum radio frequency output power to antenna of

40 dBm (Ku band) and 46 dBm (C band)

Mass: 52 kg for a dual frequency, dual configuration with

one antenna

Duty cycle: 100%

Power: 66 W (43 W RFU, 23 W PCU)

DC supply bus: Unregulated 21-32 V

Transmission frequency: 13.575 GHz, 5.3 GHz

Data rate: 22.5 kbps (including wave form data and onboard estimated parameters)

Thermal control by: Heat transfer by conduction to

mounting surface and by radiation within the instrument

module

Thermal operating range: -5-35° C

IFOV: 20° cone (centered on nadir)

Pointing requirements (platform+instrument, 3 σ):

Control (Satellite): 0.33° (3 σ)

Knowledge: <0.1°

Physical size: 42.2 × 24.6 × 24.5 cm (RFU);

 26.8 × 20.5 × 24.9 cm (PCU)

ates most efficiently at an altitude between 750 and 1,500

km. However, DORIS can operate from 300 km to several thousand km.

Team Leader

Since Jason-1 is essentially a follow-on to TOPEX/Poseidon as a collaborative effort between NASA and CNES,

it was decided that the organization and management of

its Science Working Team (SWT) should follow the

model of TOPEX/Poseidon. The SWT is co-chaired by a

French Project Scientist and an American Project Scientist. As co-leaders of the SWT, the two Project Scientists

will fulfill the role of the Team Leader. The current American Project Scientist is Dr. Lee-Lueng Fu of the Jet Propulsion Laboratory of California Institute of Technology,

and the French Project Scientist is Dr. Yves Menard of

CNES’s Toulouse Space Center. To facilitate the participation of the members of the SWT in important mission

decisions, two members of the SWT (one from the US

and one from France) will be selected to be part of the

mission’s top management team (the Joint Steering

Group).

by the altimeter for precise topography measurements.

In order to achieve the required 1.2-cm path delay, the

absolute accuracy required of JMR is 1 K.

JMR will passively measure microwave radiation

continously, and derived data will be used to determine

water vapor and liquid water content in the altimeter fieldof-view. JMR consists of a collecting aperture, a multifrequency feed assembly that illuminates the collecting

aperture; multichannel microwave receivers; a data unit;

power supplies; and ground support equipment.

Developed by the Jet Propulsion Laboratory (JPL),

JMR operates at frequencies of 18.7, 23.8, and 34 GHz

to provide estimates of total atmospheric water-vapor

content. By operating simultaneously on three frequencies, the columnar path delay is derived from microwave

brightness temperature. The 23.8 GHz frequency is the

primary measurement channel; the 18.7 and 34 GHz channels are used to remove the effects of wind speed and

cloud cover, respectively. The 23.8 GHz channel is redundant. These data allow reduction of the water vapor

delay error to 1 cm, permitting an overall altimetric accuracy of 3 cm. In-flight calibration is provided by three

cross-calibrated noise diodes.

DORIS

DORIS is based upon the accurate measurement of the

doppler shift of radiofrequency signals transmitted from

ground-based beacons and received on board the spacecraft when it passes over. Measurements are made on

two frequencies: 2.03625 GHz for precise doppler measurement and 401.25 MHz for ionospheric correction.

The 401.25 MHz is also used for measurement time tagging and auxiliary data. Approximately 50 global allweather radio beacons are currently in operation.

The separation of the two transmitting frequencies

makes it possible to reduce the ionospheric effect to

around the centimeter level. Tropospheric refraction is

modeled using surface meteorological data which are

directly transmitted to the satellite from the ground stations.

DORIS was validated by a prototype flown on the

Systeme pour l’Observation de la Terre-2 (SPOT-2) satellite, launched in January 1990. It provides over six thousand measurements per day, which are used to refine dataprocessing methods and to improve models of the Earth’s

gravity field. A DORIS instrument now operates aboard

the Ocean Topography Experiment (TOPEX/Poseidon)

spacecraft, a joint mission between the U.S. and France

launched in August 1992. A new capability has been validated onboard SPOT-4 (launched in 1998). It is the realtime onboard orbit determination.

The DORIS instruments slated for the Jason series

will be upgraded versions of those aboard TOPEX/

Poseidon. Experience with SPOT-2, SPOT-4, and

TOPEX/Poseidon has shown that the instrument oper-
1999 ESE Reference Handbook EOS Instruments • 123

DORIS Parameters

Onboard DORIS receiver accurately measures the Doppler shift

on both transmitted frequencies (401.25 and 2,036.25 MHz)

received from an orbit determination beacon (ODB) station

Network of ~50 ODBs located worldwide

Receiver: 5.6 kg

USO: 1.2 kg (Total mass for a dual-string configuration is

17 kg)

Antenna: 2 kg

USO Shielding: 8 kg (Depending on magnetic environment.)

Duty Cycle: 100%

Power: 24 W (28 W peak)

Data rate: 500 bps (including the raw doppler data; 360 bps for

the science operational data)

Thermal control: Heat transfer by conduction to mounting

surface and by radiation within the instrument module

Thermal operating range: -10-50° C

IFOV: 125° cone (centered on nadir)

Pointing requirements (platform+instrument, 3 σ):

Control: 1.5°

Knowledge: 0.2° (depending on the distance between the

antenna phase center and the satellite center of

mass

Physical size: 32 × 27 × 10 cm (receiver);

9 × 7 × 11 cm (Ultra Stable Oscillator [USO]);

32 × 27 × 22 cm (USO magnetic shielding)

Antenna: 40 cm height × 16 cm diameter cone

JMR Parameters

Measures brightness temperatures in the nadir column at

18.7, 23.8, and 34 GHz.

Beamwidth: 1.8° at 18.7 GHz, 1.5° at 23.8 GHz, and

0.9° at 34 GHz

Temperature resolution: <1 K

System temperature: <650 K

Mass: 27 kg

Duty cycle: 100%

Power: 24 W

DC supply bus: Unregulated 23-36 V

Data rate: 1024 bps

Thermal control by: Thermal control on the JMR is by

radiation to the satellite structure. The JMR box is

internally mounted, with no direct exposure to space.

Thermal operating range: 10-35° C

Physical size: 75 × 86 × 137 cm

Team Members

Rodrigo Abarca - University of Chile

Sabine Arnault - LODYC, France

David V. Arnold - Brigham Young University

Pierre Bahurel - SHOM/CMO, France

Mike Bell - U.K. Met Office

George H. Born - University of Colorado

Jean-Philippe Boulanger - LODYC, France

Derek M. Burrage - Australian Institute of Marine

Science

Antonio Busalacchi - NASA/Goddard Space Flight

Center

Stephane Calmant - ORSTOM, France

Anny Cazenave - LEGOS/GRGS/UMR5566, France

Peter Challenor - SOC, U.K.

Benjamin Fong Chao - NASA/Goddard Space Flight

Center

Dudley B. Chelton - Oregon State University

Robert E. Cheney - NOAA/NESDIS/NODC

John A. Church - CSIRO, Australia

David Cotton - SOC, U.K.

Philipe Courtier - LODYC, France

Pierre De Mey - LEGOS/GRGS/UMR5566, France

Richard J. Eanes - University of Texas, Austin

William J. Emery - CSIRO, Australia

Pierre Exertier - OCA/CERGA, France

Laurence Eymard - CETP/IPSL/CNRS, France

Nelson M. Frew - Woods Hole Oceanographic Institution

Ichiro Fukumori - Jet Propulsion Laboratory

Sarah Gille - University of East Anglia, U.K.

Roman E. Glazman - Jet Propulsion Laboratory

Bruce J. Haines - Jet Propulsion Laboratory

David W. Hancock - NASA/Goddard Space Flight

Center

Shiro Imawaki - Kyushu University, Japan

Gregg A. Jacobs - NASA/Stennis Space Flight Center

Per Knudsen - NSC, Denmark

Chester J. Koblinsky - NASA/Goddard Space Flight

Center

Christian Le Provost - LEGOS/GRGS/UMR5566,

France

Pierre-Yves Le Traon - CLS, France

Jean-Michel Lefevre - Météo-France

Daniel S. MacMillan - NVI, Inc.

Mark A. Merrifield - University of Hawaii

Gary T. Mitchum - University of South Florida

Philip Moore - Aston University, U.K.
124 • EOS Instruments 1999 ESE Reference Handbook

Rosemary Morrow - LEGOS/GRGS/UMR5566, France

Steven R. Nerem - University of Texas, Austin

James J. O'Brien - Florida State University

Young-Hyang Park - LOP Museum, France

Michel Petit - ORSTOM, France

Joel Picaut - ORSTOM, France

Rui M. Ponte - AER, Inc.

Christine Provost - LODYC, France

Bo Qui - University of Hawaii, Manoa

Richard D. Ray - Raytheon ITSS

John C. Ries - University of Texas, Austin

Ernesto Rodriguez - Jet Propulsion Laboratory

Dean Roemmich - University of California, San Diego

Philippe Rogel - CERFACS, France

Christopher S. Ruf - Pennsylvania State University

Ernst Schrama - DEOS, The Netherlands

Jens Schroeter - AWI, Germany

David Smith - NASA/Goddard Space Flight Center

Radar Altimetry Data Products

Product Name

Altimetry Sensor

Data Record

Altimetry

Geophysical Data

Record

Sea_surface

Topography Map

Accuracy

Absolute :: Relative

0.7 :: 0.2 dB

4 cm :: 2 cm

10 cm :: 2 cm

Temporal

Resolution

20/second

1/second

1/(10 day)

Horizontal

Resolution :: Coverage

0.35 km :: Earth

7 km :: Ocean

25 km :: Ocean

Vertical

Resolution :: Coverage

N/A :: Surface

N/A :: Surface

N/A :: Surface

Detlef Stammer - Massachussetts Institute of Technology

Robert H. Stewart - Texas A&M University

P. Ted Strub - Oregon State University

Robin T. Tokmakian - Naval Postgraduate School

Jean Tournade - IFREMER, France

Douglas C. Vandemark - Wallops Flight Facility

Jacques Verron - LEGI, France

Michael M. Watkins - Jet Propulsion Laboratory

Warren B. White - University of California, San Diego

Pascal Willis - IGN, France

Philip Woodworth - POL, U.K.

Reference

Carayon, G., E. Thouvenot, N. Armand, C. Goldstein, P.

DeChateau-Thierry, L. Rey: “Jason Mission Poseidon-2

Radar Altimeter Design,” CNES Technical Note.
1999 ESE Reference Handbook EOS Instruments • 125

LIS is currently on orbit investigating the global incidence of lightning, its correlation with convective rainfall, and its relationship

with the global electric circuit. Conceptually, LIS is a simple device, consisting of a staring imager optimized to locate both

intracloud and cloud-to-ground lightning with storm-scale resolution over a large region of the Earth’s surface, to mark the time

of occurrence, and to measure the radiant energy. It will monitor

individual storms within the field-of-view (FOV) for 80 seconds,

long enough to estimate the lightning flashing rate. Location of

lightning flashes is determined to within 5 km over a 600 × 600 km

FOV.

The LIS design uses an expanded optics wide-FOV lens, combined with a narrow-band interference filter that focuses the image on a small, high-speed, charge-coupled-device focal plane.

The signal is read out from the focal plane into a real-time data

processor (rtdp) for event detection and data compression. The

particular characteristics of the sensor design result from the requirement to detect weak lightning signals during the day when

the background illumination, produced by sunlight reflecting from

the tops of clouds, is much brighter than the illumination produced by the lightning.

A combination of four methods is used to take advantage of

the significant differences in the temporal, spatial, and spectral

characteristics between the lightning signal and the background

noise. First, spatial filtering is used to match the instantaneous

FOV of each detector element in the LIS focal-plane array to the

typical cloud-top area illuminated by a lightning event (about 5

km). Second, spectral filtering is applied, using a narrow-band

interference filter centered about the strong OI (1) emission multiplet in the lightning spectrum at 777.4 nm. Third, temporal filtering is applied. The lightning pulse duration is of the order of

400 μsec, whereas the background illumination tends to be constant on a time scale of seconds. The lightning signal-to-noise

ratio improves as the integration time approaches the pulse duration. Accordingly, an integration time of 2 msec is chosen to minimize pulse splitting between successive frames and to maximize

lightning detectability. Finally, a modified frame-to-frame background subtraction is used to remove the slowly varying background signal from the raw data coming off the LIS focal plane.

If, after background removal, the signal for a given pixel exceeds

a specified threshold, that pixel is considered to contain a lightning event.

LIS investigations are striving to understand processes related to, and underlying, lightning phenomena in the Earth/atmosphere system. These processes include the amount, distribution,

and structure of deep convection on a global scale, and the coupling between atmospheric dynamics and energetics as related to

the global distribution of lightning activity. The investigations will

contribute to a number of important EOS mission objectives, inEOS-funded instrument selected for flight on

TRMM

Staring telescope/filter imaging system that

detects the rate, location, and radiant energy

of lightning flashes

Investigates the distribution and variability of

lightning over the Earth with storm-scale

spatial resolution

90% detection efficiency under both day and

night conditions using background remover

and event processor

In-house NASA/Marshall Space Flight Center

development

Phase C/D start January 1991

Prototype for geostationary orbit

Key LIS Facts

LISLightning Imaging Sensor

LIS URL

http://thunder.msfc.nasa.gov/lis.html

Sensor Head Assembly and Telescope
126 • EOS Instruments 1999 ESE Reference Handbook

LIS Parameters

Storm-scale (5-km) spatial resolution; 2-msec temporal

resolution

Spectral filter to image at 0.777 μm onto a 128 x 128 CCD

array detector

Event processor to subtract out the bright background

during daylight (instrument taking data day and night)

Swath: 600 × 600 km

Spatial resolution: 5 km

Mass: 20 kg

Duty cycle: 100%

Power: 33 W

Data rate: 6 kbps

Thermal control by: Heater, radiator

Thermal operating range: 0 - 40° C

FOV: 80° x 80°

Instrument IFOV: 0.7°

Pointing requirements (platform+instrument, 3 σ):

Control: None

Knowledge: 1 km on ground

Stability: TBD

Jitter: TBD

Physical size:

Sensor head assembly (cylindrical): 20 × 30 cm;

Electronics assembly: 30 × 20 × 30 cm

cluding cloud characterization and hydrologic cycle studies. Lightning activity is closely coupled to storm convection, dynamics, and microphysics, and can be correlated to the global rates, amounts, and distribution of

convective precipitation, to the release and transport of

latent heat, and to the chemical cycles of carbon, sulfur,

and nitrogen. LIS standard products include intensities,

times of occurrence, and locations of lightning events.

LIS was launched as part of the Tropical Rainfall

Measuring Mission (TRMM) in November 1997. Since

that time its performance has exceeded specifications. It

has been returning unprecedented data on lightning activity. LIS on the TRMM spacecraft is enabling investigators to quantify relationships between lightning, convection, and ice production. Check the Web site at http:/

/thunder.msfc.nasa.gov/ for the latest results.

Principal Investigator

Hugh Christian

Hugh Christian is a graduate of the University of Alaska,

and received M.S. and Ph.D. degrees in Space Physics

and Astronomy from Rice University. He has served in

various government, private industry, and academic capacities, primarily within his area of expertise: thunderstorms, atmospheric electricity, lightning data acquisition systems, and airborne instrumentation. Since 1980,

Dr. Christian has been a space scientist at the Marshall

Space Flight Center.

Co-Investigators

Richard Blakeslee - NASA/Marshall Space Flight

Center

Steven J. Goodman - NASA/Marshall Space Flight

Center

Douglas M. Mach - University of Alabama

References

Christian, H.J., R.J. Blakeslee, and S.J. Goodman, 1989:

The detection of lightning from geostationary orbit. J.

Geophys. Res., 94, 13,329-13,337.

Christian, H.J., R.J. Blakeslee, and S.J. Goodman, 1992:

Lightning Imaging Sensor (LIS) for the Earth Observing

System. NASA Technical Memorandum 4350, MSFC,

Huntsville, AL.

Goodman, S.J., and H.J. Christian, 1993: Global observations of lightning. Atlas of Satellite Observations Related to Global Change, Edited by R. Gurney, J. Foster,

and C. Parkinson. Cambridge University Press, New

York, 191-219.
1999 ESE Reference Handbook EOS Instruments • 127

LIS Data Products

ACCURACY

Absolute :: Relative

:: 2.4 × 10-4

:: 2.4 × 10-4

:: 7.8 × 10-3

:: 7.8 × 10-3

:: 7.8 × 10-3

:: 7.8 × 10-3

:: 1

:: 1

:: N/A

TEMPORAL

Resolution

2 ms

2 ms

2 ms

2 ms

2 ms

2 ms

1 orbit

1 orbit

1 orbit

HORIZONTAL

Resolution :: Coverage

3.5 km :: Global

3.5 km :: Global

3.5 km :: Global

3.5 km :: Global

3.5 km :: Global

3.5 km :: Global

500 km :: Global

3.5 km :: Global

3.5 km :: Global

Vertical

Resolution :: Coverage

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

PRODUCT/

COMPONENT NAME

Raw Data

Lightning

Background Images

(Level 1-B Component)

Events

(Level 1-B Component)

Groups

(Level 2 Component)

Flashes

(Level 2 Component)

Areas

(Level 2 Component)

Vector Data

(Level 2 Component)

Browse Data

(Level 3 Component)

Orbit Stats

(Level 3 Component)
128 • EOS Instruments 1999 ESE Reference Handbook

Key MISR Facts

Selected for flight on Terra

Heritage: GLL, Wide-Field/Planetary Camera

Provides top-of-atmosphere, cloud, and surface

angular reflectance functions

Provides global maps of planetary and surface

albedo, and aerosol and vegetation properties

In-house Jet Propulsion Laboratory development

Phase C/D start January 1991

MISR will routinely provide multiple-angle, continuous sunlight

coverage of the Earth with high spatial resolution. The instrument

will obtain multidirectional observations of each scene within a

time scale of minutes, thereby under virtually the same atmospheric

conditions. MISR uses nine individual charge-coupled device

(CCD)-based pushbroom cameras to observe the Earth at nine discrete view angles: One at nadir, plus eight other symmetrical views

at 26.1, 45.6, 60.0, and 70.5° forward and aftward of nadir. Images at each angle will be obtained in four spectral bands centered

at 446, 558, 672, and 866 nm. Each of the 36 instrument data channels (4 spectral bands × 9 cameras) is individually commandable

to provide ground sampling of 275 m, 550 m, or 1.1 km. The swath

width of the MISR imaging data is 360 km, providing global multiangle coverage of the entire Earth in 9 days at the equator, and 2

days at the poles.

The instrument design and calibration strategies have the goal

of maintaining absolute radiometric uncertainty to less than ±3%

over bright surfaces and ±6% over dark surfaces, with smaller uncertainties in relative band-to-band and angle-to-angle radiances.

These objectives will be met through the use of state-of-the-art

detector-based calibration, using on a monthly basis an on-board

calibrator consisting of deployable solar diffuser panels and an

array of radiation-resistant and high-quantum-efficiency diodes.

Semi-annual field calibration exercises are planned to provide a

ground-truth verification of the diode performance.

MISR images will be acquired in two observing modes: Global and Local. Global Mode provides continuous planet-wide observations, with most channels operating at moderate resolution

and selected channels operating at the highest resolution for cloud

screening and classification, image navigation, and stereo-photogrammetry. Local Mode provides data at the highest resolution in

all spectral bands and all cameras for selected 300 km × 300 km

regions. In addition to data products providing radiometrically calibrated and geo-rectified images, Global Mode data will be used to

generate two standard Level 2 science products during ground data

processing: the Top-of-Atmosphere (TOA)/Cloud Product and the

Aerosol/Surface Product.

The purpose of the TOA/Cloud Product is to enable study, on

a global basis, of the effects of different types of cloud fields (classified by their heterogeneity and altitude) on the solar radiance

and irradiance reflected to space, and to determine their effects on

the Earth’s climate. Additionally, this product provides a cloud

screen for MISR aerosol and surface retrievals.

The aerosol parameters contained within the Aerosol/Surface

Product will enable study, on a global basis, of the magnitude and

natural variability in space and time of sunlight absorption and

scattering by aerosols in the Earth’s atmosphere, particularly in

the troposphere, and to determine their effects on climate; to improve our knowledge of the sources, sinks, and global budgets of

MISRMulti-angle Imaging SpectroRadiometer

MISR URL

http://www-misr.jpl.nasa.gov/
1999 ESE Reference Handbook EOS Instruments • 129

natural and anthropogenic aerosols, and to provide atmospheric correction inputs for surface-imaging data acquired by MISR and other instruments (e.g., MODIS and

ASTER) that are simultaneously viewing the same portion of the Earth. The surface parameters within the Aerosol/Surface Product are designed to enable improved

measures of land-surface characteristics, particularly bidirectional and hemispherical reflectances, leaf area index, surface-cover type, and fractional absorbed photosynthetically active radiation, on a global basis; to provide, in conjunction with MODIS, improved measures

of land-surface classification, dynamics, and over vegetated terrain, canopy photosynthesis and transpiration

rates; and to supplement MODIS studies of the biogeochemical cycle in the tropics by providing atmospherically corrected ocean color data.

Principal Investigator

David J. Diner

David J. Diner received a B.S. in Physics with honors

from the State University of New York at Stony Brook,

and an M.S. and Ph.D. in Planetary Science from the

California Institute of Technology. He joined the Jet

Propulsion Laboratory as a National Research Council

Resident Research Associate in 1978, and is currently an

Element Leader in the Earth and Space Sciences Division.

He has been involved in numerous NASA planetary and

Earth remote-sensing investigations, as Principal and CoInvestigator. He is a member of the American

Astronomical Society, Division for Planetary Sciences.

Co-Investigators

Thomas P. Ackerman - Pacific Northwest National

Laboratory

Carol J. Bruegge - Jet Propulsion Laboratory

James E. Conel - Jet Propulsion Laboratory

Roger Davies - University of Arizona

Siegfried Gerstl - Los Alamos National Laboratory

Howard R. Gordon - University of Miami

Ralph Kahn - Jet Propulsion Laboratory

John V. Martonchik - Jet Propulsion Laboratory

Jan-Peter Muller - University College London

Ranga Myneni - Boston University

Bernard Pinty - Joint Research Centre

Piers Sellers - NASA/Johnson Space Center

Michel Verstraete - Joint Research Centre

References

Diner, D.J., C.J. Bruegge, J.V. Martonchik, G.W.

Bothwell, E.D. Danielson, E.L. Floyd, V.G. Ford, L.E.

Hovland, K.L. Jones, and M.L. White, 1991: A Multiangle Imaging SpectroRadiometer for terrestrial remote

sensing from the Earth Observing System. Int. J. Imaging Systems and Technology, 3, 92-107.

Diner, D.J., J.C. Beckert, T.H. Reilly, C.J. Bruegge, J.E.

Conel, R. Kahn, J.V.Martonchik, T.P. Ackerman, R.

Davies, S.A.W. Gerstl, H.R. Gordon, J-P. Muller, R.

Myneni, P.J. Sellers, B. Pinty, and M.M. Verstraete, 1998:

Multi-angle Imaging SpectroRadiometer (MISR) description and experiment overview. IEEE Trans. Geosci. Remote Sens., 36, 1072-1087.

MISR Parameters

Nine CCD cameras fixed at nine viewing angles out to 70.5°

at the Earth’s surface, forward and aftward of nadir,

including nadir

Four spectral bands discriminated via filters bonded to the

CCDs

Global coverage in 9 days

Swath: 360 km viewed in common by all nine cameras

Spatial sampling: 275 m, 550 m, or 1.1 km, selectable inflight

Mass: 149 kg

Duty cycle: 50%

Power: 83 W (average), 131 W (peak)

Thermal control by: Passive cooling and active temperature

stabilization

Thermal operating range: 0-10° C

FOV: ±60° (along-track) × ±15° (cross-track)

Data rate: 3.3 Mbps (orbit average), 9.0 Mbps (peak)

Pointing requirements (spacecraft):

Control: 150 arcsec

Knowledge: 90 arcsec

Stability: 5 arcsec/1 sec; 14 arcsec/420 sec

Physical size: 0.9 m (W) × 0.9 m (H) × 1.3 m (L)
130 • EOS Instruments 1999 ESE Reference Handbook

MISR Data Products

Product Name

Level 1A Reformatted Annotated Product

Level 1B1 Radiometric Product

Level 1B2 Geo-rectified Radiance Product

Level 2 Top of Atmosphere/Cloud Product

Level 2 Aerosol/Surface Product

Level 3 Gridded Radiation Product

Level 3 Gridded Cloud Product

Level 3 Gridded Aerosol Product

Level 3 Gridded Surface Product

Level 1B2 Ancillary Geographic Product

Level 1B2 Ancillary Radiometric Product

Level 2 Aerosol Climatology Product

3% :: 1%

(@ equivalent reflectance of

1.0), 6% :: 2% (@0.05)

3% :: 1%

(@ equivalent reflectance of

1.0), 6% :: 2% (@0.05)

3% :: 1%

(@ equivalent reflectance of

1.0), 6% :: 2% (@0.05)

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Parameter Dependent

Accuracy

Absolute :: Relative

1/(2-9 day)

1/(2-9 day)

1/(2-9 day)

1/(2-9 day)

1/(2-9 day)

1/(9 day, 16 day,

month, season,

year)

1/(9 day, 16 day,

month, season,

year)

1/(9 day, 16 day,

month, season,

year)

1/month

Updated

infrequently

Updated 1/month

Updated

infrequently

Temporal

Resolution

Horizontal

Resolution :: Coverage

275 m-1.1 km :: Global;

275 m :: Regional

275 m-1.1 km :: Global;

275 m :: Regional

275 m-1.1 km :: Global;

275 m :: Regional

1.1, 2.2, 17.6, 35.2 km ::

Global

1.1, 17.6 :: Global

1.1, 2.2, 17.6, 35.2 km ::

Global

1.1, 2.2, 17.6, 35.2 km ::

Global

17.6 km :: Global

1.1 km :: Global

1.1 km :: Global

N/A :: N/A

N/A :: N/A

Vertical

Resolution :: Coverage

N/A :: Top of

Atmosphere

N/A :: Top of

Atmosphere

N/A :: Top of

Atmosphere

N/A :: Troposphere, Top

of Atmosphere

N/A :: Troposphere,

Surface

N/A :: Surface, Top of

Atmosphere

N/A :: Troposphere

N/A :: Troposphere

N/A :: Surface

N/A :: Surface

N/A :: N/A

N/A :: Atmosphere
1999 ESE Reference Handbook EOS Instruments • 131

Key MLS Facts

Selected for flight on EOS CHEM

Heritage: UARS MLS

Passive microwave limb-sounding radiometer/

spectrometer

Measures thermal emission from the atmospheric

limb

Spectral bands at millimeter and submillimeter

wavelengths

Provides reliable measurements even in presence

of cirrus and dense volcanic aerosols

In-house JPL development with subsystems from

industry

The scientific priorities and objectives of the MLS investigation

are to improve understanding of the following processes and parameters vital to global change research and environmental policy:

• Chemistry of the lower stratosphere and upper troposphere –

MLS measures lower stratospheric temperature and concentrations of H2O, O3, ClO, BrO, HCl, OH, HO2, HNO3, HCN,

and N2O, for their effects on (and diagnoses of) ozone depletion, transformations of greenhouse gases, and radiative forcing of climate change. These measurements will be especially

valuable for diagnosing the potential for severe loss of Arctic

ozone during the critical period following the turn of the century when abundances of stratospheric chlorine will still be

high, and slight cooling of the stratosphere could exacerbate

ozone loss due to chlorine chemistry. The measurements will

help determine whether the stratosphere is responding as expected to the effects of the Montreal Protocol agreements for

phasing out ozone-depleting substances. MLS also measures

upper tropospheric H2O, O3, CO, and HCN for their effects

on radiative forcing of climate change and for diagnoses of

exchange between the troposphere and stratosphere.

• Chemistry of the middle and upper stratosphere – MLS observes the details of ozone chemistry by measuring many radicals, reservoirs, and source gases in chemical cycles which

destroy ozone. This set of measurements will provide stringent tests on understanding of global stratospheric chemistry,

will help explain observed trends in ozone, and can provide

early warnings of any changes in the chemistry of this region.

• Water in the upper troposphere – the Upper Atmosphere Research Satellite (UARS) has demonstrated the MLS capability of measuring upper tropospheric water vapor profiles,

knowledge of which is essential for understanding climate variability and global warming but which previously has been extremely difficult to observe reliably on a global scale. MLS is

unique in its ability to provide these measurements in the presence of dense tropical cirrus, where important processes affecting climate variability occur. MLS also provides unique

measurements of cirrus ice content. The simultaneous MLS

measurements of upper tropospheric water vapor, ice content,

and temperature, under all conditions and with good vertical

resolution, will be of great value for improving our understanding of processes (such as El Niño) affecting the distribution of atmospheric water, climate variability, and troposphericstratospheric exchange. The simultaneous measurements of

dynamical tracers CO and N2O enhance the value of this data

set by helping identify source regions of the air masses being

observed.

MLSMicrowave Limb Sounder

MLS URL

http://mls.jpl.nasa.gov
132 • EOS Instruments 1999 ESE Reference Handbook

• The effect of volcanoes on global change – MLS measures SO2, and other gases mentioned above, in volcanic plumes to investigate the effects of volcanic injections into the atmosphere.

EOS MLS objectives address three priority science areas of the U.S. Global Change Research Program:

1. Changes in ozone, UV radiation, and atmospheric

chemistry;

2. decade-to-century climate change; and

3. seasonal-to-interannual climate variability.

EOS MLS continues the successful effort started on

UARS MLS, and uses advanced technology to provide

important new measurements. Particularly noteworthy in

this regard are its capabilities for OH, HO2, and BrO;

measurements of these species have never before been

possible on a global scale, but are essential for a comprehensive understanding of stratospheric chemistry. The

instrument observes in spectral bands centered near the

following frequencies:

• 118 GHz, primarily for temperature and pressure;

• 190 GHz, primarily for H2O, HNO3, and continuity

with UARS MLS measurements;

• 240 GHz, primarily for O3 and CO;

• 640 GHz, primarily for N2O, HCl, ClO, HOCl, BrO,

HO2, and SO2; and

• 2.5 THz, primarily for OH.

Principal Investigator

Joe W. Waters

Dr. Waters has led the development of microwave limb

sounding since its inception in 1974. His Ph.D. from MIT

focused on microwave sensing of the upper atmosphere.

He has been at JPL since 1973, where he is currently a

senior research scientist and leader of Microwave Atmospheric Science and Upper Atmosphere Microwave Experiment Development groups. Dr. Waters is author of

more than 100 peer-reviewed scientific publications, most

of which are on atmospheric measurements with microwave techniques, and has twice received the NASA Medal

for Exceptional Scientific Achievement.

Co-Investigators

The following are from the University of Edinburgh:

Mark J. Filipiak

Robert S. Harwood

Hugh C. Pumphrey

The following are from the Jet Propulsion Laboratory:

Richard E. Cofield

Lucien Froidevaux

Robert F. Jarnot

Nathaniel J. Livesey

Herbert M. Pickett

William G. Read

Michelle L. Santee

Peter H. Siegel

Dong L. Wu

References

Froidevaux, L., et al., 1996: Validation of UARS Microwave Limb Sounder ozone measurements. J. Geophys.

Res., 101, 10,017-10,060.

Jarnot, R.F., et al., 1996: Calibration of the Microwave

Limb Sounder on the Upper Atmosphere Research Satellite. J. Geophys. Res., 101, 9957-9982.

Manney, G.L., et al., 1994: Chemical depletion of ozone

in the Arctic Lower Stratosphere during winter 1992-

1993. Nature, 370, 429-434.

MLS Parameters

Spectral bands: At millimeter and submillimeter

wavelengths.

Spatial resolution: Measurements are performed along

the suborbital track, and resolution varies for different

parameters; 5 km cross-track × 500 km along-track × 3

km vertical are typical values.

Mass: 430 kg

Duty cycle: 100%

Power: 530 W full-on; 460 W time-shared

Data rate: 100 kbps

Thermal control: Via radiators and louvers to space as well

as heaters

Thermal operating range: 10 to 35° C

FOV: Boresight 60-70° relative to nadir

Instantaneous field-of-view at 640 GHz: 1.5 km vertical ×

3 km cross-track × 300 km along-track at the limb

tangent point

Pointing requirements (platform+instrument, 3 σ):

Control: 36 arcsec

Knowledge: 1 arcsec per second

Stability: 72 arcsec per 30 seconds

Jitter: 2.7 arcsec per 1/6 second

Size: 1.5 × 1.9 × 1.8 m (GHz sensor);

0.8 × 1 × 1.1 m (THz sensor);

1.6 × 0.5 × 0.3 m (spectrometer)
1999 ESE Reference Handbook EOS Instruments • 133

MLS Data Products

MLS radiances

temperature

geopotential height

cirrus ice content

H2O concentration

N2

O concentration

CO concentration

O3

 conc. (strat)

O3

 conc. (trop)

OH conc. (lower strat)

OH conc. (upper strat)

HO2 concentration

BrO concentration

ClO concentration

HCl concentration

HOCl concentration

HNO3 concentration

HCN concentration

SO2 concentration

absolute accuracy is 2K or better; precision varies,

with ~0.01K achieved on long-term averages

1-2K :: 0.3-1K (5-40 km)

30-100 m :: 10-30 m (10-50 km)

5-10% :: 0.005 g/m3

3-5% :: 2-10% (5-50 km)

3-5% :: 0.02-0.05 ppmv (10-45 km)

3-5% :: 8-20 ppbv (8-30 km)

3 -5% :: 0.5-10% (15-50 km)

3 -5% :: 2-10 ppbv (8-15 km)

3-10% :: 0.2-0.5 pptv (18-35 km)

3-10% :: ~10% (35-60 km)

3-10% :: 5-50 pptv (20-50 km)

3-10% :: 3-6 pptv (20-40 km)

3-5% :: 0.1-0.5 ppbv (15-45 km)

3-5% :: 0.06-1 ppbv (10-55 km)

3-10% :: 0.01-0.1 ppbv (20-50 km)

3-5% :: 2-5 ppbv (10-30 km)

3-10% :: 0.05-0.2 ppbv (8-40 km)

3-10% :: 2 ppbv (10-40 km)

2/day (d,n)

daily global map

daily global map

monthly global map

daily global map

daily global map

monthly global map

daily global map

monthly global map

monthly zonal mean

daily global map

monthly zonal mean

monthly zonal mean

daily global map

daily global map

monthly zonal mean

daily global map

daily zonal mean

daily global map

500 km :: global

500 km :: global

500 km :: global

200 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

500 km :: global

0.1-1 km :: 0-120 km

3 km :: 5-120 km

3 km :: 5-120 km

3 km :: 10-20 km

3 km :: 5-100 km

3 km :: 10-60 km

3 km :: 8-100 km

3 km :: 15-100 km

3 km :: 8-15 km

3 km :: 18-30 km

3 km :: 30-80 km

3 km :: 20-60 km

5 km :: 20-40 km

3 km :: 15-60 km

3 km :: 10-100 km

3 km :: 20-50 km

3 km :: 10-60 km

5 km :: 8-50 km

3 km :: 10-40 km

Product Name Accuracy

Absolute :: Relative

Temporal

Resolution

Horizontal

Resolution :: Coverage

Vertical

Resolution :: Coverage

NOTE: MLS measurements are made only along suborbital track. A vertical profile is obtained every 1.5 degrees great circle (165 km) along the track, and data products above are retrieved routinely with standard data processing

software and archived with this full resolution. The resolutions and accuracies given here are for the products produced from these data which are likely to have the most widespread scientific use. Global maps have approximately

5 degrees latitude resolution and 10-20 degrees longitude resolution at mid-latitudes. There are trade-offs between resolution and precision: useful upper tropospheric water vapor measurements, for example, are expected to be

obtained with approximately 1-km vertical resolution, and ClO monthly zonal means will have approximately 0.01 pppv precision. Values for accuracy and precision given here are current estimates and may be refined with further

study. The height ranges in parentheses in column two are those over which the precisions stated there apply and are the primary height range of interest; measurements are, however, obtained over the full vertical range stated

in the righthand column. Some time-sharing of MLS measurements may be required because of spacecraft power limitations. The SO2 maps will likely be useful only after volcanic eruptions.

Morrey, M.W., and R.S. Harwood, 1998: Interhemispheric differences in stratospheric water vapour during

late winter, in version 4 MLS measurements. Geophys.

Res. Lett., 25, 147-150.

Newell, R.E., et al., 1997: Relationship between tropical

upper tropospheric moisture and eastern tropical Pacific

sea surface temperature. Geophys. Res. Lett., 24, 25-28.

Pumphrey, H.C., 1998: Nonlinear retrievals of water

vapour from the UARS Microwave Limb Sounder

(MLS). Adv. Space Res., 21, 389-392.

Read, W.G., et al., 1993: Microwave Limb Sounder

(MLS) measurements of SO2 from Mt. Pinatubo volcano.

Geophys. Res. Lett., 20, 1299-1302.

Read, W.G., et al., 1995: Upper tropospheric water vapor from UARS MLS. Bull. Amer. Met. Soc., 76, 2381-

2389.

Sandor, B.J., et al., 1998: Seasonal behavior of tropical

to mid-latitude upper tropospheric water vapor from

UARS MLS. J. Geophys. Res., 103, 25,935-25,947.

Santee, M.L., et al., 1995: Interhemispheric differences

in HNO3, H2O, ClO and O3. Science, 267, 849-852.

Waters, J.W., et al., 1993: Stratospheric ClO and Ozone

from the Microwave Limb Sounder on the Upper Atmosphere Research Satellite. Nature, 362, 597-602.

Waters, J.W., et al., 1999: The UARS and EOS Microwave Limb Sounder (MLS) Experiments. J. Atmos.Sci.,

56, 194-218.

Wu, D.L., 1998: Equatorial diurnal Variations observed

in UARS MLS temperature during 1991-1994 and simulated by the Canadian Middle Atmosphere Model. J.

Geophys. Res., 103, 8909-8917.
134 • EOS Instruments 1999 ESE Reference Handbook

Key MODIS Facts

Selected for flight on Terra and EOS PM

Heritage: AVHRR, HIRS, LANDSAT TM, and

Nimbus-7 CZCS

Medium-resolution, multi-spectral, cross-track

scanning radiometer

Measures biological and physical processes

Launch in 1999

Prime Contractor: Raytheon Santa Barbara Remote

Sensing

Responsible Center: NASA/Goddard Space Flight

Center

MODIS is an EOS facility instrument designed to measure biological and physical processes on a global basis every 1-to-2 days.

Slated for both the Terra and EOS PM satellites, the instrument

will provide long-term observations from which an enhanced

knowledge of global dynamics and processes occurring on the

surface of the Earth and in the lower atmosphere can be derived.

This multidisciplinary instrument will yield simultaneous, congruent observations of high-priority atmospheric (aerosol and

cloud properties, water vapor and temperature profiles), oceanic

(sea-surface temperature and chlorophyll), and land-surface features (land-cover changes, land-surface temperature, snow cover,

and vegetation properties). The instrument is expected to make

major contributions to understanding the global Earth system,

including interactions among land, ocean, and atmospheric processes.

The MODIS instrument employs a conventional imaging

spectroradiometer concept, consisting of a cross-track scan mirror and collecting optics, and a set of linear arrays with spectral

interference filters located in four focal planes. The optical arrangement will provide imagery in 36 discrete bands between

0.4 and 14.5 μm selected for diagnostic significance in Earth science. The spectral bands will have spatial resolutions of 250, 500,

or 1,000 m at nadir. Signal-to-noise ratios are greater than 500 at

1-km resolution (at a solar zenith angle of 70 ̊), and absolute irradiance accuracies are < ±5% from 0.4 to 3 μm (2% relative to the

sun) and 1 percent or better in the thermal infrared (3.7 to 14.5

μm). MODIS instruments will provide daylight reflection and

day/night emission spectral imaging of any point on the Earth at

least every 2 days, operating continuously. MODIS will provide

specific global data products, which include the following:

• Surface temperature with 1-km resolution, day and night, with

absolute accuracy of 0.3 K-0.5 K for oceans and 1 K for

land;

• water-leaving radiance to within 0.2 percent from 415 to

653 nm;

• chlorophyll fluorescence within 50 percent at surface concentrations of 0.5 mg m-3

;

• concentration of chlorophyll-a within 35 percent, net ocean

primary productivity, other optical properties;

• vegetation/land-surface cover, conditions, and productivity:

- Net primary productivity, leaf area index, and intercepted

photosynthetically active radiation

MODISModerate-Resolution Imaging Spectroradiometer

MODIS URL

http://ltpwww.gsfc.nasa.gov/MODIS/MODIS.html
1999 ESE Reference Handbook EOS Instruments • 135

- land cover type, with change detection and

identification;

- vegetation indices corrected for atmosphere,

soil, and directional effects; and

- snow cover and reflectance;

• cloud mask containing confidence of clear sky (or,

alternatively, the probability of cloud), shadow, fire,

and heavy aerosol at 1-km resolution;

• cloud properties characterized by cloud phase, optical thickness, droplet size, cloud-top pressure, and

temperature;

• aerosol properties defined as optical thickness, particle size, and mass loading;

• fire occurrence, temperature, and burn scars;

• global distribution of total precipitable water; and

• cirrus cloud cover

MODIS will fly on both the Terra and EOS PM satellites to maximize cloud-free remote sensing of the

Earth’s surface and to exploit synergism with other EOS

sensors.

Team Leader

Vincent V. Salomonson

Dr. Salomonson brings substantial experience to his role

as Team Leader of MODIS. He has functioned as the

MODIS Team Leader for the past 11 years. He also served

for 12 years as the Landsat 4 and 5 Project Scientist, including leadership and management of the Landsat Image Data Quality and Analysis (LIDQA) Investigator

Team and Thematic Mapper Research in the Earth Sciences Investigator Team. Additional experience includes

over 25 years as a line manager of research groups at

Goddard Space Flight Center and leadership of the NASA

Water Resources Subdiscipline Panel and Program for

several years in the 1970s. He has published research

materials directly relevant to the investigation, and has

over 120 refereed publications, conference proceedings,

and NASA reports to his credit.

Cited on numerous occasions for his outstanding research and scientific achievement, Dr. Salomonson is the

recipient of several NASA awards for exceptional scientific achievement, service, and performance; the Distinguished Achievement Award of the IEEE Geoscience and

Remote Sensing Society; the William T. Pecora Award;

and the Distinguished Alumnus Award from Colorado

State University. In addition to his present duties as Director of Earth Sciences at Goddard, he served as President of the American Society for Photogrammetry and

Remote Sensing (ASPRS) in 1992. He was made a Fellow of ASPRS in 1994, and was elected a Fellow of IEEE

in 1998.

Science Team Members

Mark R. Abbott - Oregon State University

William L. Barnes - NASA/Goddard Space Flight

Center

Ian Barton - Commonwealth Scientific and Industrial

Research Organization, Australia

Otis B. Brown - University of Miami

Janet W. Campbell - University of New Hampshire

Kendall L. Carder - University of South Florida

Dennis K. Clark - NOAA/National Environmental

Satellite, Data, and Information Service

Wayne Esaias - NASA/Goddard Space Flight Center

Robert H. Evans - University of Miami

Bo-Cai Gao - Naval Research Laboratory

Howard R. Gordon - University of Miami

Frank E. Hoge - Wallops Flight Facility

Alfredo R. Huete - University of Arizona

Christopher O. Justice - University of Virginia

Yoram J. Kaufman - NASA/Goddard Space Flight

Center

Michael D. King - NASA/Goddard Space Flight Center

W. Paul Menzel - NOAA/NESDIS, University of

Wisconsin-Madison

Jan-Peter Muller - University College London

Ranga B. Myneni - Boston University

John Parslow - Commonwealth Scientific and Industrial Research Organization, Australia

Steven W. Running - University of Montana

Kurtis Thome - University of Arizona

Alan H. Strahler - Boston University

Didier Tanré - Centre National d’Etudes Spatiales/

Laboratoire d’Optique Atmosphérique, France
136 • EOS Instruments 1999 ESE Reference Handbook

John R.G. Townshend - University of Maryland

Eric Vermote - University of Maryland

Zhengming Wan - University of California-Santa

Barbara

References

Barnes, W.L., T.S. Pagano, and V. Salomonson, 1998:

Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS AM-1. IEEE

Trans. Geosci. Remote Sens., 36, 1088-1100.

Esaias, W., M. Abbott, O. Brown, J. Campbell, K. Carder,

D. Clark, R. Evans, F. Hoge, H. Gordon, W. Balch, R.

Letelier, and P. Minnett: 1998: An overview of MODIS

capabilities for ocean science observations. IEEE Trans.

Geosci. Remote Sens., 36, 1250-1265.

Guenther, B., G.D. Godden, X. Xiong, E.J. Knight, S.

Qiu, H. Montgomery, M.M. Hopkins, M.G. Khayat, and

Z. Hao, 1998: Pre-launch algorithm and data format for

the Level 1 calibration products for the EOS AM-1 Moderate Resolution Imaging Spectroradiometer (MODIS).

IEEE Trans. Geosci. Remote Sens., 36, 1142.

Justice, C., E. Vermote, J. Townshend, R. Defries, D. Roy,

D. Hall, V. Salomonson, J. Privette, G. Riggs, A. Strahler,

W. Lucht, R. Myneni, Y. Knjazihhin, S. Running, R.

Nemani, Z. Wan, A. Huete, W. van Leeuwen, R. Wolfe,

L. Giglio, J. Muller, P. Lewis, and M. Barnsley, 1998:

The Moderate Resolution Imaging Spectroradiometer

(MODIS): Land remote sensing for global change research. IEEE Trans. Geosci. Remote Sens., 36, 1228-1249.

King, M.D., Y. Kaufman, W. Menzel, and D. Tanré, 1992:,

Remote sensing of cloud, aerosol, and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS). IEEE Trans. Geosci. Remote Sens., 30, 2-

27.

Masuoka, E., A. Fleig, R. Wolfe, and F. Patt, 1998: Key

characteristics of MODIS data products. IEEE Trans.

Geosci. Remote Sens., 36, 1313-1323.

36 spectral bands–21 within 0.4-3.0 μm; 15 within

3-14.5 μm

Continuous global coverage every 1 to 2 days

Polarization sensitivity: 2% from 0.43 μm to 2.2 μm and

±45 ̊ scan

Signal-to-noise ratios from 900 to 1300 for 1-km ocean

color bands at 70 ̊ solar zenith angle

NEDT’s typically <0.05 K at 300 K

Absolute irradiance accuracy of 5% for <3 μm and 1% for

>3 μm

Daylight reflection and day/night emission spectral

imaging

Swath: 2,300 km at 110 ̊ (±55 ̊) from 705-km altitude

Mass: 229 kg

Duty cycle: 100%

Power: 162.5 W (average), 225 W (peak)

Data rate: 6.2 Mbps (average), 10.5 Mbps (day), 3.2

Mbps (night)

Thermal control by: Radiators

Thermal operating range: 268 K ± 5 K

Instrument IFOV: 250 m (2 bands), 500 m (5 bands),

1,000 m (29 bands)

Pointing requirements (platform+instrument, 3 σ):

Control: 3,600 arcsec

Knowledge: 141 arcsec

Stability: 28 arcsec/sec

Jitter: 1,031 arcsec/sec (yaw and roll), 47

arcsec/sec (pitch)

Physical size: 1.044 × 1.184 × 1.638 m

MODIS Parameters
1999 ESE Reference Handbook EOS Instruments • 137

Product Name Accuracy

Absolute :: Relative

Temporal

Resolution

Horizontal

Resolution :: Coverage

Vertical

Resolution :: Coverage

MODIS Data Products

N/A

N/A :: N/A

N/A :: Atmosphere

N/A :: Cloud

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A :: Surface

N/A

N/A :: Surface

N/A :: Surface

N/A :: Surface, Atmosphere

N/A :: Surface

N/A :: Cloud

0.25, 0.5, 1 km :: Global

0.25, 0.5, 1 km :: Global

10 km

1 km :: Global

0.25, 0.5, 1 km :: Land

1 km :: Land

1 km :: Land/Regional

1 km :: Land

1 km :: Ocean Regional,

Local

1, 5 km :: Ocean

1 km :: Local

1 km :: Ocean/Global

1 km :: Ocean/Local

0.25, 1 km :: Global

1 - 2/day*

1 - 2/day*

1/day

1/day

1 - 9/day

1/day

1/day, 1/week, 1/month

1/(3 months)

1/day, 1/week, 1/month

1/day, 1/week, 1/month

1/day, 1/week, 1/month

1/day

1/day, 1/week, 1/month

1 - 2/day

*Thermal bands 2/day; VIS/NIR/SWIR bands 1/day.

N/A

5% (1σ) ::

<0.05

2 - 5 K ::

10% ::

0.03 ::

<10% ::

1 K ::

0.02 ::

N/A

35%

0.017 W m-2 sr-1 μm-1 at 1 km

0.002 ::

5 - 10% ::

0.3 - 0.5 K ::

N/A

Level -1A Radiance

Level-1B Radiance, Calibrated Geolocated

Aerosol Product

Cloud Product

—Cloud Top Temperature

—Optical Thickness & Effective Radius

Surface Reflectance

Snow Cover

Land-surface

Temperature/

Emissivity

Land-cover Type

Chlorophyll-a Pigment Concentration

Chlorophyll Fluorescence

Water-leaving Radiance

Instantaneous PAR

Sea Surface Temperature (SST)

Cloud Mask
138 • EOS Instruments 1999 ESE Reference Handbook

Key MOPITT Facts

Selected for flight on Terra

Heritage: Pressure-modulated cell elements used

in the PMR, SAMS, and ISAMS instruments,

using similar correlation spectroscopy

techniques

Four-channel correlation spectrometer with crosstrack scanning

Flight on EOS AM-2 to be confirmed

Canadian Space Agency to provide the instrument

Prime Contractor: COM DEV

The MOPITT experiment is provided under a Memorandum of

Understanding with the Canadian Space Agency (CSA). MOPITT

will measure emitted and reflected infrared radiance in the atmospheric column which, when analyzed, permits retrieval of tropospheric CO profiles and total column CH4.

Both CO and CH4 are produced by biomass systems, oceans,

and human activities. CO is intimately connected with the OH

chemical cycle in the troposphere, and moves both vertically and

horizontally within the troposphere. CH4 is a greenhouse gas and

is increasing on an annual basis. MOPITT measurements will allow studies of the global and temporal distributions that drive

budget and source/sink studies. Since human activities have a significant influence on both CO and CH4 concentrations, a better

understanding of the role of these constituents is essential in understanding anthropogenic effects on the environment.

MOPITT operates on the principle of correlation spectroscopy, i.e., spectral selection of radiation emission or absorption

by a gas, using a sample of the same gas as a filter. The instrument

modulates sample gas density by changing the length or the pressure of the gas sample in the optical path of the instrument. This

modulation changes the absorption profile in the spectral lines of

the gas in the cell as observed by a detector. The modulated gas

sample acts as an optical filter which selectively picks out the

parts of the atmospheric absorption lines of that gas in the atmosphere. The detector thus observes a signal highly correlated with

the abundance of the sample gas in the atmosphere.

Atmospheric sounding and column CO are mapped by using

thermal and reflected solar channels in the regions of 4.7 and 2.3

μm, respectively. Column CO and CH4 are measured using solar

channels viewed through modulation cells to sense solar radiation reflected from the surface. The solar channels are duplicated

in the instrument at different correlation cell pressures, to allow a

failure in one channel without compromising the column measurement.

MOPITT is designed as a scanning instrument. The field of 4

pixels, aligned along the direction of motion, and each 1.8 degrees (or 22 km) on a side, is scanned through a cross-track scan

angle of 26.1 degrees, or 29 pixels, to give a swath width of 640

km. This swath leaves gaps in coverage between successive orbits using the nominal 705-km altitude and 98.2° inclination orbit.

MOPITT data products will include total column retrievals

of CH4 with a horizontal resolution of 22 km and a precision of 1

percent. CO soundings will be retrieved with 10% accuracy provided by three independent pieces of information, and represented

by values on 7 pressure levels between 0 and 14 km. These soundings will be taken at laterally scanned sampled locations with 22-

km horizontal resolution. Column CO abundance will be retrieved

MOPITT Measurements Of Pollution In The Troposphere

MOPITT URL

University of Toronto:

http://www.atmosp.physics.utoronto.ca/MOPITT/

home.html
1999 ESE Reference Handbook EOS Instruments • 139

Correlation spectroscopy utilizing both pressure- and lengthmodulated gas cells, with detectors at 2.3, 2.4, and

4.7 μm

Uses pressure modulation and length modulation to obtain

CO concentrations with three independent pieces of

information represented by values on seven pressure

levels, as well as CO and CH4 columns

CO concentration accuracy is 10%

CH4 column abundance accuracy is 1%

Swath: 640 km (29 fields of view)

Spatial resolution (each pixel): 22 × 22 km

Mass: 192 kg

Power: 250 W (average), 260 W (peak)

Duty cycle: 100%

Data rate: 28 kbps

Thermal control by: 80 K Stirling cycle cooler, capillary

pumped coldplate and passive radiation

Thermal operating range: 25° C (instrument), 100 K

(detectors)

Instrument IFOV: 22 km across track × 88 km along track

(1.8° × 7.2° - 4 pixels)

Pointing requirements (platform+instrument, 3 σ):

Control: 500 arcsec

Knowledge: 300 arcsec

Stability: 322 arcsec/12.47 sec

Physical size: 115 × 93 × 57 cm (stowed),

 115 × 105 × 71 cm (deployed)

with 22-km horizontal resolution. Scientific studies will

employ these data to derive three-dimensional global

maps as part of an effort to model global tropospheric

chemistry.

Principal Investigator

James Drummond

James Drummond studied at Oxford University where

he obtained his B.A and D.Phil. degrees in Physics. He

has taught in the Physics Department at the University

of Toronto since 1979, as a Full Professor since 1992,

and as a holder of an Industrial Research Chair in Atmospheric Remote Sounding from Space since 1996.

His major research interests are in the field of atmospheric remote-sounding measurements, modeling and

molecular spectroscopy. He has participated in many

balloon, aircraft, and spacecraft experiments over nearly

30 years of his career, and is currently involved in several such programs as well as running an extensive laboratory program in line-shape measurements and instrument development.

Co-Investigators

Guy Brasseur - National Center for Atmospheric

Research

G.R. Davis - University of Saskatchewan, Canada

John C. Gille - National Center for Atmospheric

Research

Gurpreet S. Mand - University of Toronto

Jack McConnell - York University, Canada

Guy Peskett - Oxford University, United Kingdom

Henry G. Reichle - North Carolina State University

N. Roulet - McGill University, Canada

References

Drummond., J.R., 1992: Measurements of Pollution in

the Troposphere (MOPITT). The Use of EOS for Studies of Atmospheric Physics, J. Gille and G. Visconti, Eds.,

North Holland, 77-101.

Drummond, J.R., and G.S. Mand, 1996: The Measurements of Pollution in the Troposphere (MOPITT) instrument: Overall performance and calibration requirements.

J. Atmos. Ocean. Tech., 13, 314-320.

MOPITT Parameters

Pan, L., D. Edwards, J.C. Gille, M.W. Smith, and J.R.

Drummond, 1995: Satellite remote sensing of tropospheric CO and CH4. Appl. Opt., 34, 6976.

Pan, L., J.C. Gille, D.P. Edwards, P.L. Bailey, and C.D.

Rodgers, 1998: Retrieval of tropospheric carbon monoxide for the MOPITT experiment. J. Geophys. Res., 103,

32,277-32,290.

Wang, J., J. Gille, P.L. Bailey, J.R. Drummond, and L.

Pan, 1999: Instrument sensitivity and error analysis for

the remote sensing of tropospheric carbon monoxide by

MOPITT. J. Atmos. Ocean. Tech., 16, 465-474.
140 • EOS Instruments 1999 ESE Reference Handbook

MOPITT Data Products

Product Name

Level-1B Radiance

(= Ancillary Data

including CR pressure)

CH4 Column

(Total Burden)

CO Profiles

CO Column

(Total Burden)

1% :: 1%*

10% :: 10%

10% :: 10%

Accuracy

Absolute :: Relative

1 view/0.4 seconds

1 view/0.4 seconds

1 view/0.4 seconds

1 view/0.4 seconds

Temporal

Resolution

Horizontal

Resolution :: Coverage

22 km :: Global

22 km :: Global

22 km :: Global

22 km :: Global

Vertical

Resolution :: Coverage

:: Atmosphere

Column :: Atmosphere

4 km :: 0 - 15 km

Column :: Atmosphere

* Limited by knowledge of spectroscopic parameters; requires post-launch verification
1999 ESE Reference Handbook EOS Instruments • 141

OMI is a contribution of the Netherland’s agency for aerospace

programs (NIVR) in collaboration with Finland to the EOS CHEM

mission. It will continue the TOMS record for total ozone and

other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other

instruments on the EOS CHEM platform. The OMI instrument

employs hyperspectral imaging in a push-broom mode to observe

solar backscatter radiation in the visible and ultraviolet. The Earth

will be viewed in 740 wavelength bands along the satellite track

with a swath large enough to provide global coverage in 14 orbits

(1 day). The nominal 13 × 24 km spatial resolution can be zoomed

to 13 × 13 km for detecting and tracking urban-scale pollution

sources. The hyperspectral capabilities will improve the accuracy

and precision of the total ozone amounts. The hyperspectral capabilities will also allow for accurate radiometric and wavelength

self calibration over the long term. The expanded wavelength characteristics will provide the following features.

• Continue global total ozone trends from satellite measurements beginning in 1970 with BUV on Nimbus-4.

• Map ozone profiles at 36 × 48 km, a spatial resolution never

achieved before.

• Measure key air quality components such as NO2, SO2, BrO,

OCLO, and aerosol characteristics.

• Distinguish between aerosol types, such as smoke, dust, and

sulfates.

• Measure cloud pressure and coverage, which provide data to

derive tropospheric ozone.

• Map global distribution and trends in UV-B radiation.

• A combination of algorithms including TOMS version 7, Differential Optical Absorption Spectroscopy (DOAS),

Hyperspectral BUV Retrievals and forward modeling will be

used together to extract the various OMI data products.

Science Team

The OMI international science team will be led by the principal

investigator from the Netherlands, in collaboration with the coinvestigator and science team leader from Finland and the United

States. The team will have the responsibility for developing algorithms, calibration, data processing, validation, and analysis. The

international team draws experience from TOMS, SBUV, GOME

on ERS-2, SCIAMACHY and GOMOS flying on Envisat.

OMIOzone Monitoring Instrument

A Netherlands contribution to EOS CHEM in

collaboration with Finland

Heritage: TOMS, SBUV, GOME, SCIAMACHY,

GOMOS

Nadir-viewing wide-field-imaging spectrometer

Daily global coverage

Continues TOMS data record for total ozone,

aerosols, UVB, and SO2

Enhanced mapping capability for ozone profiles,

NO2, BrO, and OClO columns, cloud pressure

and coverage

13 km × 24 km nominal IFOV

Capable of mapping pollution products on

urban-to-super-regional scales.

Prime Contractor: Fokker Space (Netherlands)

Contributing Contractors: TNO-TPD (Netherlands), Patria Finavitec (Finland), VTT

(Finland)

Key OMI Facts
142 • EOS Instruments 1999 ESE Reference Handbook

Product Name

Radiances

Total Ozone

Ozone Profile

UV-B

Aerosol Index

Aerosol Optical

Thickness

Cloud Height (and coverage)

SO2

NO2

BrO

OCLO

Accuracy

Absolute::Relative

<5% :: <1%

5% :: 2%

15% :: 8%

10% :: 10%

0.1 (0-5)

TBD

30 mb :: 0-15 km

20% :: 10%

TBD

TBD

TBD

Temporal

 Resolution

1 view/2 sec

1 view/2 sec

1 view/4 sec

1 view/2 sec

1 view/2 sec

1 view/2 sec

1 view/2 sec

1 view/4 sec

TBD

TBD

TBD

Horizontal

Resolution::Coverage

13 × 24 km :: Global, daylight

13 × 24 km :: Global, daylight

36 × 48 km :: Global, daylight

13 × 24 km :: Global, daylight

13 × 24 km :: Global, daylight

13 × 24 km :: Global, daylight

13 × 24 km :: Global, daylight

TBD

TBD

TBD

TBD

Vertical

Resolution::coverage

N/A

Column

8 km :: 0-60 km

N/A

N/A

N/A

1 km

Column

Column

Column

Column

Data products are preliminary pending approval of the OMI Science Team and peer review.

OMI Data Products

The instrument observes Earth’s backscattered radiation with a

wide-field telescope feeding two imaging grating

spectrometers, with each spectrometer employing a CCD

detector

Onboard calibration includes a white light source, LEDs, and

a multi-surface solar-calibration diffuser; a depolarizer

removes the polarization from the backscattered radiation

Wavelength

Visible: 350 to 500 nm

UV: UV-1, 270 to 314 nm, UV-2 306 to 380 nm

Spectral resolution: 1.0-0.45 nm FWHM

Spectral sampling: 2-3 for FWHM

Telescope FOV: 114o (2600 km on ground)

IFOV: 3 km, binned to 13 × 24 km

Detector: CCD: 780 × 576 (spectral × spatial) pixels

Mass: 65 kg

Power: 66 W

Data rate: 0.8 Mps (average)

Duty cycle: 60 minutes on daylight side

Pointing requirements (arcseconds)

(Platform+instrument, pitch:roll:yaw, 3 σ):

Accuracy: 866:866:866

Knowledge: 87:87:87

Stability (6 sec): 87:87:87

Physical Size: 50 × 40 × 35 cm

OMI Parameters Principal Investigator

Pieternel Levelt

Pieternel Levelt is with the Royal Dutch Meteorological

Institute’s (KNMI) Atmospheric Composition section,

which has a research program that includes an analysis of

ground based and satellite data and chemical-transport

models. Dr. Levelt has conducted research on the use of

ozone data in data assimilation models and has participated

in GOME data validation and the planning for

SCIAMACHY validation.

Co-Investigator

Gilbert W. Leppelmeier

Gilbert W. Leppelmeier is Research Professor at Finnish

Meteorological Institute’s (FMI) Geophysical Research

center. FMI has overall responsibility for weather and climate, air quality, and geophysics in Finland. The center

conducts planetary, geomagnetic, aeronomic, and space

plasma physics research. The Geophysical Research center develops sensor technology for interplanetary missions.

Dr. Leppelmeier is also a co-investigator on the GOMOS

instrument.

U.S. Science Team

The U.S. Science Team consists of the EOS CHEM Project

Scientist and team members who will be selected through

a NASA Research Announcement in 1999. The team leader

will be responsible for developing the EOSDIS TOMSbased standard data products with enhancements employing OMI’s hyperspectral capabilities. The team leader will

also be responsible for integrating algorithms for producing other OMI data products for archiving in the DAAC.
1999 ESE Reference Handbook EOS Instruments • 143

SAGE III Stratospheric Aerosol and Gas Experiment III

Key SAGE III Facts

Selected for flight on Russian Meteor 3M and

International Space Station

Heritage: SAM II, SAGE I and SAGE II

Earth limb-scanning grating spectroradiometer

Phase C/D start November 1994

First flight aboard Meteor 3M in 1999

Prime Contractor: Ball Aerospace

Responsible Center: NASA/Langley Research Center

SAGE III is an improved extension of the successful Stratospheric

Aerosol Measurement II (SAM II), SAGE I, and SAGE II experiments. The additional wavelengths and operation during both lunar and solar occultation that SAGE III provides will improve

aerosol characterization; improve the gaseous retrievals of O3, H2O,

and NO2; add retrievals of temperature, pressure, NO3 and OClO;

extend the vertical range of measurements; provide a self-calibrating instrument independent of any external data needed for

retrieval; and expand the sampling coverage. The science objectives are:

• Retrieve global profiles (with 1-to-2-km vertical resolution)

of atmospheric aerosols, O3, H2O, NO2, NO3, OClO, temperature, and pressure in the mesosphere, stratosphere, and

troposphere

• Investigate the spatial and temporal variability of the measured species in order to determine their role in climatological processes, biogeochemical cycles, the hydrologic cycle,

and atmospheric chemistry

• Characterize tropospheric and stratospheric aerosols and upper tropospheric and stratospheric clouds, and investigate their

effects on the Earth’s environment, including radiative, microphysical, and chemical interactions

• Extend the SAM II, SAGE I, and SAGE II self-calibrating

solar-occultation data sets (begun in 1978), enabling the detection of long-term trends

• Provide atmospheric data essential for the calibration and interpretation/correction of other satellite sensors, including

EOS- and ground-based sensors.

SAGE III takes advantage of both solar and lunar occultations to measure aerosol and gaseous constituents of the atmosphere. Most of the objectives rely on the solar-occultation technique, which involves measuring the effects of extinction of solar

energy by aerosol and gaseous constituents in the spectral region

from 0.29 to 1.55 μm during spacecraft sunrise and sunset events.

For example, during a sunset event, exoatmospheric solar limb

data are obtained when the sun-satellite vector is high above the

Earth’s atmosphere. As the sun sets, a series of scans through the

atmosphere is performed during which measurements of the solar

transmission through the atmosphere are made. Because all atmospheric measurements are ratioed to the exoatmospheric solar limb

profiles taken during the same event, the instrument is nearly selfcalibrating, and the retrieved data are not susceptible to long-term

instrument degradation.
144 • EOS Instruments 1999 ESE Reference Handbook

The moon will be used as another source of light for

occultation measurements. In the spectral region from

0.4 to 0.95 μm, the moon has a relatively flat, i.e., grey,

albedo. A determination of the average lunar spectral albedo is obtained by ratioing the exoatmospheric scans of

the moon to an appropriate set of exoatmospheric scans

of the sun, thereby ratioing out the structure in the solar

spectrum. This average lunar spectral albedo can then be

used along with the extinction cross sections of all absorbing species in an optimal fit to the measurements.

Present plans call for concurrent flight of at least

two instruments—one in an inclined orbit on the International Space Station (51.6°) and one in a sun-synchronous orbit on Meteor 3M (~9:15 a.m.)—to obtain nearglobal coverage. This comprehensive approach will allow SAGE III to make long-term measurements and to

provide the congruent aerosol and gaseous data important to radiative and atmospheric chemistry studies.

Principal Investigator

M. Patrick McCormick

M. Patrick McCormick received an M.A. and Ph.D. in

Physics from the College of William & Mary. After 30

years of service, he retired from NASA’s Langley Research Center in 1996, joining the staff of Hampton University as a Professor in the Physics Department. Dr.

McCormick is Principal Investigator of the SAM II,

SAGE I, SAGE II, SAGE III, and LITE spaceflight experiments, as well as numerous other atmospheric remotesensing instrument and data analysis experiments and is

Co-Principal Investigator of the Pathfinder Instruments

For Cloud And Aerosol Spaceborne ObservationsClimatologie Etendue des Nuages et des Aerosols

(PICASSO-CENA) mission. He received the Arthur S.

Flemming Award for Outstanding Young People in Federal Service in 1979, the NASA Exceptional Scientific

Achievement Medal in 1981, the American Meteorological Society’s Jule G. Charney Award in 1991, the William T. Pecora Award in 1996, and numerous NASA Group

or Special Achievement Awards. In addition, he received

an Honorary Doctor of Science degree from Washington

& Jefferson College in 1981, and has served on their

Board of Trustees. Dr. McCormick is a member of the

International Radiation Commission, the American Meteorological Society, and the American Geophysical

Union, and was past chairman of the International Coordination group on Laser Atmospheric Studies. He was a

member of the National Academy of Sciences Panel on

Aerosol Radiative Forcing, the Committee on Meteorological Analysis, Prediction, and Research, the Panel on

Climate Variability on Decade-to-Century time scales,

and presently he is on the Committee on Earth Studies.

Co-Investigators

Albert A. Chernikov - Central Aerological Observatory, Russia

William P. Chu - NASA/Langley Research Center

Derek M. Cunnold - Georgia Institute of Technology

John J. DeLuisi - NOAA/Environmental Research

Laboratory

Philip A. Durkee - Naval Postgraduate School

Nikolai P. Elansky - Institute of Atmospheric Physics,

Russia

Benjamin M. Herman - University of Arizona

Peter V. Hobbs - University of Washington

Geoffrey S. Kent - Science and Technology Corporation

Jacqueline Lenoble - Universite des Sciences et

Techniques de Lille, France

Alvin J. Miller - NOAA/National Weather Service

SAGE III Parameters

Self-calibrating solar and lunar occultation, with measurements within nine spectral regions between (290-1,550 nm),

to study aerosols, O3, OClO, NO2, NO3, H2O, temperature, and

pressure

Swath: n/a (looks at sun and/or moon through Earth’s limb)

Spatial resolution: 1-2 km vertical

Mass: 40 kg excluding unique hardware

Duty cycle: During solar and lunar Earth occultation

Power: 30 W (average), 75 W (peak)

Data rate: 100 kbps for 8 min, three times per orbit

Thermal control by: Passive, heaters, and thermal electric

cooler

Thermal operating range: 10-30° C

FOV: ±185° azimuth, 13-31° elevation,

dependent on orbital altitude

Instrument IFOV: <0.5 km vertical at 20-km tangent height

Pointing requirements (platform+instrument, 3 σ):

Control: 1°

Knowledge: 0.25°/axis

Stability: 30 arcsec/sec per axis

Physical size: 25 × 25 × 42 cm

34-cm diameter × 74 cm
1999 ESE Reference Handbook EOS Instruments • 145

SAGE III Data Products

Level 1B Transmission

(≥80 wavelengths) Solar Events

Aerosol Extinction Strat. Optical

Depth (at 8 wavelengths),

Aerosol to molecular extinction

ratio at 1020 nm (solar only)

H2

O

 Concentration (Alt.)

 Mixing Ratio (Pressure)

NO2

 Concentration (Alt.)

 Mixing Ratio (Pressure)

 Slant Path Col. Amt. (Alt.)

NO3 (Lunar Only)

 Concentration (Alt.)

 Mixing Ratio (Pressure)

O3

 Concentration (Alt.)

 Mixing Ratio (Pressure)

 Slant Path Col. Amt. (Alt.)

OCIO (Lunar Only)

 Concentration (Alt.)

 Mixing Ratio (Pressure)

Pressure

Temperature Profile

(solar only)

Cloud Presence

Accuracy

Absolute :: Relative

0.05% :: 0.05%

5% :: 5%

10% :: 15%

10% :: 15%

10% :: 10%

6% :: 5%

25% :: 20%

2% :: 2%

2 K :: 2 K

N/A

Temporal

 Resolution

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

1/(2 minutes), 30/day

Horizontal

Resolution :: Coverage

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Solar 1.5 km :: Global

Lunar 3.5 km :: Global

Vertical

Resolution :: Coverage

0.5 km :: 0-100 km

0.5 km :: 0-40 km

0.5 km :: 0-50 km

24 levels/decade :: 1000-0.8 hPa

0.5 km :: 10-50 km

24 levels/decade :: 250-0.8 hPa

0.5 km :: 10-50 km

0.5 km :: 20-55 km

24 levels/decade :: 50-0.4 hPa

0.5 km :: 6-85 km

24 levels/decade :: 500-0.004 hPa

0.5 km :: 50-85 km

0.5 km :: 15-25 km

24 levels/decade :: 121-25 hPa

0.5 km :: 0-85 km

0.5 km :: 0-85 km

24 levels/decade :: 1000-0.004 hPa

0.5 km :: 6-30 km

Volker Mohnen - State University of New York-Albany

Venkatachalam Ramaswamy - Princeton University

David H. Rind - NASA/Goddard Institute for Space

Studies

Philip B. Russell - NASA/Ames Research Center

Vinod K. Saxena - North Carolina State University

Eric P. Shettle - Naval Research Laboratory

Gabor Vali - University of Wyoming

Steven C. Wofsy - Harvard University

Joseph M. Zawodny - NASA/Langley Research Center

Reference

McCormick, M.P., 1991: SAGE III capabilities and global change. Paper 91-0051, 29th Aerospace Sciences

Meeting, 7-10 January 1991, Reno, Nevada, American

Institute of Aeronautics and Astronautics; Washington,

DC.

Product Name
146 • EOS Instruments 1999 ESE Reference Handbook

SeaWinds URL

http://winds.jpl.nasa.gov/

SeaWinds

Key SeaWinds Facts

The SeaWinds instruments are designed to acquire accurate, highresolution, continuous, all-weather measurements of global (land,

ice, and ocean) radar cross-section and near-surface vector winds

over the ice-free global oceans. As the only instruments capable

of measuring wind velocity—both speed and direction—under

all-weather conditions, SeaWinds data are crucial for studies of

tropospheric dynamics, upper-ocean circulation, and air-sea interaction. SeaWinds data will also be provided in near-real-time

to the U.S. National Centers for Environmental Prediction (NCEP)

for use in global and regional operational weather prediction.

SeaWinds transmits pulses of microwave radiation at 13.4

GHz and measures the backscattered signal from the Earth over a

continuous, 1800-km-wide swath centered on the subsatellite

track. The surface normalized radar cross-section is calculated

from the backscatter measurements and knowledge of the viewing geometry and instrument characteristics. Over the ocean, the

received power results primarily from scattering from centimetric

ocean roughness elements whose amplitudes and directional distributions are in equilibrium with the local wind; thus

backscattered power varies as a function of wind speed and direction relative to the radar beam. Multiple, near-simultaneous

measurements of normalized radar cross-section obtained from

the same location, but from different viewing directions and incidence angles, are combined with an empirical model function relating backscatter cross-section to wind conditions to allow calculation of near-surface wind speed and direction over the icefree oceans.

The SeaWinds instruments are follow-ons to the NASA

scatterometer (NSCAT), which flew on NASDA’s Advanced Earth

Observation Satellite (ADEOS) from August 1996 until the failure of the ADEOS spacecraft in June 1997. The QuikScat mission was developed rapidly following the premature demise of

ADEOS. QuikScat was launched on June 19, 1999 and is expected

to operate for at least two years, overlapping the launch and validation of the SeaWinds instrument on ADEOS-II (currently

planned for late 2000). The SeaWinds/ADEOS-II mission will

operate for 3 years after launch with a 5-year lifetime goal. The

dual-scanning-pencil-beam design of the SeaWinds instruments

replaces the 6, 3-m-long antenna array used for NSCAT with a

single 1-m diameter rotating-dish antenna. This compact design

allows SeaWinds to be accommodated on both the QuikScat and

ADEOS-II spacecraft, and provides a contiguous measurement

swath (eliminating the 329-km nadir gap in the NSCAT data).

NASA’s SeaWinds scatterometers will acquire high-accuracy

wind speed and direction measurements over nearly 90% of the

ice-free global oceans each day (exceeding the temporal resolution requirements in the data product table found at the end of

Flights on QuikScat and ADEOS-II missions.

Heritage: SEASAT, NSCAT.

Ku-band scatterometer with rotating antenna to

measure global radar scattering cross-section and

ocean near-surface wind velocity.

All-weather global ocean surface wind speed and

direction measurements used for research studies

and operational weather prediction.

Non-ocean scattering cross-sections used for

vegetation classification/monitoring and ice edge/

type investigations.

Continues cooperative efforts between the U.S. and

Japan to evaluate and monitor global change.

Follow-ons to NSCAT, which flew on ADEOS-I in

1996-1997.

Instrument is in-house Jet Propulsion Laboratory

development, subcontracts for major subsystems.

QuikScat spacecraft is procured by GSFC for JPL.

Overall instrument Phase C/D started in 1992.

QuikScat started in 1997 and fills the gap between

the failure of the ADEOS-I spacecraft (6/97) and the

launch of ADEOS-II.

NASA Scatterometer for Flight on ADEOS II

SeaWinds on ADEOS II
1999 ESE Reference Handbook EOS Instruments • 147

SeaWinds Parameters

Mass: 220 kg

Power: 220 W

Duty Cycle: 100%

Data Rate: 40 kbps

Thermal control by: radiators

Thermal operating range: 5-40 ̊ C

FOV: Rotating (at 18 rpm) pencil beam antenna with dual

feeds pointing 40 ̊ and 46 ̊ from nadir

IFOV: ±51 ̊ from nadir

Swath: 1800 km (±51 ̊) from 705 km altitude

Pointing requirements (3 σ):

Control: <0.3 ̊ (~1000 arcsec)

Knowledge: <0.05 ̊ (~167 arcsec)

Stability: <0.008 ̊/sec (30 arcsec/sec)

Physical Size: 32 × 46 × 34 cm (CDS)

81 × 91 × 43 cm (SES)

100 cm diameter antenna dish on

 60 cm diameter x 60 cm pedestal

Total height is ~150 cm (SAS)

this section). SeaWinds measurements will be provided

in near-real time to NCEP for use in marine forecasting,

operational global numerical weather prediction, and climate forecasting. SeaWinds data will play a crucial role

in interdisciplinary scientific investigations of global

weather patterns and marine meteorology, wind-driven

ocean circulation, and air-sea interaction and climate

dynamics. Raw backscatter measurements from land and

ice are also used to classify vegetation type, monitor

large-scale land use and productivity changes, and identify and monitor ice type and extent. Post-launch validation of the NSCAT measurements showed that they exceeded the pre-launch science accuracy requirements.

Research studies and operational analyses using NSCAT

data confirm the utility and impact of the scatterometer

vector winds and demonstrate the scientific potential of

the scatterometer measurements over land and ice.

SeaWinds data products will consist of global, multiazimuth normalized radar cross-section measurements

with ~6 × 25-km spatial resolution, and 25-km resolution ocean vector winds (~12% speed and 20-deg direction accuracies for wind speeds of 3-30 m/s) in the measurement swath. Cross-section measurements obtained

by the ADEOS-II instrument will be rain-flagged and corrected for atmospheric attenuation effects using ADEOSII AMSR data where available.

Principal Investigator

Michael Freilich

Michael Freilich received degrees in Physics (honors)

and Chemistry from Haverford College, and a Ph.D. in

Oceanography from Scripps Institution of Oceanography in 1982. He joined the Jet Propulsion Laboratory in

1983 as a member of the Oceanography Group. He served

as the NSCAT Project Scientist from 1983 to 1992, and

was a Principal Investigator and Coordinating Investigator for the European Space Agency’s ERS-1 and ERS2 missions. Currently, he is an associate professor in the

College of Oceanic and Atmospheric Sciences at Oregon

State University.

Co-Investigators

Robert M. Atlas - NASA/Goddard Space Flight Center

Robert A. Brown - University of Washington

Peter Cornillon - University of Rhode Island

David Halpern - Jet Propulsion Laboratory

Ross Hoffman - Atmospheric and Environmental

Research

W. Timothy Liu - Jet Propulsion Laboratory

David G. Long - Brigham Young University

Richard K. Moore - University of Kansas

James J. O’Brien - Florida State University

References

Naderi, F.M., M.H. Freilich, and D.G. Long, 1991:

Spaceborne radar measurement of wind velocity over the

ocean—An overview of the NSCAT Scatterometer System. Proc. Ins. IEEE, 79, 850-866.

Wu, C., J. Graf, M. Freilich, D. Long, M. Spencer, W.

Tsai, D. Lisman, and C. Winn, 1994: The Sea Winds

scatterometer instrument. International Geoscience and

Remote Sensing Symposium, Volume 3, 8-12 August

1994, Pasadena, CA, T.I. Stein, Ed., Institute of Electrical and Electronic Engineers, Pisacataway, N.J., 1511-

1515.
148 • EOS Instruments 1999 ESE Reference Handbook

SeaWinds Data Products

Product Name

Level-1B Product

Global Backscatter

Cross-section

Ocean Vector Winds

Accuracy

Absolute :: Relative

 :: 0.25 dB

~12% speed ::

20° direction ::

Temporal

 Resolution

70% daily,

90% every 2 days

90% oceans

every 2 days

Horizontal

Resolution :: Coverage

6 × 25 km :: Global

6 × 25 km :: Global

(Land, Ocean, & Ice)

25 km :: Ocean

Vertical

Resolution :: Coverage

N/A :: Surface

N/A :: Surface

Monthly mean wind velocity and wind stress curl in the tropical Pacific during November 1996, as measured by the NASA Scatterometer.

Arrows indicate monthly mean near-surface wind velocity. Instantaneous NSCAT velocity measurements were transformed to wind stress,

and the vertical component of wind stress curl was calculated from the monthly mean stress field. Dark shading indicates regions of

mean wind stress curl greater than 1 × 10-7 N/m3; light shading delimits mean curls less than -1 × 10-7 N/m3.

The zonally coherent bands of intense positive curl near the Intertropical Convergence Zone and negative curl to the south drive the

complex zonal North Equatorial Current and North Equatorial Counter Current systems.

During November 1996, winds over the Gulf of Tehuantepec (15° N, 95° W) were dominated by a few short but intense northerly wind

events. The white line of zero wind stress curl (separating the intense negative curl to the northwest and the similarly large positive curl

to the southeast) defines the monthly mean core of the jet.
1999 ESE Reference Handbook EOS Instruments • 149

Key SORCE Facts

PI Mode Mission

Heritage: UARS SOLSTICE

Four instruments on a solar/stellar pointed

spacecraft:

1) four-channel active cavity radiometer (TIM);

2) visible and near-infrared prism spectrometer

(SIM);

3) two-channel ultraviolet grating spectrometer

(SOLSTICE);

4) extreme ultraviolet and soft X-ray photometer

(XPS)

Provides daily measurements of total solar

irradiance (TSI) and spectral solar irradiance

between 1 nm and 2000 nm, incorporating

absolute sensors, in-flight calibration and, in the

case of the UV observations, comparison to

bright early-type stars

Responsible Center: Laboratory for Atmospheric

and Space Physics (LASP)/University of

Colorado at Boulder

SORCESOlar Radiation and Climate Experiment

SOLSTICE

SIM

TIM

XPS

The SOlar Radiation and Climate Experiment (SORCE) consists

of a small, free-flying satellite carrying four instruments to measure solar radiation incident at the top of the Earth's atmosphere. It

is scheduled for launch in mid-2002 carrying the Total Irradiance

Monitor (TIM), Spectral Irradiance Monitor (SIM), Solar Stellar

Irradiance Comparison Experiment (SOLSTICE), and the XUV

Photometer System (XPS).

The total solar irradiance, or TSI, along with Earth’s global

average albedo, determines Earth’s global average equilibrium temperature. Because of selective absorption and scattering processes

in the Earth’s atmosphere, different regions of the solar spectrum

affect Earth’s climate in distinct ways. Approximately 20-25% of

the TSI is absorbed by atmospheric water vapor, clouds, and ozone,

by processes that are strongly wavelength dependent. Ultraviolet

radiation at wavelengths below 300 nm is completely absorbed by

the Earth’s atmosphere and contributes the dominant energy source

in the stratosphere and thermosphere, establishing the upper

atmosphere’s temperature, structure, composition, and dynamics.

Even small variations in the Sun’s radiation at these short wavelengths will lead to corresponding changes in atmospheric chemistry. Radiation at the longer visible and infrared wavelengths penetrates into the lower atmosphere, where the portion not reflected

is partitioned between the troposphere and the Earth’s surface, and

becomes a dominant term in the global energy balance and an essential determinant of atmospheric stability and convection. Thus

it is important to accurately monitor both the TSI and its spectral

dependence.

Variations of the solar radiation field are still largely unknown,

but in the visible they are likely far less than one percent. The

observations therefore require precision and accuracy that can only

be achieved from space. Although the shortest wavelength ultraviolet radiation from the Sun varies by much larger factors, its

measurement also requires access to space since the radiation does

not penetrate the atmosphere. Precise space measurements obtained

during the past 20 years imply that TSI varies on the order of 0.1%

over the solar cycle, but with greater variations on a short-term

basis. For example, the passage of sunspots over the disk produces

2-4 times that amount. The variation apparently occurs over most

time scales, from day-to-day variations up to and including variations over the 11-year solar cycle. How TSI variations are distributed in wavelength is still poorly understood. The largest relative

solar variations are factors of two or more at ultraviolet and shorter

wavelengths, but the greater total energy available at visible and

longer wavelengths makes their small variations of potential importance.

Assuming climate models include a realistic sensitivity to solar forcing, the record of solar variations implies a global surface

temperature change on the order of only 0.2° C. However, global

energy balance considerations may not provide the entire story.

Some recent studies suggest that the cloudy lower atmosphere abSORCE URL

http://lasp.colorado.edu/sorce
150 • EOS Instruments 1999 ESE Reference Handbook

sorbs more visible and near infrared radiation than previously thought (25% rather than 20%), which impacts convection, clouds, and latent heating. Also, the solar ultraviolet, which varies far more than the TSI, influences

stratospheric chemistry and dynamics, which in turn controls the small fraction of ultraviolet radiation that leaks

through to the surface.

SORCE provides precise daily measurements of the

total solar irradiance with the TIM instrument, and also

the solar spectral irradiance at wavelengths extending from

the far ultraviolet to the near infrared with the SOLSTICE,

SIM, and XPS instruments. The TIM instrument will continue the precise measurements of total solar irradiance

that began with the Nimbus-7/ERB instrument in 1979

and have continued to the present with the ACRIM series

of measurements as well as ERBS/ERBE, which began

in 1984. The Sun has both direct and indirect influences

on the terrestrial system, and SORCE’s total and spectral

solar measurements provide the requisite understanding

of one of the primary climate system variables.

TIM incorporates four cavities (cones) and adheres

to the basic concepts of Electrical Substitution Radiometers (ESRs), but employs modern, state-of-the-art electronics and materials. The four cavities provide multiple

redundancy and added duty-cycling capability. It will provide an absolute accuracy of 300 ppm, and a precision

and long-term relative accuracy of 10 ppm per year.

SIM is a doubly-redundant, prism spectrometer covering the full spectral range 200-2000 nm with a resolving power greater than 30 (bandwidth < 34 nm). Its optical design is a variant of a prism spectrometer first described by Féry in 1910—the prism has a concave front

surface and a convex, aluminized rear surface, and is therefore self-focusing. The optical system uses two quartz

prisms, each with a separate optical path, providing complete redundancy. The two paths can also be coupled,

whereby one prism delivers monochromatic light to the

other for in-flight calibration. Using a miniature electrical substitution radiometer (ESR) as a detector, SIM will

provide an absolute accuracy of 0.03%, and long-term

relative accuracy of 0.01% per year.

SOLSTICE consists of a two-channel grating spectrometer capable of being pointed at the Sun or at selected

stars and measures from 115-300 nm. The stellar targets,

observed with the same optics and detectors employed

for the solar measurements, are essential because they

establish long-term corrections to the instrument calibration. The ensemble average flux from these 20 or so bright,

early-type stars should remain absolutely constant—intrinsic variability of less than one part in ten thousand

over thousands of years. The unique in-flight calibration

technique of SOLSTICE thereby establishes the instrument response as a function of time throughout the SORCE

mission, and yields time series of solar data corrected for

instrumental effects to an accuracy of about 1 percent.

Moreover, the SOLSTICE technique provides the unique

ability to directly compare solar irradiance measurements

made during the SORCE mission with previous and future observations. Since the stellar irradiance remains

essentially constant, stellar measurements provide a stable

in-flight reference that is readily transferred between

missions, provided each mission makes observations of

the same stars.

The SORCE investigation will also model the penetration of solar radiation into the Earth’s atmosphere to

establish the radiation field as a function of location and

altitude. The standard SORCE data product will provide

four measurements per day of the total solar irradiance

and of the spectral solar irradiance from 1 nm to 2000

nm. More specifically, spectral data products will consist of solar ultraviolet irradiance from 115-300 nm with

a spectral resolution of 1 nm, the visible and near-infrared irradiance from 200-2000 nm with a varying resolution of 1-34 nm, and six broadband samples of the XUV

from 1-31 nm and at Lyman-α (121.6 nm).

Principal Investigator

Gary Rottman

Gary Rottman holds an M.S. and Ph.D. in Physics from

the Johns Hopkins University. He is the Associate Director of the Laboratory for Atmospheric and Space Physics

of the University of Colorado, Boulder. His space research

includes roles as Principal or Co-Investigator on numerous solar and atmospheric investigations, including Solar-Mesosphere Explorer, the Upper Atmosphere Research Satellite (UARS) SOLSTICE Program, and the

Solar Extreme Ultraviolet Experiment on the TIMED

mission.

Co-Investigators

Thomas N. Woods - University of Colorado

George M. Lawrence - University of Colorado

Jerry Harder - University of Colorado

Bill McClintock - University of Colorado

Julius London - University of Colorado

Judith Lean - Naval Research Laboratory

Oran R. White - National Center for Atmospheric

Research

Peter Fox - National Center for Atmospheric Research

Paul C. Simon - Belgian Institute of Space Aeronomy

Dominique Crommelynck - Royal Meteorological

Institute of Belgium
1999 ESE Reference Handbook EOS Instruments • 151

SORCE Parameters

Spectral range from 1-2000 nm

TIM: Total Irradiance Monitor

SIM: Spectral Irradiance Monitor (200-2000 nm)

SOLSTICE: Solar Stellar Irradiance Comparison Experiment (115-300 nm)

XPS: XUV Photometer System (1-31 nm)

Photometric accuracy: TIM will provide an absolute

accuracy of 300 ppm with a relative accuracy of 10 ppm per

year; SIM an absolute accuracy of 0.03% and a relative

accuracy of 0.01% per year; SOLSTICE an absolute

accuracy better than 5%, and relative accuracy better than

1%, and XPS an absolute accuracy of 12% and a relative

accuracy of 4%.

Spectral resolution: varying from 1-34 nm

Swath: n/a

Spatial resolution: n/a

Mass: 78 kg

Duty cycle: 83% data taking

Power: 113 W (Orbit average)

Data rate: 6.8 kbps (average)

Thermal control by: Passive radiator/actively heated

detectors

Thermal operating range: -10 to +20° C (15° average)

FOV: 2π unobstructed from spacecraft

Instrument IFOV: TIM 12.8°, SOLSTICE 1.5° × 1.5°, SIM

1.5° × 1.5°, and XPS 6°

Pointing requirements:

Control: +/- 1 arcmin

Knowledge: 30 arcsec

Stability: 1 arcmin/min

Jitter: 15 arcsec per sec

Physical size: TIM 16 × 21 × 30 cm;

SIM 16 × 18 × 81 cm; SOLSTICE 18 × 39 × 85 cm;

XPS 16 × 19 × 18 cm

300 ppm :: 10 ppm/year

3-5% :: 1% UV

0.03% :: 0.01%/year visible/

near IR

12% :: 4% XUV

0% :: N/A

N/A :: N/A

N/A :: N/A

2 deg :: Global

SORCE Data Products

Product Name

Total Solar Irradiance (TSI)

Solar Spectral Irradiance,

(1-2000 nm)

Level-1B Radiance

Accuracy

Absolute :: Relative

4/day

4/day

On demand

Temporal

Resolution

Horizontal

Resolution :: Coverage

Vertical

Resolution :: Coverage

N/A :: Top of Atmos

N/A :: Top of Atmos

1 km :: 40-100 km

SORCE Project

William Ochs - SORCE Project Manager

Robert Cahalan - SORCE Project Scientist

References

Rottman, G.J., T.N. Woods, and T.P. Sparn, 1993: Solar

Stellar Irradiance Comparison Experiment I: 1 Instrument

Design and Operation. J. Geophys. Res., 98, 10,667-

10,677.

Woods, T.N., G.J. Rottman, and G. Ucker, 1993: Solar

Stellar Irradiance Comparison Experiment I: 2 Instrument

Calibration. J. Geophys. Res., 98, 10,679-10,694.

Woods, T.N., D.K. Prinz, G.J. Rottman, J. London, P.C.

Crane, R.P. Cebula, E. Hilsenrath, G.E. Brueckner, M.D.

Andrews, O.R. White, M. E. VanHoosier, L.E. Flyod, L.

C. Herring, B.G. Knapp, C.K. Pankratz, and P.A. Reiser,

1996: Validation of the UARS Solar Ultraviolet Irradiances: Comparison with the ATLAS - 1, - 2 Measurements. J. Geophys. Res., 101, 9541-9569.

Rottman, G.J., G. Mount, G. Lawrence, T. Woods, J.

Harder, and S. Tournois, 1997: Solar spectral irradiance

measurements: Visible to near infrared, NEWRAD’97.

Metrologia, 35, 707-712.

Lawrence, G.M., J. Harder, G. Rottman, T. Woods, J.

Richardson, and G. Mount, 1998: Stability considerations

for a solar Spectral Intensity Monitor (SIM). SPIE, 3427,

477-485.
152 • EOS Instruments 1999 ESE Reference Handbook

Selected for flight on EOS CHEM

Heritage: ATMOS, SCRIBE, AES

High-spectral-resolution infrared-imaging Fourier

transform spectrometer

Generates three-dimensional profiles on a global

scale of virtually all infrared-active species

from Earth’s surface to the lower stratosphere

In-house Jet Propulsion Laboratory development

Key TES Facts

TES is a high-resolution infrared-imaging Fourier transform spectrometer with spectral coverage of 3.2 to 15.4 μm at a spectral

resolution of 0.025 cm-1, thus offering line-width-limited discrimination of essentially all radiatively active molecular species in

the Earth’s lower atmosphere. TES has the capability to make both

limb and nadir observations. In the limb mode, TES has a height

resolution of 2.3 km, with coverage from 0 to 34 km. In the downlooking modes, TES has a spatial resolution of 0.53 × 5.3 km with

a swath of 5.3 × 8.5 km. TES is a pointable instrument and can

access any target within 45° of the local vertical, or produce regional transects up to 885-km length without any gaps in coverage.

TES employs both the natural thermal emission of the surface and atmosphere and reflected sunlight, thereby providing daynight coverage anywhere on the globe.

Observations from TES will further understanding of longterm variations in the quantity, distribution, and mixing of minor

gases in the troposphere, including sources, sinks, tropospherestratosphere exchange, and the resulting effects on climate and

the biosphere. TES will provide global maps of tropospheric ozone

and its photochemical precursors. These observations will serve

as primary inputs to a database of the three-dimensional distribution (on global, regional, and local scales) of gases important to

tropospheric chemistry, troposphere-biosphere interactions, and

troposphere-stratosphere exchange. Other objectives include:

• Simultaneous measurements of NOy, CO, O3, and H2O for

use in the determination of the global distribution of OH, an

oxidant of central importance in tropospheric chemistry;

• measurements of SO2 and NOy as precursors to the strong

acids H2SO4 and HNO3, which are the main contributors to

acid deposition;

• measurements of gradients of many tropospheric species in

order to understand troposphere-stratosphere exchange; and

• determination of long-term trends in radiatively active minor

constituents in the lower atmosphere to investigate effects on

global radiative balance and atmospheric dynamics.

TES measurements will help determine local atmospheric

temperature and humidity profiles, local surface temperatures, and

local surface reflectance and emittance. TES observations will also

be used to study volcanic emissions for hazard mitigation, indications of the chemical state of the magma, eruption prediction, and

quantification of the role of volcanoes as sources of atmospheric

aerosols.

TESTropospheric Emission Spectrometer

TES URL

http://tes.jpl.nasa.gov/
1999 ESE Reference Handbook EOS Instruments • 153

The aforementioned database will calibrate models

of the present and future state of the Earth’s lower atmosphere. These models will investigate topics such as:

• Biogeochemical cycles between the lower atmosphere and biosphere (primarily carbon monoxide

and methane);

• global climate modification caused by an increase

in radiatively active gases;

• distribution and lifetimes of chlorofluorocarbons

(CFCs) and halons, which contribute substantially

to the depletion of stratospheric ozone;

• changes in the oxidizing power of the troposphere

and the distribution of tropospheric ozone caused

by urban and regional pollution sources, particularly

carbon monoxide, nitrogen oxides, methane, and

other hydrocarbons;

• acid deposition precursors;

• sources and sinks of species important to the generation of tropospheric and stratospheric aerosols;

and

• natural sources of trace gases such as methane from

organic decay, nitrogen oxides from lightning, and

sulphur compounds from volcanoes.

Principal Investigator

Reinhard Beer

Dr. Beer received a B.Sc. and Ph.D. in Physics from the

University of Manchester, United Kingdom. He has been

associated with the Jet Propulsion Laboratory since 1963;

his current position is that of Senior Research Scientist

and Leader of the Tropospheric Emission Spectrometry

Flight Team. Dr. Beer was chairman of the NASA Infrared Experiments Working Group and now serves as Principal Investigator for the Airborne Emission Spectrometer (AES). He has been awarded the NASA Exceptional

Scientific Achievement Medal for the discovery of extraterrestrial deuterium, three NASA group achievement

awards, and numerous certificates of recognition.

Co-Investigators

Shepard A. Clough - Atmospheric and Environmental

Research

Daniel J. Jacob - Harvard University

Jennifer A. Logan - Harvard University

TES Parameters

Maximum sampling time of 16 sec, with a signal-tonoise ratio of up to 600:1

Limb mode: Altitude coverage = 0-34 km

Nadir and limb viewing (fully targetable)

Spectral region: 3.2 to 15.4 μm, with four single-line

arrays optimized for different spectral regions

Swath: 5.3 × 8.5 km

Spatial resolution: 0.53 × 5.3 km

Mass: 385 kg (allocation)

Duty cycle: Variable

Power: 334 W (allocation)

Data rate: 6.2 Mbps (peak); 4.9 Mbps (average)

Thermal control by: 2 Stirling cycle coolers, heater,

radiators

Thermal operating range: 0-30° C

FOV: +45° to -72° along-track, ±45° cross-track

Instrument IFOV: 12 × 7.5 mrad

Pointing requirements (platform+instrument, 3 σ):

Control: 156 arcsec (pitch)

Knowledge: 124 arcsec

Stability: 156 arcsec (over 50 sec)

Physical size: 140 × 130 × 135 cm (stowed);

304 × 130 × 135 cm (deployed)

Frank Murcray - University of Denver

David Rider - Jet Propulsion Laboratory

Curtis P. Rinsland - NASA/Langley Research Center

Clive D. Rodgers - Oxford University

Stanley P. Sander - Jet Propulsion Laboratory

Fredric W. Taylor - Oxford University

Helen Worden - Jet Propulsion Laboratory
154 • EOS Instruments 1999 ESE Reference Handbook

Reference

Glavich, T.A., and R. Beer, 1991: Tropospheric Emission Spectrometer for the Earth Observing System. Infrared Technology XVII, 22-26 July 1991, San Diego,

California-Proceedings of SPIE - The International Society for Optical Engineering, Vol. 1540, Society of

Photo-Optical Instrumentation Engineers, Bellingham,

Washington, 148-159.

1% :: 1%

3% :: 14 ppbv

3% :: 3-10 ppbv

5% :: 3 pptv

3% :: 15-25 pptv

5% :: 100 pptv

3% :: 3-20 ppbv

2 K :: 0.2 K

3% :: 0.5-50 ppmv

1 K :: 0.1 K

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

5.3 × 8.5 km Global

TES Data Products

Product Name

Level-1B Radiance, TES

(IR spectra in selected

bands 3.2 - 15.4 μm)

CH4

 Mixing Ratio

CO Mixing Ratio

HNO3 Mixing Ratio

NO Mixing Ratio

NO2 Mixing Ratio

O3 Mixing Ratio

H2O/HDO Mixing Ratio

Temperature Profile

Land-Surface Brightness

Temperature

Level 2 Detection Flags

Accuracy

Absolute :: Relative

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

1/(16 day) measured over a

4-day period

Temporal

Resolution

2-6 km :: 0-34 km

2-6 km :: 0-34 km

2-3 km :: 0-34 km

2-3 km :: 5-34 km

2-3 km :: 5-34 km

2-6 km :: 0-34 km

4-6 km :: 0-34 km

2-6 km :: 0-34 km

N/A :: Surface

Horizontal

Resolution :: Coverage

Vertical

Resolution :: Coverage
1999 ESE Reference Handbook EOS Instruments • 155

This is a sequence of frames, beginning at the top, from an animation depicting the launch

and deployment of the Earth Observing System’s Terra platform from an ATLAS II AS

rocket. This and other animations can be found at http://terra.nasa.gov/
156 • EOS Instruments 1999 ESE Reference Handbook

The ETM+ scanner (above) being prepared prior to

shipment for installation on the Landsat 7 platform

(right). Landat 7 was successfully launched from

Vandenberg Air Force Base on April 15, 1999.

This is a photograph of the Clouds

and the Earth’s Radiant Energy

System (CERES) instrument.

CERES measures both solar-reflected and Earth-emitted radiation from the top of the atmosphere to the surface. It will also

determine cloud properties including the amount, height, thickness,

particle size, and phase of clouds

using simultaneous measurements by other instruments. One

CERES scanner (left) was successfully launched on the TRMM

spacecraft on November 27, 1997.

Two more CERES scanners will fly

on the Terra as well as the EOS

PM spacecraft.

The Moderate-resolution Imaging

Spectroradiometer (MODIS) instruments—

built to NASA specifications by Santa

Barbara Remote Sensing—represent the

finest in engineering of spaceflight hardware

for remote sensing of the atmosphere, land,

and ocean. MODIS is scheduled for flight

on Terra and EOS PM.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 157

In 1988, NASA issued an Announcement of

Opportunity (AO) for the selection of instruments, science teams, and interdisciplinary investigation teams in support of the Earth Observing System (EOS). A total of 458 proposals were received in response to the AO, and

early in 1990 NASA announced the selection

of 29 Interdisciplinary Science (IDS) investigations. The IDS teams were selected to conduct basic research, develop methods and

models for analysis of EOS observations, develop and refine models of Earth system processes, and forge new alliances among scientific disciplines fostering a unique perspective

into how the Earth functions as an integrated

system. As the program has evolved, the number of IDS investigations has been increased

to 71.

Many of the important scientific questions to be studied by EOS require analyses

by interdisciplinary teams using data and information from multiple EOS and international instruments and in situ observations.

The IDS investigation teams bring together

highly talented experts from diverse fields to

tackle specific areas of uncertainty regarding

the functioning of the Earth as a coupled system. All investigations will exploit the newly

accessible EOS data, with research results

being made available through EOSDIS to enhance broad participation by the science community at large.

The list on this and the following pages

provides the names of the IDS Principal Investigators, the title of their investigations, and

the pages on which descriptions of their investigations can be found.

 Interdisciplinary Science

Investigations

Mark Abbott 162

Coupled Atmosphere-Ocean Processes and Primary Production

in the Southern Ocean

Kevin R. Arrigo 165

Validation of MODIS Primary Productivity Algorithms

Marcia Baker 168

Water Transport to the Upper Troposphere by Convective

Systems, as Inferred from Global Lightning Data

Eric J. Barron 170

Global Water Cycle: Extension Across the Earth Sciences

Ian J. Barton 172

Interdisciplinary Studies of the Relationships Between Climate,

Ocean Circulation, Biological Processes, and Renewable

Marine Resources

G. Robert Brakenridge 175

River Flooding and Global Environmental Change: A Multi-Sensor Approach

Douglas G. Capone 178

Collaborative Research: Modeling of N2 and CO2 Fixation by the

Oceanic Diazotroph Trichodesmium

Mary-Elena Carr 180

An Historical and Modeling Comparison Study of Four Coastal

Upwelling Systems

William L. Chameides 182

The Yangtze Delta of China as an Evolving Metro-Agro-Plex

(China-MAP)

Josef Cihlar 185

Northern Biosphere Observation and Modeling Experiment

(NBIOME)

Jean O. Dickey 188

Retrieval, Assimilation, and Modeling of Atmospheric Water

Vapor from Ground- and Space-Based GPS Networks: Investigation of the Global and Regional Hydrological Cycles
158 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Robert E. Dickinson 191

Project to Interface Modeling on Global and Regional Scales with EOS Observations

Paul A. Dirmeyer 193

The Global Soil Wetness Project

Jeff Dozier 195

Hydrology, Hydrochemical Modeling, and Remote Sensing In Seasonally Snow-covered Alpine

Drainage Basins

Ralph Dubayah 198

Combining Remote Sensing and Hydrological Modeling for Applied Water and Energy Balance

Studies

Dara Entekhabi 201

Direct Use of Satellite Remote Sensing in the Estimation of Hydrologic Transports

Paul G. Falkowski 202

Representing Key Phytoplankton Groups in Ocean Carbon Cycle Models

Jonathan Foley 204

Integrating Biogeochemical, Ecological, and Hydrological Processes in a Dynamic Biosphere

Inez Fung 208

Biosphere-Atmosphere Interactions

Steven J. Ghan 210

Aerosols, Clouds, Chemistry, and Radiative Forcing

Barry E. Goodison 213

Use of the Cryospheric System (CRYSYS) to Monitor Global Change in Canada

Sirpa Hakkinen 216

Freshwater Cycle in the Global Ocean

James E. Hansen 218

Interannual Variability of the Global Carbon, Energy, and Hydrologic Cycles

Dennis Hartmann 220

Climate Processes Over the Oceans

Eileen Hofmann 222

Evaluation of Marine Productivity in the Tropical Pacific and Atlantic Oceans Using Satellite

Ocean Color and Numerical Models

Brent Holben 224

Characterizing Aerosol Forcing Over the Atlantic Basin

Marc Lee Imhoff 226

Assessing the Impact of Expanding Urban Land Use on Agricultural Productivity Using Remote

Sensing Data and Physically Based Soil Productivity Models

Thomas J. Jackson 228

Soil Moisture Mapping at Satellite Temporal and Spatial Scales
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 159

Daniel J. Jacob 230

Investigation of the Coupling Between Tropospheric Ozone, Sulfate Aerosols, and Climate Using

a General Circulation Model

Prasad Kasibhatla 233

A Study of Carbon Monoxide Using Trace Constituent Data Assimilation: A New Approach in

Global Tropospheric Chemistry Analysis

R. F. Keeling 235

Southern Ocean Seasonal Net Production From Atmosphere and Ocean Data Sets

Yann Kerr 238

Soroosh Sorooshian

The Hydrologic Cycle and Climatic Processes in Arid and Semi-Arid Lands

Jeffrey T. Kiehl 241

Climate and Chemical Cycles: The Role of Sulfate and Ozone in Climate Change

Charles E. Kolb 243

Urban Metabolism and Trace Gas Respiration

Randal D. Koster 246

The Land Surface Component of the Climate System: (i) Improved Representation of Subgrid

Processes and (ii) Analysis of Land Surface Effects on Climate Variability

William K. M. Lau 248

Regional Land-Atmosphere Climate Simulation System (RELACS) for the Asian Monsoon

Region

W. Timothy Liu 251

The Role of Air-Sea Exchanges and Ocean Circulation in Climate Variability

Yongqiang Liu 253

Spatial and Temporal Variability of Soil Moisture and Its Relation to Water and Energy Balances

in a Monsoon Region

John C. Marshall 255

Interannual Variability of Ocean Color: A Synthesis of Satellite Data and Models and Participation

in the Ocean Carbon Cycle Model Intercomparison

Charles R. McClain 256

Physical-Biological Interactions in the Tropical Pacific & Atlantic Equatorial Surface Layers

Dennis McGillicuddy 259

Modeling Mesoscale Biogeochemical Processes in a TOPEX/Poseidon Diamond Surrounding the

U.S. JGOFS Bermuda Atlantic Time-series Study

Linda O. Mearns 260

Analysis of the Effect of Changing Climate Variability on Crop Production in the Southeastern

United States: An Integration of Stochastic Modeling, Regional Climate Modeling, Crop Modeling, and Remote Sensing Techniques
160 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Massimo Menenti 263

Observation and Modeling of Heat and Water Fluxes Over Heterogeneous Land Surfaces at

Mesoscale

Norman L. Miller 265

Global Climate Impact on Regional Hydro-Climate and its Effect on Southeastern Asian

Agro-Ecosystems

Berrien Moore 267

Changes in Global Biogeochemical Cycles

Peter J. Mouginis-Mark 269

A Global Assesment of Active Volcanism, Volcanic Hazards, and Volcanic Inputs to the

Atmosphere

Frank E. Muller-Karger 272

Synoptic Analysis of Factors Influencing Carbon Fluxes at a Continental Margin Time Series:

CARIACO

Masato Murikami 275

Investigation of the Atmosphere-Ocean-Land System Related to Climate Processes

Raymond G. Najjar 277

Evaluation and Comparison of Global Three-dimensional Marine Carbon Cycle Models

Kenneth E. Pickering 278

Tropospheric Convection and Stratosphere-Troposphere Exchange: Effects on Photochemistry, Aerosols, and Climate

Roger Pielke, Sr. 281

Coupling Atmospheric, Ecological, and Hydrologic Processes in a Regional Climate Model

John A. Pyle 285

Chemical, Dynamical, and Radiative Interactions Through the Middle Atmosphere and

Thermosphere

Dale A. Quattrochi 287

Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air quality)

John O. Roads 292

Variability and Predictability of Land-Atmosphere Interactions: Observational and Atmosphere Interactions: Observational and Modeling Studies

Richard B. Rood 294

The Development and Use of a Four-Dimensional Atmospheric-Ocean-Land Data Assimilation System for EOS

Cynthia Rosenzweig 2987

Impacts of Interannual Climate Variability on Agricultural and Marine Ecosystems and

Fisheries

D. Andrew Rothrock 300

POLar Exchange at the Sea Surface (POLES)
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 161

David S. Schimel 302

Using Multi-Sensor Data to Model Factors Limiting Carbon Balance in Global Arid and

Semiarid Land

Mark R. Schoeberl 304

Investigation of the Chemical and Dynamical Changes in the Stratosphere

Christopher A. Shuman 306

Interdisciplinary Determination of Snow Accumulation Patterns on the Greenland Ice Sheet:

Combined Atmospheric Modeling and Field and Remote Sensing Studies

W. James Shuttleworth 308

Influence of Subgrid-Scale Heterogeneity on Remotely-Sensed Surface Temperature

David A. Siegel 277

Development and Application of the Next Generation of Ocean Color Models for the Understanding of Marine Processes on Regional and Global Scales

Ronald B. Smith 312

Climate Change and Human Response in the Semi-arid Near East

Joao V. Soares 314

Thomas Dunne

Long-Term Monitoring of the Amazon Ecosystems Through EOS: From Patterns to Processes

Meric Srokosz 317

Middle And High Latitude Oceanic Variability Study (MAHLOVS)

Graeme Stephens 320

Water Vapor in the Climate System

Byron D. Tapley 323

Earth System Dynamics: The Determination and Interpretation of the Global Angular Momentum Budget Using EOS

Ina Tegen 326

Modeling of Distribution and Interannual to Interdecadal Variations of Aerosols

Owen B. Toon 328

The Role of Natural and Anthropogenic Aerosols in Earth’s Radiation Budget and Climate:

Microphysical Simulations with the NCAR Community Climate Model

John J. Walsh 330

A Numerical Analysis of New Nitrogen Sources of NO3 and N2 Affecting Carbon Cycling in the

Southern Caribbean Sea: A Key to CDOC Contamination of Satellite Color Signals

Bruce A. Wielicki 333

An Interdisciplinary Investigation of Clouds and the Earth’s Radiant Energy System: Analysis

(CERES-A)

Eric F. Wood 335

Terrestrial Hydrology and Climate Studies Using EOS-Era Data
162 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Coupled Atmosphere-Ocean Processes and

Primary Production in the Southern Ocean

Principal Investigator – Mark Abbott

Science Background

The Southern Ocean plays a critical role in the physical

and biogeochemical dynamics of the ocean/atmosphere

system through its role in carbon cycling and heat exchange with the atmosphere. The Antarctic Circumpolar

Current, which links all of the major ocean basins, regulates the oceanic component of the southward/poleward

heat flux. Most ventilation of the deep ocean occurs in

the Southern Ocean where density layers outcrop at the

sea surface. Through cooling, mixing, and sea-ice formation, new water masses are produced, which sink into the

ocean interior and replenish the deep and intermediate

waters of the global ocean.

Carbon fluxes in the Southern Ocean are a significant component of the global carbon cycle. Since individual subsystems within the Southern Ocean can act as

either sources or sinks of carbon dioxide, and our sampling is so poor, it is not known if the region as a whole is

a source or sink for atmospheric carbon dioxide. Measurements of carbon dioxide in the atmosphere and in the

upper ocean suggest that the Southern Ocean is one of

the primary sinks for atmospheric carbon dioxide. Yet recent models suggest that the Southern Hemisphere has

no net uptake of carbon dioxide by the ocean. One explanation for this discrepancy between field measurements

and modeling is the sparse sampling in the Southern

Ocean. As this region is noted for its intense spatial and

temporal variability in nearly all processes, it is possible

that either the field measurements are not sampling these

processes adequately or that the models have not resolved

them.

Of perhaps greater importance, processes in the

Southern Ocean that regulate carbon fluxes are especially

sensitive to the impacts of climate change. Numerical

models suggest that subtle latitudinal shifts in the core of

the westerly winds will greatly affect processes related to

intermediate-water formation and hence ocean circulation. Changes in water vapor transport can affect air/sea

fluxes, thus impacting the rate of deep convection and

deep-water ventilation. Such changes in atmospheric forcing will have complex feedbacks with sea-ice formation

which, in turn, impact deep-water formation and stratification.

Our research focuses on the dynamics of the Southern Ocean and how changes in atmospheric forcing and

ocean circulation regulate the growth rates, abundances,

and distributions of phytoplankton. Our approach is based

on a foundation of satellite- and field-data analysis and

data-assimilation models that will provide a predictive

capability to understand the response of the Southern

Ocean ecosystem to climate change. Our focus is on the

large meanders of ocean fronts in the Antarctic Polar Frontal Zone (APFZ) and their impacts on secondary circulation and their time-dependent impacts on chlorophyll concentrations and primary productivity. The ecosystem in

the APFZ behaves much like a coastal upwelling system

which is characterized by episodic diatom blooms. These

blooms result in high rates of new production, high preservation rates of biogenic silica, and relatively low vertical flux of particulate biogenic material. However, the

APFZ has carbon burial rates that are about 3-to-5 times

those of the Equatorial Pacific, and, during glacial periods, these burial rates were nearly 20 times those of the

Equatorial Pacific. The lack of meridional barriers leads

to a recirculation of diatoms associated with frontal meanders. Phytoplankton alternately upwell and then

downwell in these meanders, creating a helical circulation path. Such bloom events may be unimportant in the

total productivity of the system but play a disproportionate role in carbon fluxes. The critical element in this process is mesoscale variability in ocean circulation. Mesoscale processes are closely linked to both topographic and

wind-stress forcing. Thus, changes in atmospheric forcing may significantly affect this important region of the

world ocean.

Our approach is to combine field observations, analysis of various satellite data sets, and numerical modeling

to study this set of ocean and atmosphere processes. The

tight coupling between ocean physics and biology in the

APFZ requires such a multi-faceted approach, as well as

multiple data sets that will be available in the EOS era.

The APFZ is an important component of the Southern

Ocean, both in terms of biogeochemistry and ecosystem

function. Shifts in the patterns of wind stress or sea-ice

formation will change ocean circulation in the APFZ,

which in turn will affect primary productivity. The APFZ

is thus especially sensitive to climate change. The intense

mesoscale variability (Rossby radius on the order of 15

km) and the storminess of the region requires a combination of observing strategies in order to resolve the critical

scales.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 163

Science Goal

Our focus is to develop coupled physical/biological models that can eventually be used in a predictive mode to

understand the effects of changes in physical forcing of

the ocean.

Current Activities

Our current activities are divided into modeling, satellite-data analysis, and field measurements. We have developed and implemented a 1/6 ̊-resolution circulation

model of the Southern Ocean. This model now runs with

full and accurate eddy dynamics to provide a good simulation of mesoscale processes. We have developed a robust model of the upper ocean ecosystem, using data-assimilation techniques to tune the model parameters. This

model is now being coupled with the mixed-layer model

which is part of the high-resolution circulation model. We

also are continuing our research on isopycnal circulation

models, and the development of state-of-the-art techniques

in ocean-data assimilation.

In the area of satellite-data analysis, we have mapped

the path of the Polar Front using 10 years of sea-surface

temperature imagery from the AVHRR Pathfinder data

set. The intensity of meandering (and hence vertical circulation) is damped where gradients in planetary potential vorticity are large, such as near ocean ridges. We are

reanalyzing air/sea heat and freshwater fluxes from various general circulation models and comparing them with

satellite passive microwave radiometer measurements.

These improved data sets will be used to force the circulation model. Lastly, we have combined altimeter and

AVHRR data to estimate the ocean circulation field. These

data have been compared with model results as well.

Our field work is focused on the impacts of mesoscale processes on phytoplankton biomass and primary

productivity. Bio-optical drifters have been deployed in

Drake Passage and in the APFZ. The first deployments in

Drake Passage revealed the importance of small, mesoscale eddies in supplying nutrients to the upper ocean. The

second deployments in the APFZ revealed large meanders in the Polar Front and the dramatic impacts of bottom topography on the Antarctic Circumpolar Current.

Our primary focus is now on the U.S. Joint Global Ocean

Flux Study (JGOFS) in the APFZ, where we will deploy

moorings and drifters as well as high-resolution ship surveys of the biological and physical processes.

Use of Satellite Data

Satellite data are used in several ways in this program.

First, analysis of specific data sets through the use of long

time series and ensembles of specific processes helps

guide model development. For example, if a particular

relationship between phytoplankton biomass and wind

stress curl is apparent, can the models reproduce this behavior? Second, data are used to validate model output

and quantify model accuracy. In essence, data analysis

will provide the control points with which to evaluate the

progress of the model development activities. Third, data

are assimilated into a variety of predictive models ranging from limited process models to comprehensive ocean/

atmosphere models.

We rely on all of the ocean-related satellite sensors.

TOPEX/Poseidon and the EOS radar altimeter will be used

to study large-scale changes in ocean circulation. Coupling the EOS altimeter data sets with other altimeter data

(such as Geosat Follow-On) will allow us to construct

higher resolution circulation fields to study mesoscale

processes. Infrared observations from MODIS and the

NOAA infrared imagers will be used to study sea-surface

temperature for studies of air/sea fluxes. Coupled infrared/altimeter observations will be used to calculate highresolution ocean circulation fields. Scatterometers (SeaWinds and the ESA scatterometer series) will provide

measurements of the basic wind-forcing fields. Higher

level fields, such as wind stress curl, provide critical information for models of ocean circulation. Passive microwave radiometer (SSM/I and AMSR-E on EOS) measurements are to be used to calculate latent heat fluxes.

These data will be combined with observations from

CERES to improve estimates of boundary-layer fluxes.

We will rely on MODIS (as well as other ocean color

sensors such as SeaWiFS, OCTS, MERIS, and GLI) to

provide basic information on ocean biological processes.

These sensors will be used to estimate phytoplankton

abundance as well as growth rates (based on models that

incorporate biomass, fluorescence, and incoming solar radiation). Concentrations of dissolved organic matter (derived from MODIS) are an essential component of upper

ocean carbon cycling. MODIS-derived estimates of water transparency will be combined with estimates of air/

sea heat and momentum fluxes to calculate mixed-layer

depths.

These data sets, when combined with a suite of assimilation models, will allow us to investigate the effects

of a changing environment on the structure and functioning of the upper ocean ecosystem. We expect that largescale changes, such as decreasing stratospheric ozone

(which will increase surface UV radiation) and changing

patterns of wind forcing as a result of climate change,

will greatly affect the patterns of upper-ocean heat flux

and carbon cycling. Our models will enable us to systematically examine the response of the upper ocean to these

changes, and these predictions will be made with known

error bounds.

Participation in Field Programs

Using funding from the National Science Foundation and

NASA/EOS, we will participate in the JGOFS Antarctic

Environment Southern Ocean Process Study (AESOPS).

We will deploy twelve bio-optical moorings in the APFZ
164 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

at 60 ̊S, 170 ̊W. These moorings will provide a time record

of phytoplankton biomass, productivity, and ocean circulation for six months. Thirty drifters will also be deployed

to study the surface divergence field and its impact on

phytoplankton. High-resolution ship surveys will map the

vertical structure of the physical/biological fields around

the mooring array, and surface silica production rates will

also be measured. Together, these in situ data will be combined with available satellite data to provide a view of

the three-dimensional mesoscale fields in the APFZ and

how they vary in time. These data will be crucial for evaluation of the coupled biological/physical model. We expect to continue a reduced set of mooring deployments in

collaboration with Australian researchers.

Principal Investigator

Mark Abbott

Mark Abbott has been involved in the fields of oceanography and ecology for 12 years. He received his undergraduate degree in Conservation of Natural Resources

from the University of California—Berkeley, and a Ph.D.

in Ecology from the University of California—Davis. He

has been affiliated with Oregon State University since

1988, currently as Professor in the College of Oceanic

and Atmospheric Sciences. Dr. Abbott has served on numerous EOS-related committees, including the EOS Science Executive Committee and the Moderate-Resolution

Imaging Spectroradiometer (MODIS) Panel. His research

interests include studies of coupled biological/physical

processes in the upper ocean and phytoplankton photosyntheses. He has been selected as a MODIS Team Member, and currently chairs the Committee on Earth Studies

of the National Research Council.

Co-Investigators

John Moisan - Long Island University

Leonard J. Walstad - University of Maryland

The following are from Oregon State University:

Andrew Bennett

Timothy J. Cowles

Dudley B. Chelton

Roland deSzoeke

Steven Esbensen

Michael Freilich

David Nelson

Cynthia Paden

James Richman

P. Ted Strub

Richard Walstad

References

Abbott, M.R., and R.M. Letelier, 1997: Going with the

flow—The use of drifters to study phytoplankton dynamics. Monitoring Algal Blooms: New Techniques for Detecting Large-Scale Environmental Change, M. Kahru and

C. Brown, Eds., R.G. Landes Co., New York, 145-170.

Bennett, A.F., B.S. Chua, and L.M. Leslie, 1996: Generalized inversion of a global numerical weather prediction

model. Meteorol. Atmos. Physics, 60, 165-178.

Bennett, A.F., B.S. Chua, and L.M. Leslie, 1997: Generalized inversion of a global numerical weather prediction

model II: analysis and implementation. Meteorol. Atmos.

Physics, 62, 129-140.

Bennett, A.F., B.S. Chua, D.E. Harrison, and M.J.

McPhaden, 1998: Generalized inversion of Tropical Atmosphere-Ocean (TAO) data and a coupled model of the

tropical Pacific. J. Climate, 11, 1768-1792.

Chelton, D.B., R. de Szoeke, and others, 1998: Geographical variability of the first baroclinic Rossby radius of deformation. J. Phys. Oceanogr., 28, 433-460.

Higdon, R.L., and R.A. de Szoeke, 1997: Barotropicbaroclinic time splitting for ocean circulation modeling.

J. Comp. Phys., 135, 30-53.

Letelier, R.M., M.R. Abbott, and D.M. Karl, 1997: Chlorophyll natural fluorescence response to upwelling events

in the Southern Ocean. Geophys. Res. Lett., 24, 409-412.

Moore, J.K., M.R. Abbott, and J.G. Richman, 1997: Variability in the location of the Antarctic Polar Front (90 ̊ W

to 20 ̊ W) from satellite sea surface temperature data. J.

Geophys. Res., 102, 27,825-27,833.

Moore, J.K., M.R. Abbott, and J.G. Richman: Location

and dynamics of the Antarctic Polar Front from satellite

sea surface temperature data, J. Geophys. Res., in press.

Spitz, Y.H., J.R. Moisan, M.R. Abbott, and J.G. Richman,

1998: Data assimilation and a pelagic ecosystem model:

Parameterization using time series observations. J. Mar.

Systems, 16, 51-68.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 165

Validation of MODIS Primary Productivity

Algorithms

Principal Investigator – Kevin R. Arrigo

Science Background

Human activities such as fossil-fuel burning and deforestation have led to a marked increase in atmospheric CO2

concentrations during the last century. However, only a

portion of the CO2 released from these and other related

processes has remained in the atmosphere; the rest has

entered the oceans and the terrestrial biosphere. Unfortunately, the capacity of the oceans to take up additional

CO2 is not well understood, a fact which underscores our

need to better understand the global carbon (C) cycle. An

important component of the oceanic C cycle is the socalled “biological pump.” Simply put, the biological pump

is controlled by the activity of phytoplankton, which take

up CO2 during photosynthesis. Phytoplankton grow near

the ocean surface where light is most abundant. Consequently, their removal of CO2 from surface waters (primary productivity) helps to maintain a CO2 gradient between the ocean and the atmosphere allowing additional

CO2 to diffuse into the ocean from the atmosphere. As

the phytoplankton cells die or are grazed, their biomass

may sink to great depths, potentially removing this C from

the atmosphere for thousands of years.

The efficiency of the biological pump depends on

the magnitude of primary productivity as well as the rate

of removal of this fixed C from surface waters to depth.

The more CO2 the phytoplankton take up and the faster

their biomass sinks from the ocean surface, the stronger

the ocean/atmosphere gradient will be. It has been suggested, however, that because phytoplankton appear to

be in steady state on timescales longer than a year, they

play little if any role in the global C cycle. Steady-state

populations of phytoplankton would be unable to ameliorate increasing atmospheric CO2 concentrations since

they would have no added capacity to take up additional

CO2.

Unfortunately, there is not nearly enough in situ primary productivity data available to assess, at global spatial scales and interannual time scales, whether the annual cycle of phytoplankton growth is in steady state or

not. What is needed is a long time series of globally-synoptic estimates of primary productivity; estimates which

can best be generated from satellite observations of a number of relevant oceanic parameters, including ocean color

(an indicator of phytoplankton biomass), sea-surface temperature (controls algal growth rates and may be used as

an indicator of nutrient supply), wind speed (determines

mixed layer depths), cloud cover (controls light levels),

and sea-ice distributions (important for determining ocean

surface area in polar regions). These parameters are being used in a variety of algorithms to estimate primary

productivity over large spatial scales. Our need to understand the temporal and spatial variability in rates of oceanic primary productivity is the main reason why this

parameter was selected as one of the MODIS-Ocean Level

2 data products. However, the accuracy of these algorithms

must be rigorously assessed by comparing algorithm-derived primary productivity estimates with in situ estimates

at the same time and location. At the present time, no

investigators associated with either SeaWiFS or MODIS

are responsible for this type of crucial primary productivity algorithm validation.

Science Goals

The primary objective of this work will be to evaluate the

daily SeaWiFS/MODIS Primary Productivity

Algorithm(s) by performing a global point-by-point comparison between in situ primary productivity measurements and the output of the SeaWiFS/MODIS Primary

Productivity Algorithm(s). This would fill a serious gap

in the MODIS-Ocean validation effort.

Related objectives of this proposal include:

• Making matched satellite and in situ primary productivity data available to the community via an internetaccessible database

• Quantification of regional differences in global primary

productivity algorithm performance

• Tracking of primary productivity algorithm performance over time

• Quantification of errors in primary productivity estimates

• Comparison and intercalibration of primary productivity estimates from different ocean color platforms

• Constant re-evaluation of primary productivity algorithms (both old and new).
166 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Current Activities

• In situ primary productivity data are being collected,

quality controlled, and archived for algorithm validation purposes

• Primary productivity ‘maps’ are being generated from

Level 2 or 3 ocean color data (SeaWiFS initially, then

MODIS) using the SeaWiFS/MODIS Primary Productivity Algorithm(s)

• Software to perform productivity “match-ups” between

in situ measurements and algorithm output is being developed

• Productivity algorithm performance will be critically

evaluated according to the criteria outlined in the MODIS-Ocean Validation Plan

Participation in Field Activities

As Principal Investigator (PI) on the NSF-funded

ROAVERRS (Research on Ocean- Atmospheric Variability and Ecosystem Response in the Ross Sea) cruises to

the Antarctic, I have been making a variety of high-latitude data available to the MODIS validation effort, in

terms of validating both phytoplankton biomass and satellite-derived estimates of primary productivity. The first

cruise took place from December 1996 through January

1997 and the second cruise from December 1997 through

January 1998. The final cruise was planned for November through December 1998.

Bio-optical characterization of the water column.

Light transmission through the water column is measured

using the PRR 600 Spectroradiometer. This instrument

measures downwelling irradiances and upwelling radiances at 412, 443, 490, 510, 555, and 665 nm and measures downwelling photosynthetically active radiation

(PAR) and upwelling natural fluorescence. The optical

characteristics of Antarctic waters are determined by absorption by both phytoplankton pigments and chromophoric dissolved organic matter (CDOM) and detritus. The degree to which phytoplankton pigments are

packaged within the cell is also an important consideration. We are using measured particulate absorption spectra in conjunction with estimates of pigment concentrations (via High Performance Liquid Chromatography

[HPLC]) to determine the absorption characteristics of

the various phytoplankton assemblages we observe. Detrital absorption is measured using the Kishino method.

Assemblages are characterized by taxonomic analyses.

CDOM absorption spectra are determined spectrophotometrically from water samples we collect during the

cruises. The relative influence of phytoplankton pigments

and CDOM on the observed light field is determined for

a variety of water types (e.g., high vs. low algal biomass,

Phaeocystis vs. diatom dominance).

Ocean color calibration/validation. Satellite sensors

designed to measure concentrations of phytoplankton pigments in surface waters (e.g., MODIS, SeaWiFS, ADEOS/

OCTS) must be calibrated and validated regionally. To

do this we are characterizing and measuring the optical

constituents within the water column and relating these

to measured downwelling irradiances and upwelling radiances at 6 wavelengths. Water-leaving radiances at each

wavelength are calculated from vertical light profiles and

are related to the amount of absorbing material in the surface waters (e.g., algal pigments and CDOM concentrations). The relationships between surface chlorophyll,

CDOM, and water-leaving radiance are used to fine-tune

algorithms designed to measure these quantities from

space. This allows the production of accurate high-resolution maps of surface chlorophyll within our study area

from SeaWiFS/MODIS imagery.

Phytoplankton distributions determined from satellite imagery will be used to fill in the spatial and temporal

gaps in our ROAVERRS sampling grid and will be used

to help interpret other measurements, including hydrography, pCO2, dimethyl sulfide concentrations, particle

flux, and sediment chlorophyll, faunal abundance, and productivity.

Phytoplankton productivity. During ROAVERRS, primary productivity is calculated in a variety of ways to

determine the most appropriate and efficient method. Standard simulated in situ (on-deck) incubations are performed

along the 76° 30' S and 75° S transects. Photosynthesis

versus irradiance incubations are also performed at these

same sites and at numerous others and are being used in

conjunction with in situ radiometric data to estimate depthintegrated primary production. Two more experimental

approaches also are being tested to determine their appropriateness in the Antarctic environment. Vertical profiles of natural fluorescence have been shown to be a

promising technique for estimating primary production

at high spatial resolution. Estimates of productivity calculated by this method will be compared to standard methods to determine its efficacy. Finally, 14C-labeled pigments

should provide an estimate of algal growth rate which

can be used to estimate rates of production. Productivity

estimates will be used to constrain bio-optical primary

productivity models currently being developed.

Principal Investigator

Kevin R. Arrigo

Kevin R. Arrigo is a biological oceanographer with the

Oceans and Ice Branch at NASA/Goddard Space Flight

Center. He received his Ph.D. in biological oceanography from the University of Southern California in 1992

working with Cornelius W. Sullivan on sea-ice ecosystems in the Southern Ocean. After graduation, he came to

NASA/GSFC under a Department of Energy Global

Change Distinguished Post-Doctoral Fellowship to work

with Charles R. McClain and Josephino C. Comiso, between 1992 and 1994. In 1994 he received a faculty ap-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 167

pointment as Assistant Research Scientist at the Joint

Center for Earth System Science, Department of Meteorology, University of Maryland. In 1995, he was hired by

NASA/GSFC where he is now employed. His area of emphasis has been the study of biogeochemical processes in

the Southern Ocean, particularly the Ross Sea, using in

situ measurements, numerical modeling, and satellite remote sensing. His most-recent activities have dealt with

the use of CZCS, OCTS, SeaWiFS, and SSM/I data to

study the interactions between primary production and

sea-ice distribution in the Southern Ocean.

Co-Investigator

Paul Falkowski - Rutgers University

Dale Robinson - Rutgers University

References

Arrigo, K.R., A. Schnell, D.L. Worthen, and M.P. Lizotte.

1998: Primary production in Southern Ocean waters. J.

Geophys. Res., 103, 15,587-15,600. U.S. JGOFS Contribution Number 459.

Behrenfeld, M.J., and P.G. Falkowski, 1997: Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr., 42, 1-20.

Behrenfeld, M.J., and P.G. Falkowski, 1997: A

consumer’s guide to phytoplankton primary productivity

models. Limnol. Oceanogr., 42, 1479-1491.

Antoine, D., J.M. Andre, and A. Morel, 1996: Oceanic

primary production 2. Estimation at global scale from satellite (coastal zone color scanner) chlorophyll. Global

Biogeochem. Cycles, 10, 57-69.

Longhurst, A., S. Sathyendranath, T. Platt, and C.

Caverhill, 1995: An estimate of global primary production in the ocean from satellite radiometer data. J. Plankton Res., 17, 1245-1271.
168 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Water Transport to the Upper Troposphere by

Convective Systems, as Inferred from Global

Lightning Data

Principal Investigator – Marcia Baker

Science Background

Water in the upper troposphere (UT) is supplied largely

by vertical advection in convective systems. The climatology and composition (liquid-to-ice ratio) of this convective water flux are poorly known and difficult to monitor directly.

We have proposed an exploratory study of the distribution of this flux in space and time, as inferred from

satellite observations of lightning flashes. The proposed

method is based on physical reasoning, numerical modeling, and in situ observations that suggest a strong correlation between the rate of water lofting in a convective

thunderstorm and the lightning flash rate from the storm,

particularly in continental locations.

Science Goals

The goal of this investigation is to make estimates of the

climatology of liquid water and ice fluxes to the UT from

satellite lightning data. The focus will be on continental

storms. The condensate data will be useful as a source

term for stratiform anvils where horizontal advection of

condensate from convective cells accounts for 60-75%

of the stratiform condensate.

Current Activities

Mass flux, water content, and lightning observational data

are being used together with our 1.5-dimensional numerical thunderstorm model to investigate the vertical water

flux—lightning flash rate correlations. Current investigations are utilizing data collected at the New Mexico

(1984) and Convection and Precipitation Electrification

(CaPE) (1991) field projects. From this combination of

observations and model results, we will develop regional

algorithms relating flash rate to the water fluxes in these

regions and will expand the study to other continental regions where lightning is commonly present.

The results will be compared with published

climatologies and independent modeling studies.

The numerical model utilizes cloud dynamics, a

simple representation of turbulent mixing and entrainment,

explicit microphysics, electrification, and a lightning parameterization to model a single-cell thunderstorm. The

lightning parameterization is being expanded to include

the impacts of microphysics on lightning initiation based

on the results of our recent theoretical study of lightning

initiation from hydrometeors.

Use of Satellite Data

Global lightning data are being acquired by both the Optical Transient Detector (OTD) aboard the Microlab-1 satellite as well as the Lightning Imaging Sensor (LIS) on

the TRMM observatory. Both instruments are able to give

estimates of the flash rates of storms they observe. Using

the appropriate regional algorithm, these flash rates will

then be used to produce a regional map of estimated water flux in each season.

Participation in Field Programs

We plan to participate in the Cloud Electrification Studies using Aircraft and Radar (CESAR) project now being

planned for the year 2000.

Principal Investigator

Marcia Baker

Marcia Baker received her Ph.D. in Physics from the

University of Washington in 1971 and is a Professor of

Atmospheric Sciences and Geophysics at the University

of Washington. She and her students have worked on various aspects of cloud physics. These include projects concerning the role of entrainment in modifying cumulus

cloud properties, aerosol impacts on the albedo of marine

stratocumulus, laboratory, and numerical studies of ice

particle microphysics, and theoretical, laboratory and field

studies of cloud electrification. She is a Fellow of the

American Meteorological Society.

References

Baker, M., H. Christian, and J. Latham, 1995: Quart. J.

Roy. Meteor. Soc., 121, 1525-1549.

Gamache, J.F., and R.A. Houze, 1983: Water budget of a

Mesoscale Convective System in the Tropics. J. Atmos.

Sci., 40, 1835-1850.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 169

Schroeder, V., M.B. Baker, and J. Latham, 1998: Corona

initiation from colliding hydrometeors. Quart. J. Roy.

Meteor. Soc., submitted.

Solomon, R., and M.B. Baker, 1996: J. Geophys. Res.,

101, 14983-14990.

Solomon, R., and M.B. Baker, 1998: J. Geophys. Res., in

press.

Udelhofen, P., and D.L. Hartmann, 1995: The influence

of tropical cloud systems on the relative humidity in the

upper troposphere. J. Geophys. Res., 100, 7423-7440.

Investigation URL

http://www.geophys.washington.edu/Surface/

Atmospheric/
170 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Global Water Cycle: Extension Across the

Earth Sciences

Principal Investigator – Eric J. Barron

Science Background

This Interdisciplinary Science Investigation focuses on

the global water cycle to determine the scope of its interactions with all components of the Earth system, and to

understand how it stimulates, regulates, and responds on

both global and regional scales. The primary research strategy involves generating a hierarchy of simulation models—from general circulation models of the atmosphere,

to mesoscale models, to basin-scale hydrologic models—

and validating them against EOS and other global observational data. The coarse spatial resolution of current global climate models is frequently cited by the U.S. Global

Change Research Program (USGCRP) as one of the major limitations in global-change predictions.

The hierarchy of models, in conjunction with EOS

observations, will make it possible to extend the predictive capability across a wide spectrum of spatial scales

for different regions of the Earth’s surface. The EOS observations will contribute to the development of an improved understanding of key processes, including cloud

cover and radiative transfer characteristics, and energy

and moisture fluxes at the interface of the atmosphere with

the oceans, cryosphere, and land surface.

Science Goals

The goals are to simulate future climate change on a global scale and, through coupling or “nesting” with higher

spatial resolution models, to develop predictions of climate change on the scales appropriate to human activity.

In linking climate and hydrologic forecast models, this

investigation also strives to address a critical area of uncertainty—changes in the water balance associated with

natural variability and climate change. The intent is to

produce regional-scale predictions of changes in water

balance and river flow as a function of climate change.

Such predictions are characterized by many uncertainties, and initially the investigation may only produce a

better assessment of the areas of uncertainties in producing regional-scale predictions. However, this understanding will undoubtedly lead to a better capability to do highresolution climate-model predictions on a global scale.

Current Activities

The focus of this effort is currently on the Susquehanna

River Basin of Pennsylvania, but the methodology is being developed for applications for any region of the globe.

Near-term plans include the Ohio River Basin and the

Tennessee River Basin. These efforts will allow us to contribute significantly to the GEWEX Continental International Project (GCIP) centered within the Mississippi

Valley. Future research efforts will expand to additional

regional foci, including oceanic and polar regions.

Use of Satellite Data

ASTER and MODIS surface radiance, reflectance, surface temperature, and vegetation measures will provide

inputs for the soil, vegetation, and atmosphere models

(SVATs) to be used in the model predictions of energy

and water fluxes. A major focus of the investigation will

be improved cloud parameterizations in mesoscale and

global atmospheric models, for which CERES and MISR

measurements will be a key for both cloud properties and

cloud radiative transfer.

EOS PM observations such as temperature, humidity, and precipitable water profiles from AIRS, AMSU,

and HSB will be utilized in model development and later

as a part of a regional 4-dimensional assimilation and global analysis of multiphase water and temperature and diabatic heating.

Scatterometry from SeaWinds will aid substantially

in the determination of air/sea energy and moisture fluxes,

and GLAS altimetry will be of considerable significance

in assessing model predictions of ice-sheet mass balance.

Participation in Field Programs

Participation in two field programs has added an important element to model development and validation. Participation in the CaPE Experiment (Convection and Precipitation Electrification) focused on methods to diagnose

large-scale land and atmosphere water budget components

with the objective of applying these techniques over regional-scale areas in conjunction with GEWEX. MAC

(Multi-sensor Airborne Campaign) Hydro ’90 was conducted over the Mahantango watershed in Pennsylvania,
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 171

the central test area for this investigation. The objective

of the campaign was to improve our ability to remotely

determine the near-surface soil moisture.

The development and verification of the nested hierarchy of simulation models is strongly tied to field programs, such as MAC Hydro and CaPE.

Co-Investigators

Bruce Albrecht - University of Miami

John Christy - University of Alabama Huntsville

Steven Goodman - NASA/Marshall Space Flight Center

Timothy Miller - NASA/Marshall Space Flight Center

Franklin (Pete) Robertson - NASA/Marshall Space Flight

Center

Thomas Warner - National Center for Atmospheric Research

Peter Webster - University of Colorado

The following are from Pennsylvania State University:

Thomas Ackerman

Richard Alley

Toby Carlson

Robert Crane

Thomas Gardner

Lee Kump

Arthur Miller

Gary Petersen

Donna Peuquet

Rudy Slingerland

Brent Yarnal

References

Capehart, W.J., and T.N. Carlson, 1997: Decoupling of

surface and near-surface soil water content: A remote sensing perspective. Water Resour. Res., 33, 1383-1395.

Carlson, T.N., and D.A.J. Ripley, 1997: On the relation

between NDVI, fractional vegetation cover, and leaf area

index. Remote Sens. Environ., 62, 241-252.

Christy, J.R., R.W. Spencer, and W.D. Braswell, 1997:

How accurate are satellite ‘thermometers’? Nature, 389,

342-343.

Jenkins G.S., and E.J. Barron, 1997: Global climate model

and coupled regional climate model simulations over the

Eastern United States: GENESIS and RegCM2 simulations. Glob. and Planet. Change, 15, 3-32.

Lakhtakia, M.N., B. Yarnal, D.L. Johnson, R.A. White,

D.A. Miller, and Z. Yu, 1998a: A simulation of river-basin response to mesoscale meteorological forcing: The

Susquehanna River Basin Experiment (SRBEX). J. Am.

Water Resour. Assoc., in press.

Investigation URL

http://www.essc.psu.edu
172 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Interdisciplinary Studies of the Relationships

Between Climate, Ocean Circulation,

Biological Processes, and Renewable Marine

Resources

Principal Investigator – Ian J. Barton

International Sponsor – Australia

Science Background

The CSIRO Marine Laboratories employs physical,

chemical, and biological oceanographers and fisheries

scientists in its new Division of Marine Research. The

recent amalgamation of the Divisions of Fisheries and

Oceanography has strengthened the interaction between

these scientists, especially in the fields of this Interdisciplinary Investigation. Funding for the Cooperative Research Center (CRC) at the University of Tasmania is now

secure for the next six years, and the close collaboration

between the CSIRO and the CRC continues. This investigation aims to integrate current and new research projects

that use existing satellite data in a way that ensures the

expected benefit from the application of the data to flow

through the EOS program. The projects will benefit from

the Laboratories’ substantial capability in satellite-data

acquisition and processing. This capability includes Land X-band direct data reception coupled with the ability

to process these data in near-real-time.

In its initial phases, the investigation was largely

observationally based, but now the activities are being

complemented by the use of numerical models that can

assimilate EOS remotely sensed and other data. Satellite

data from current and future programs will be used to

develop tools for the management of Australia’s Exclusive Economic Zone (EEZ). These will be available for

use by resource managers in studies of a wide variety of

problems, including pollution, dispersion of fish and pest

larvae, and search and rescue. They will be used for Goals

2 and 3 below of our EOS Interdisciplinary Investigation. A second global model is used to study the Indian

Ocean, and is intended to become part of a global coupled

model (in collaboration with other Australian institutions)

for studying climate change and variability, with particular emphasis on the Australian region. It will be used to

further our work on Goals 1 and 3 below.

Science Goals

We have three goals:

1) To improve the quantification of air-sea interaction

and oceanic heat storage, for the purposes of determining the ocean’s role in climate variability and

change. EOS satellite data are imperative to extend

these studies to regional and global scales

2) To examine the carbon cycle in the waters surrounding Australia and its influence on the global carbon

cycle.

3) To address the implications of interannual variability and long-term change in the regional oceanography for marine ecosystems, and commercial fisheries in particular.

Current Activities

Recent activities have included:

• Continuing validation of satellite-derived products using ground-based data. These include the verification

of TOPEX/Poseidon sea levels using tide gauges in

northern Tasmania and the Pacific and Indian Oceans,

sea-surface temperature using ship-borne radiometers,

and ocean-color products using a suite of ship instruments.

• Validation of net heat flux measurements during TOGACOARE by explicit ocean heat budget closure, to an

accuracy of better than 10 W/m2 over a few days

(Godfrey et al., 1998). These activities have now extended to studies over the tropical Indian Ocean.

• Optimal interpolation techniques have been developed

for application to NOAA/NASA Pathfinder SST data

sets. These techniques are being further developed to

allow interpolation in both space and time for combined

altimeter and SST data sets. Analyzed data will be ap-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 173

plied to studies of the East Australian and Leewin Currents.

• Participation in the TOPEX Extended Mission to use

altimeter and other satellite data to improve our understanding and prediction of climate variability and

change in the Australian region.

• Completion of several deep hydrographic sections for

the World Ocean Circulation Experiment (WOCE), including seven from Tasmania to Antarctica. Thirty occupations of a high-density expendable bathythermograph (XBT) line between Tasmania and Antarctica

have been obtained since 1992.

• Continuation of a series of voyages to determine the

spatial and temporal variability in carbon sources and

sinks in the Southern Ocean.

• Three ocean-color/optics voyages have been completed

in the Southern Ocean. These studies will be used to

relate remotely sensed data to measurement of ocean

biological and production parameters, as well as to assist in the development of primary production models.

Such models are being developed using historic CZCS

data as well as the new data from SeaWiFS. A regular

coastal ocean-color ground-truth collection program has

commenced. These measurements will also assist in the

assimilation of MODIS ocean-color data into carboncycle models .

• Development of a new research program into impacts

of climate variability in marine ecosystems and fisheries, making use of ongoing field research in southeastern Australia and northern Australia.

• Development of techniques to assist in the understanding and management of Australia’s Exclusive Economic

Zone. This includes techniques for assimilating altimeter and other satellite data into numerical models. Preliminary results indicate that combining satellite data

from altimeters, scatterometers, and AVHRR-type instruments should revolutionize our ability to keep track

of the copious eddies found around Australia. We anticipate that this project will provide a major integrating tool for the work of the Marine Laboratories.

Use of Satellite Data

The development of the new models greatly increases our

use of satellite data, particularly from AVHRR and from

the TOPEX/Poseidon and ERS-1 altimeters. Our studies

are also now using wind scatterometer data from ERS

and other satellites. We so far work on a range of projects

using remotely-sensed data:

• Development of “synthetic XBTs,” in which we use

XBT data along existing lines in the Indian Ocean to

estimate temperature anomaly profiles from surface

steric height and SST alone. It is proposed to use these

to complement the (very sparse) XBT data set throughout the Indian Ocean, using altimeter and AVHRR data.

• Use of optimal interpolation techniques in the development of sea-level maps (and associated synthetic

XBTs) in the eddy-rich Tasman and Coral Sea region,

for use in understanding, modeling, and management

of the EEZ in this region.

• Use of CSIRO-generated AVHRR maps in studies of

interannual variability of current systems around Australia, and in the application of SST and ocean color to

commercial fisheries.

• Analysis of seasonal and interannual variation in the

low-resolution historical CZCS pigment data for the

Australian region has been essentially completed. A

similar analysis of the high-resolution data for the areas of the East Australia and Leeuwin currents is

planned. These data will now be complemented by locally received SeaWiFS data. CZCS pigment data are

also being used to model seasonal variability in the

Southern Ocean carbon cycle.

• Data from geostationary and polar-orbiting satellites

have been used to map solar radiation in Australian

ocean regions including fields of UV-B radiation for

biological studies.

• Southern Ocean Assimilation modeling, aimed at assimilating the time-varying TOPEX/Poseidon altimeter

data into a prognostic primitive equation model, and

diagnosing the role of eddies on the transport of momentum, heat, and freshwater. Our archive of AVHRR

data will be used to assess the heat transport of eddies

in the East Australian Current.

• Development of improved techniques for the derivation of SST from satellite data. These studies are combined with a joint validation study with the Australian

Institute of Marine Sciences.

Participation in Field Programs

Since 1990, the investigators in this study have led many

voyages using the three research vessels based in Hobart;

namely, the Franklin, Southern Surveyor, and Aurora Australis. Most recently these have included voyages to the

tropical Indian Ocean and Indonesia to study ocean heat

fluxes, voyages to the Southern Ocean for ocean-color/

optical measurements, and regular hydrographic sections

both in the Indian and Southern Oceans in support of

WOCE and other international programs.
174 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Principal Investigator

Ian J. Barton

Ian Barton graduated with B.Sc. and Ph.D. degrees from

the University of Melbourne in 1972. He joined the

CSIRO Division of Meteorological Physics the following year and worked on the use of airborne microwave

radiometry to determine soil-moisture content. During a

year at Oxford University, in 1979-80, as a Research Fellow, his attention turned to satellite data—especially the

measurement of sea-surface temperatures from infrared

radiometers. This initial sojourn at Oxford University saw

the start of the European ATSR program, and subsequent

extended visits to the Rutherford Appleton Laboratory in

the UK during 1986 and 1993 consolidated the joint UKAustralia Program in ATSR. Ian Barton has published

widely on the analysis and application of infrared satellite data, and he currently collaborates in the scientific

programs of Japan’s NASDA and Europe’s ESA, as well

as with NASA. The latter collaboration includes membership of the MODIS Science Team, where he has a responsibility for the development of algorithms for the determination of sea-surface temperatures.

Co-Investigators

Graeme Pearman - CSIRO Atmospheric Research

John Wilkin - University of Aukland, New Zealand

The following are from the Marine Laboratories of the

Commonwealth Scientific and Industrial Research Organization:

John Church

George Cresswell

Peter Craig

Chris Fandry

Stuart Godfrey

Vince Lyne

Denis Mackey

Gary Meyers

John Parslow

Chris Rathbone

Ken Ridgway

Steve Rintoul

Bronte Tilbrook

Paul Tildesley

Susan E. Wijffels

The following are from the University of Tasmania:

Nathan Bindoff

Richard Coleman

Manuel Nunez

Jeorg Wolff

References

Barton, I.J.,1995: Satellite-derived sea surface temperatures: current status. J. Geophys. Res., 100 (C5), 8777-

8790.

Godfrey, J.S., R.A. House, R.H. Johnson, R. Lukas, J.-L.

Redelsperger, A. Sumi, and R. Weller,1998: The Coupled

Ocean Atmosphere Response Experiment (COARE): an

interim report. J. Geophys. Res., in press.

Mackey, D.J., J. Parslow, H.W. Higgins, F.B. Griffiths,

and J.E. O’Sullivan, 1995: Plankton productivity and biomass in the western equatorial Pacific: biological and

physical controls. Deep Sea Res., 42, 499-533.

Michael, K.J., M. Nunez, and G.A. Meyers, 1994: Validation of tropical ocean-atmosphere heat fluxes from

marine data against a satellite-based method. Int. J. Climatology, 14, 429-437.

Nilsson, C.S., and P.C. Tildesley, 1995: Imaging of oceanic features by ERS 1 synthetic aperture radar. J.

Geophys. Res., 100, 953-967.

Rintoul, S.R., J.-R. Donguy, and D. Roemmich, 1997:

Seasonal evolution of upper ocean thermal structure between Tasmania and Antarctica. Deep Sea Res., 44, 1185-

1202.

Walker, A.E., and J.L. Wilkin, 1998: Optimal averaging

of NOAA/NASA Pathfinder satellite sea surface temperature data. J. Geophys. Res., in press.

White, N.J., Coleman, R., Church, J.A., Morgan, P.J., and

Walker, S.K., 1994: A southern hemisphere verification

for the TOPEX/Poseidon satellite altimeter mission. J.

Geophys. Res., 99 (C12), 24505-24516.

Wilkin, J.L., J.V. Mansbridge, and J.S. Godfrey, 1995:

Pacific Ocean heat transport at 24 ̊N in a high resolution

global model. J. Phys. Oceanogr., 25, 2204-2214.

Investigation URL

http://www.marine.csiro.au
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 175

River Flooding and Global Environmental

Change: A Multi-Sensor Approach

Principal Investigator - G. Robert Brakenridge

Science Background

Extreme floods occur when the incoming water discharge

to a river reach greatly exceeds the system’s normal conveyance capacity. At such times, and along some but not

all valley reaches, discharge cross-sections broaden to

include extensive floodplains, tens of kilometers in width.

This direct runoff component of the Earth’s hydrological

cycle can be directly observed and measured by a variety

of orbital remote sensors.

Despite their direct effects on human affairs, the geographic location, extent, frequency, and magnitude of extreme river floods are poorly measured at present. Compared to meteorological data, international streamflow

data sharing is far from complete, and flood peak discharges are either unmeasured or are unavailable for many

nations. Even within the technologically developed nations, large floods commonly exceed gaging station design, or destroy the stations. However, the assessment of

flood risk is directly dependent on such flood-discharge

measurements and also on inundation-limit mapping, and

both can be carried out or assisted by remote sensing.

There also is utility in obtaining a global record of

such events, because, as the Earth’s climate changes, the

geographic patterns and frequency of extreme meteorological events will also change.

Flooding in both monsoonal and extra-tropical regions of the world is sensitive to air-sea interactions such

as those associated with the El Niño/Southern Oscillation teleconnection. Such linkages indicate the eventual

feasibility of interannual prediction of extreme floods, but,

at present, it is not possible to characterize temporal trends

or validate model predictions because the required systematic observations of flooding at the global scale are

lacking. Socio-economic data also indicate that some years

are more flood-prone than others, but consistent physical

measurements of these same events are needed in order

to understand the climatic causation. This EOS IDS project

is using the era of sustained multi-sensor Earth observation from space to observe and measure extreme floods

on a global basis, and to analyze their causation. The research will employ Terra and other remote-sensing data

sources to provide basic information about flooding as a

global-change phenomenon, and it will thereby allow testing of hypotheses and validation of model predictions that

concern interannual-to-interdecadal global variations in

flooding and their resulting societal effects.

Science Goal

Much of the EOS science agenda concerns the Earth’s

hydrological cycle. At least the large flood event outliers

in most river flow series can be measured by EOS Terra

and other spacecraft. Very large floods commonly overwhelm engineering control structures, so, along some or

all river reaches, floodwater spills through or over levees

onto the floodplain. Along many less-regulated rivers, the

entire floodplain temporarily becomes the river’s channel. Even at coarse spatial resolution (e.g., AVHRR’s 1

km), many river floods are observable and, when remote

sensing is combined with auxiliary data sets, flood magnitudes can be assessed. At higher spatial resolution, aspects of flow dynamics can be observed. Finally, if adequate topographic data for the floodplain and channel

are available, flood flow modeling can be validated by

remote sensing and peak discharge estimates can be obtained.

Our primary goal is to produce an annual set of globally consistent observational data concerning very large

flood events. These data will then be used to characterize

and to classify such events, to assess their magnitude, and

to analyze their causation. By accumulating consistent data

each year, we expect to also compute global and regional

flood indices, and thereby to determine on both a large

region and global basis the year-to-year changes in extreme flood frequency. The investigation thereby complements projects focusing on changes in the mean state of

the Earth’s hydrosphere

Current Activities

Late in 1997, several months after project initiation, we

began employing AVHRR for flood inundation mapping.

This methodology has been designed as preparation for

the MODIS data stream, which will increase spatial and

spectral resolution and thus improve water/land discrimination.

Our WWW site currently provides daily updates of

flooding worldwide. For each new flood event, AVHRR

multispectral image data are corrected for sun-angle ef-
176 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

fects, calibrated according to current sensor information,

and geometrically rectified to a latitude and longitude map

coordinate system. A variety of image enhancement and

classification techniques are then used to identify flooded

areas. The enhanced image data are imported into a Geographic Information System (GIS) and co-registered to

the GTOPO (updated global topography in digital format) digital topography; these layers are then, in turn,

overlain by the Digital Chart of the World vector data for

streams and rivers, roads, railroads, utilities, and human

settlements. For example, images and maps were created

for the late 1997 extreme flooding in Somalia and adjacent regions, and the UN-supported Relief Web site made

available these outcomes for the international disaster relief effort. Sample image maps are found at:

http://www.reliefweb.int/mapc/afr_horn/cnt/som/

somdfo1.html

http://www.reliefweb.int/mapc/afr_horn/cnt/som/

somdfo2.html

http://www.reliefweb.int/mapc/afr_horn/cnt/som/

somdfo3.html.

We are actively involved in studies of 1998 El Niñoinduced flooding in California and other locations in the

Western U.S. Radarsat SCANSAR data are being obtained, and a fast-delivery pathway from the Prince Albert,

Canada, receiving station to the Alaska SAR Facility and

thence to us has been developed. Two of us are performing field investigations of 1998 flooding in the Central

Valley and in support of the remote-sensing data acquisitions.

We have established a formal collaboration with a

group of Chinese scientists based at the Chinese Remote

Sensing Satellite Ground Station in Beijing. Radarsat

SCANSAR data are being obtained for the summer monsoon/tropical storm season of 1998 for a set of 7 critical

rivers in southern and eastern China. These data will be

downloaded to their station at our request, and the SAR

image data will be made immediately available to both

groups. After a December, 1997 meeting, we also requested early ASTER imaging of these same valley

reaches for 1999. The Chinese side is also providing much

in situ, field-based data for these river reaches.

This IDS project includes flood geomorphology and

hydrology, flood climatology, and remote sensing expertise. Extreme river floods are a synthetic outcome from a

panoply of meteorological and ground surface variables,

including: unusual rainfall events, antecedent soil moisture, snow-melt contributions, frozen-ground status, watershed soil composition, vegetation cover and land use,

watershed topography, watershed geometry, and drainage density. Some large floods are associated with very

temporary and perhaps stochastic anomalies in atmospheric circulation patterns; others are related to morepersistent atmospheric changes and to phenomena such

as El Niño. Still others are, on occasion, the nearly direct

results of drastic watershed modifications. As an example,

and along one critical river reach in China (the Dong Ting

lakes region), the frequency of large floods is increasing

due to channel bed and lake aggradation; this increased

flooding will continue to occur with or without climate

change. The IDS team is employing its different but

complementary disciplinary skills around the common

focus of understanding the causation of extreme flood

events in a global context.

Uses of Satellite Data

A multisensor approach is needed for three reasons:

1) Floods occur across a range of spatial scales, and

large-ground-coverage sensors are needed in order

to provide consistent overall magnitude estimates for

geographically extensive events. We are currently

using AVHRR data for this purpose, but will eventually move to MODIS.

2) For floods along many river floodplains, that range

in widths from tens of kilometers to only few kilometers, the 1-km resolution of AVHRR is barely adequate for flood-limit mapping, or is inadequate. Thus

higher-resolution sensors, such as Landsat ETM,

ASTER, or Radarsat are useful, and can also help to

validate measurements obtained by the lower resolution sensor.

3) Floods are temporally limited and cloud cover is a

severe constraint: the sensor must either have a frequent revisit capability (e.g., AVHRR and MODIS)

and thus utilize gaps in cloud cover, or a radar sensor

may be required.

Although issues of sensor calibration are important

to some aspects of our work (e.g., retrieval of sediment

concentration data), we also can make use of many different sensors, calibrated or not, and in different orbits,

as flood events are followed in time. Finer temporal sampling also facilitates the determination and acquisition of

peak overbank flooding conditions and thus better peak

magnitude estimates.

We also require global terrain and hydrological data

sets. ESA and the Joint Canadian-American research and

applications program using radarsat data (called ADRO)

are currently providing selected orbital SAR data, including some interferometric data useful for river-reach topography. A global hydrology data facility in Germany is

being tapped for available in situ records of extreme

floods, and our Chinese collaborators are assisting us in

obtaining in situ data for the study sites in their nation.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 177

With support from the National Science Foundation,

Dartmouth will soon install a high-speed network connection between its campus in Hanover, New Hampshire,

and the NSF-funded Very-high-speed Backbone Network

Service (vBNS). Dartmouth has joined a consortium of

New England colleges and universities that will access

the vBNS and Internet 2 through the Boston University

POP. The DS-3 line from the Boston University POP will

terminate at a router or switch in the Kiewit Computation

Center at Dartmouth. The upgraded campus backbone

includes extra fiber, so dedicated 100-Mb fiber paths will

become available to individual laboratories such as the

Flood Observatory. This will place this IDS project’s computers just two network hops from the vBNS POP.

Participation in Field Programs

Most of the six co-investigators are field-based scientists.

K. Prestegaard has been working since 1994 in the Raccoon Creek drainage that was severely affected by the

1993 Mississippi Valley flood. She also conducted a field

study in the Red River Valley of North Dakota in 1997, in

cooperation with USGS workers, and the team has selected the Great Flood of 1997 as the topic of its first

group-authored research paper. L. Mertes continues field

studies supporting flood remote sensing in Amazonia, in

Georgia, and in Iceland. Brakenridge is investigating an

extreme flood event in southern Vermont that occurred in

the early summer of 1997, as well as late Holocene records

of extreme flood events preserved in this region. He also

continues work on the Mississippi Valley flood of 1993

in collaboration with Jim Knox of the University of Wisconsin. The Dartmouth workers are collaborating with the

nearby Remote Sensing/GIS facility of the U.S. Army

Corps of Engineers Cold Regions Research and Engineering Laboratory, who are using AIRSAR/TOPSAR data

obtained at our request for the Illinois River Valley as

validation for agency watershed models.

With our Chinese colleagues, a small watershed, already heavily instrumented, has been selected for combined field/remote sensing study, and much information

has been compiled concerning its long-term hydrological

history. We plan to expand collaboration in this regard,

with an emphasis on flood responses.

Principal Investigator

G. Robert Brakenridge

G. Robert Brakenridge received his M.S. and Ph.D. degrees from the Geosciences Department of the University of Arizona in 1979 and 1982. He held a German Academic Exchange Service postdoctoral award at the University of Duesseldorf in 1982 and taught at Wright State

University from 1983-1987. He joined the faculty of

Dartmouth College in 1987, was a Jet Propulsion Laboratory Visiting Senior Scientist at NASA Headquarters in

1991-1992, and was made a Fellow of the Geological Society of America in 1992. His research is presently focused on the emerging discipline of flood remote sensing.

Co-Investigators

Victor R. Baker - University of Arizona

Katherine K. Hirschboeck - University of Arizona

Leal A. K. Mertes - University of California, Santa Barbara

Karen Prestegaard - University of Maryland

William S. Warner - Jordforsk, Centre for Soil and Environmental Research, Norway

References

Brakenridge, G.R, B.T. Tracy, and J.C. Knox, 1998: Orbital remote sensing of a river flood wave. Int. J. Remote

Sens., 19, 1439-1445.

Ely, L.L., Y. Enzel, and D.R. Cayan,1994: Anomalous

North Pacific atmospheric circulation and large winter

floods in the southwestern United States. J. Climate, 7,

977-987.

Mertes, L.A.K., G.R. Brakenridge, K.K Hirschboeck, K.

Prestegaard, and W.S. Warner, 1996: River Flooding and

Global Environmental Change: A Multi-Sensor Approach.

EOS, Transactions, American Geophysical Union.

Mertes, L.A.K., M. Smith, and J.B. Adams, 1993: Quantifying sediment concentration in surface waters of the

Amazon River wetlands from Landsat images. Remote

Sens. Environ., 43, 281-283.

Seeley, K.C., L.A.K. Mertes, and B. Laurent, 1997: Field

Measurements of Hydraulic Roughness on the Altamaha

River Floodplain, Georgia. EOS, Transactions, American

Geophysical Union.

Bingyuan, Z., and L. Donghang,1988: The relationship

between the El Niño events and the drought or excessive

rain of Northwest China during 1845 to 1988. Scientia

Atmospherica Sinica, 16, 185-192.

Investigation URL

http://www.dartmouth.edu/artsci/geog/floods/
178 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Collaborative Research: Modeling of N2 and

CO2 Fixation by the Oceanic Diazotroph

Trichodesmium

Principal Investigators – Douglas G. Capone

Edward J. Carpenter

Science Background

N2 fixation by the marine cyanobacterium Trichodesmium

has recently been recognized to provide an important

source of new nitrogen in oligotrophic open-ocean waters. Along with atmospheric deposition of combined N,

N2 fixation supports net uptake and export to depth of

atmospheric CO2. In contrast, new NO3, which enters the

euphotic zone from below the thermocline, is limited in

its ability to sequester atmospheric CO2 because it is accompanied by an influx of dissolved inorganic carbon

from depth.

Science Goals

Our synthesis and modeling effort has the following primary research objectives: 1) develop a global database

that incorporates all existing and accumulating field observations on Trichodesmium; 2) use this database to improve existing algorithms for estimating Trichodesmium

biomass from satellite ocean-color measurements and for

developing a new analytical model for predicting rates of

N2 and CO2 fixation from satellite-derived data; 3) use

the analytical model to provide global estimates of CO2

and N2 fixation and thereby new production by

Trichodesmium; 4) compare satellite-derived estimates of

surface winds, temperature, chlorophyll, and atmospheric

dust (as a surrogate for iron) with satellite-derived

Trichodesmium biomass estimates, in order to examine

the role of these factors as determinants for the distribution, abundance, and bloom formation of Trichodesmium

population; and 5) to interface our model as an input to

the global marine carbon model being developed by

Falkowski and Sarmiento.

Current Activities

We have undertaken quantitative field studies of the importance of the Trichodesmium as a primary producer and

major source of new nitrogen in the tropical oligotrophic

ocean in the South Pacific, North Atlantic, and Indian

Oceans collecting data on biomass, depth distribution, and

N2 and CO2 fixation by Trichodesmium along with standard oceanographic data. Relevant data are also available

from the western Pacific, Caribbean, and Sargasso Seas.

We are currently incorporating satellite remote sensing in

our Trichodesmium program, specifically to develop and

verify (using spectroradiometer measurements) algorithms

to estimate Trichodesmium biomass by ocean- color sensors (e.g., OCTS, SeaWiFS, MODIS). A database will be

compiled from these studies and made available to other

workers. We will use the database to develop an analytical model for estimating Trichodesmium-specific N2 and

CO2 fixation rates from satellite-derived Trichodesmium

biomass estimates. This model will be analogous to the

productivity algorithms which are being developed by

Falkowski et al. as part of the current SeaWiFS science

team efforts, but it will be based upon measured

Trichodesmium-specific production and N2 fixation versus irradiance relationships and observed Trichodesmium

distributions.

The ultimate objective of our synthesis and modeling efforts will be to provide quantitative global estimates

of N2 fixation rates as well as Trichodesmium-specific production, which will be coordinated, and intended to interface with, the efforts of Falkowski and Sarmiento, who

are developing a global oceanic productivity model, as

well as efforts of Siegel and co-investigators, who are

modeling nitrogen and carbon cycles in the north Atlantic.

Co-Principal Investigators

Douglas G. Capone

Douglas Capone is currently a professor at the University

of Maryland Center for Environmental Science at the

Chesapeake Biological Laboratory. He will join the faculty of the University of Southern California Wrigley Institute for Environmental Studies in September, 1999. He

received his Ph.D. in Marine Sciences from the Rosenstiel

School of Marine and Atmospheric Sciences, University

of Miami in 1978.

Edward J. Carpenter

Edward J. Carpenter is a professor in the Marine Sciences

Research Center at the State University of New York in

Stony Brook. He received his Ph.D. from North Carolina

State University in 1969 and had postdoctoral and Re-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 179

search Scientist exeprience at Woods Hole Oceanographic

Institution between 1969 and 1975. He has been at Stony

Brook since 1975.

Co-Investigators

Raleigh R. Hood - Horn Point Environmental Lab

References

Capone, D.G., A. Subramaniam, J.P. Montoya, M. Voss,

C. Humborg, A. Johannsen, R. Siefert, and E.J. Carpenter, 1998: An extensive bloom of the diazotrophic

cyanobacterium, Trichodesmium erythraem, in the central Arabian Sea. Mar. Ecol. Prog. Series, 172, 281-292.

Carpenter, E.J., H.R. Harvey, B. Fry, and D.G. Capone,

1997: Biogeochemical tracers of Trichodesmium. DeepSea Research I , 44, 27-38.

Capone, D.G., J. Zehr, H. Paerl, B. Bergman, and E.J.

Carpenter, 1997: Trichodesmium: A globally significant

marine cyanobacterium. Science, 27, 1221-1229.

Carpenter, E.J., and D.G., Capone, 1992: Nitrogen fixation in Trichodesmium blooms. Chapter 13, pp. 211-217.

In: Marine Pelagic Cyanobacteria: Trichodesmium and

Other Diazotrophs. E.J. Carpenter, D.G. Capone and J.G.

Rueter (eds.) Kluwer Academic Publishers, Dordrecht,

Boston, London.

Capone, D.G., J.M. O’Neil, E.J. Carpenter, and J. Zehr,

1991: Basis for diel variation in nitrogenase activity in

the marine planktonic cyano-bacterium, Trichodesmium

thiebautii. Appl. Environ. Microbiol., 56, 3532-3536.

Carpenter, E.J., J.P. Montoya, J. Burns, M. Mulholland,

A. Subramaniam, and D.G. Capone, 1999: Extensive

bloom of N2 fixing symbiotic association in the tropical

Atlantic ocean. Mar. Ecol. Prog. Series, submitted.

(A) SeaWiFS image of total chlorophyll concentration in the Georgia Bight off the coasts of Florida and Georgia on October 30, 1998. The

chlorophyll concentration was calculated using the standard SeaWiFS Project OC2 algorithm. (B) Trichodesmium specific chlorophyll concentration from the same image derived using our algorithm.
180 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

An Historical and Modeling Comparison Study

of Four Coastal Upwelling Systems

Principal Investigator – Mary-Elena Carr

Science Background

Although coastal upwelling regions of the Eastern Boundary Currents (EBC) cover less than 0.5% of the world

ocean, it is estimated that they account for 11% of global

new production (Chavez and Toggweiler 1995) and 20%

of global fish catch (Pauly and Christensen 1995). Consequently, these regions play a disproportionate role in

the oceanic carbon budget. The high productivity of the

EBCs is due to the upwelling of cold nutrient-rich water

in response to seasonal equatorward winds along the northsouth continental margins. Additionally, the California

Current and Peru-Humboldt Current systems are characterized by strong interannual variability associated with

El Niño. The yield of 12 million metric tons of anchoveta

fishery off coastal Peru in 1971 accounted for one-sixth

of global fish catch between 1963 and 1972, prior to collapse of the stock in 1972 due to the combined effect of

El Niño and excessive fishing pressure (Bakun 1996). This

project consists of comparing the Canary, Benguela, California, and Peru-Humboldt Current regions using an integrated approach of satellite and in situ measurements

and modeling. We aim to understand the physical forcing

of biological productivity in these regions. An internally

consistent, simultaneous study of all sites can be done

only from space.

Modeling is integral to a study of this kind as it enables us to incorporate measurements of various aspects

of the system into a dynamical framework. Since we want

to characterize the biological response to physical forcing, increasingly complex parameterizations of the system allow us to identify relevant processes and compartments. For example, seasonal variation in chlorophyll concentration depends to first order on the seasonal cycle in

wind forcing, but there is also a latitudinal and seasonal

variation of the characteristics of the source water. Therefore the circulation of sub-thermocline waters is also relevant to understanding the observed patterns of phytoplankton abundance. Models of the biological system

alone provide upper and lower constraints for various rate

processes, such as photosynthesis, and especially those

involving trophic levels which are not at all accessible

via satellite, such as grazing.

An integrated approach of modeling and satellite observations is only effective when there is sufficient knowledge of in situ parameters. For example, ocean-color

measurements from space provide an estimate of nearsurface pigment concentration, but we rely on a combination of in situ measurements and models to extend this

estimate to one of euphotic zone biomass and productivity. The applicability of these models changes on short

space and time scales due to physical processes, as upwelled waters stratify or mix when transported off-shore

or when upwelling favorable winds cease. Likewise, if

the nutrient content or species composition of the upwelling source water change, the algorithms for primary

productivity will be affected. Thus, the highest possible

resolution of in situ conditions for different forcing regimes is needed to properly utilize and interpret satellite

measurements. On another level, although quasi-synoptic, the satellite data set is restricted in space and time.

For most parameters, there is no long-term historical time

series. This limitation of the satellite time series is compounded by the problem of coverage because of orbit characteristics and the presence of clouds. In situ measurements are necessary to complement, complete, and validate those made from spaceborne sensors. Additionally,

many parameters vital to the understanding of the environment cannot be measured from space: physical characteristics such as water column structure (e.g., mixedlayer depth and shear), chemical characteristics (e.g., concentration of nutrients), and biological characteristics (e.g.,

phytoplankton community composition or biomass of the

non-pigmented organisms).

Science Goals

There are two major goals to this project. The first goal is

to generate a historical database of atmospheric, physical, chemical, and biological oceanographic parameters.

This climatology will be placed on the World Wide Web

for community access. This climatology will be integrated

with the satellite climatology and will be the foundation

for a regional carbon-balance study for each coastal upwelling region. The second goal is to utilize the in situ

and satellite climatologies to develop and implement statistical and modeling studies of the controlling factors of

biological productivity and of the pathways of carbon flow.

Current Activities

We are in the process of collecting historical data to construct the climatological fields. The data available through

NOAA’s National Oceanographic Data Center (NODC)
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 181

have already been integrated and we are now adding data

from the Benguela region, provided by the South African

Data Center for Oceanography (SADCO) and for the PeruHumboldt Current region from the Instituto del Mar de

Peru (IMARPE). The programs to estimate averages on

pressure or density surfaces are already in place, as well

as to those carry out quality control. Likewise, there is a

prototype web page (still only for internal use) that provides easy access to plots and data. The present focus is

on the California Current region, where the most complete datasets are presently available. We are working on

a statistical budget of carbon and nutrients for the system.

The modeling studies are proceeding. The first approach uses a size-based ecosystem model (Moloney and

Field 1991) with parameterized physics. In our first study,

we compared the effect of periodic upwelling events on

two different parameterizations of the ecosystem (Carr

1998). We found that a more-complex food-web structure is less vulnerable to strong and frequent physical forcing than a model with a single phytoplankton and zooplankton compartment. The size-based model is fairly

complex from a biological standpoint, which, although

relatively realistic, makes it inefficient in terms of coupling to a circulation model. Thus, we are exploring alternative ways to incorporate size information into simpler ecosystem parameterizations. We have recently

coupled the size-based model successfully to a mixedlayer model and plan to start integrating it, or a simpler

version, with a circulation model.

Use of Satellite Data

We use a combination of ocean-viewing satellite observations, as the basic variables are measurable from space:

TOPEX/Poseidon to provide the large-scale flow fields,

wind direction and speed from NSCAT and/or ERS-1/2

for past periods and QuikSCAT in the near future; seasurface temperature from the Advanced Very High Resolution Radiometer (AVHRR); and ocean color from SeaWiFS (and OCTS for the 1996-1997 period). We look

forward to the launch of MODIS to provide concurrent

estimates of temperature and ocean color.

Participation in Field Activities

Although we do not participate actively in field programs,

we rely heavily on data collected through international

JGOFS and other past and ongoing sampling programs

of the study regions.

Principal Investigator

Mary-Elena Carr

Mary-Elena Carr has been a Research Scientist at the Jet

Propulsion Laboratory since 1996 where she studies biological oceanography with a focus on the interaction of

biological and physical processes in the upper ocean. Her

investigations are based on remotely sensed observations

of biological and physical oceanographic variables and

numerical simulations of the ecosystem and of the physical environment. She received her Ph.D. in Oceanography at Dalhousie University in 1991, where she researched

the physical constraints of primary production in the equatorial Pacific. She was awarded a Postdoctoral Fellowship at Oregon State University (1991-1993) to investigate the coupling of physical forcing and biological structure on very small vertical scales. As Marine Scientist at

the University of Rhode Island (1993-1996), she worked

with Tom Rossby on the pathways of transport and exchange in the North Atlantic Current. She is a member of

the SeaWiFS Science Team and of the Executive Council

of the SeaWiFS Science Team.

Co-Investigator

Edward J. Kearns - University of Miami

References

Bakun, A., 1996: Patterns in the ocean: ocean processes

and marine population dynamics. California Sea Grant

College System in cooperation with Centro de

Investigaciones Biologicas del Noroeste, La Paz, BCS

Mexico, 323 pp.

Carr, M.-E. 1998: A numerical study of the effect of periodic nutrient supply on pathways of carbon in a coastal

upwelling regime. J. Plankton Res., 20, 491-516.

Chavez, F., and J.R. Toggweiler, 1995: Physical estimates

of global new production: the upwelling contribution. In

Summerhayes, C.P., Emeis, K.-C., Angel, M. V., Smith,

R. L., and Zeitzschel, B., editors, Upwelling in the ocean:

modern processes and ancient records, pp. 314-320. John

Wiley and Sons.

Moloney, C.L., and J.G. Field, 1991: The size-based dynamics of plankton food webs. 1. A simulation-model of

carbon and nitrogen flows. J. Plankton Res., 13, 1003-

1038.

Pauly, D., and V. Christensen, 1995: Primary production

required to sustain global fisheries. Nature, 374, 255-257.

Investigation URL

http://oceans-www.jpl.nasa.gov
182 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The Yangtze Delta of China as an Evolving

Metro-Agro-Plex (China-MAP)

Principal Investigator – William L. Chameides

Science Background

A social and environmental experiment of unprecedented

proportions is taking place in China. The world’s most

populous nation is also its most rapidly developing. Moreover, the pace of China’s economic development is astounding. Economic and technological infrastructure that

took western nations centuries to realize, the Chinese hope

to develop in mere decades.

Will China be able to sustain this rate of development, while also absorbing the 15 million people added

to its population each year? This is a question of critical

importance to the Chinese and the world. With its Gross

Domestic Product (GDP) growing ~10% each year and

projected to exceed the GDP of the United States by the

turn of the century, China has become a major global economic force. The sustainability of China’s economy is

thus an issue of critical importance to us all. A key aspect

of this issue is food and nutrition. China’s population

growth alone will require significant increases in food

supplies. Determining how this demand for food will be

met is a complex calculus whose parameters are the subject of intense discussion and debate. A study provided

by China’s Information Office of the State Council

projects continued food self-sufficiency for the nation by

increasing grain production at a rate of about 1% per year.

However, this and other similar studies have yet to consider the effect of environmental change on China’s agriculture. The unprecedented economic and population

growth in China are bringing about profound changes in

the nation’s landscape and pollutant emissions. These will

significantly affect China’s regional climate and air quality. How will these environmental changes affect China’s

rice- and wheat-based agriculture? This is China-MAP’s

main focus.

Through a ten-year program of research and field

study, the China-MAP project will focus on four key and

interrelated issues:

Issue 1: An assessment of the effects of ground-level

ozone pollution and photochemical smog from

gaseous emissions of nitrogen oxides and volatile organic compounds on present-day and future agricultural yields of rice and wheat in

China.

Issue 2: An assessment of the effects of gaseous sulfur

oxide and nitrogen oxide emissions on acid deposition in China and its concomitant impact on

present-day and future agricultural yields of rice

and wheat in China.

Issue 3: An assessment of the effects of gaseous sulfur

oxide and particulate carbon or soot emissions

on regional climate in China and its concomitant impact on present-day and future agricultural yields of rice and wheat in China.

Issue 4: An assessment of the effects of land-use change

in China on regional climate and its concomitant impact on future agricultural yields of rice

and wheat in China.

These assessments will be carried out using a coupled

climate-atmospheric-chemistry-crop-yield modeling system driven by a geographically disaggregated database

of the socio-economic drivers of environmental change.

Both the modeling system and the database will be developed by the China-MAP Science Team and evaluated

using environmental data gathered in China from a ChinaMAP monitoring network as well as a series of intensive

field studies in the Yangtze Delta of China. By evaluating

the environmental and agricultural effects of various scenarios for economic growth in China, the modeling system can eventually be used to help identify the most promising pathways for sustainable economic development in

China.

Science Goals

The China-MAP research strategy is based on two guiding principles. The first is a multidisciplinary approach

to understanding the processes that affect China’s

economy and environment. The other is a focus on the

regional or mesoscale, the scale where environmental

change is most critically coupled to economic viability,

but with consideration of the couplings of the mesoscaleto-smaller scales (i.e., the misoscale) and larger scales

(i.e., the global scale).

Our objective is to elucidate how environmental factors in China are affected by and coupled to the underlying socio-economic drivers of environmental change.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 183

Thus, our research strategy starts with the socio-economic

factors as a given and then attempts to assess their impact

on the environmental and agricultural ecosystems of

China. More specifically, we will adopt existing databases

and models to first quantify the socio-economic drivers

of the environmental change in China, and then develop,

evaluate, and apply a hierarchy of models and field observations to assess the impact of these drivers on China’s

climate and environment, and, in turn, the impact of these

environmental perturbations upon agriculture in China.

Current Activities

China-MAP is currently in the first 3-year phase of an

anticipated 10-year lifespan. During this phase, the ChinaMAP Science Team is focusing on archiving a basic environmental Geographical Information System for China,

the development and evaluation of a coupled atmospheric

chemistry/climate/crop-response modeling system for

China, and the design and implementation of an atmospheric chemistry/terrestrial-ecosystem intensive field

study in the Yangtze Delta region scheduled to run from

the summer of 1999 through the summer of 2000 with

funding from the National Natural Science Foundation

of China. Satellite data are used in the study to document

land-use and land-cover changes in the study area and to

characterize meteorological fields needed to drive our

modeling system.

Use of Satellite Data

China is a huge country of diverse physical, chemical,

and ecological characteristics. Significant pollutant emissions, as well as agricultural production of China’s two

main staple crops—wheat and rice—abound throughout.

To attempt a comprehensive study of the interactions between economic development, environmental change, and

agriculture over the entire nation would prove a daunting

and, likely, unrealistic task. Hence, we have chosen the

Yangtze Delta, located in the southeastern corner of the

nation, as a region for more-intense study. The Yangtze

Delta contains approximately 85 cities and townships in

addition to its one megacity—Shanghai. With a population of ~200 million, it is the most densely populated area

of eastern Asia. The Yangtze Delta region is also growing

by leaps and bounds and has been responsible for 25% of

China’s growth in GDP in the 1990’s and has become a

prime target for foreign investment. Perhaps not surprisingly in view of its recent economic growth, the role of

agriculture in the Yangtze Delta has changed significantly.

Historically a major supplier of grains to the provinces in

the north of China, the region is now barely food selfsufficient.

Principal Investigator

William L. Chameides

Chameides received his Ph.D. in 1974 from Yale University. After Yale, he spent two years as a Research Scientist at the University of Michigan and four years on the

faculty at the University of Florida. In 1980 he joined the

faculty at the Georgia Institute of Technology. He served

as Director of the School of Earth and Atmospheric Sciences from 1989-1994 and is currently Regents Professor of Earth and Atmospheric Sciences.

Chameides’ research focuses on atmospheric chemistry with emphasis on global biogeochemical cycles, biospheric/atmospheric interactions, air pollution, global

change, and urbanization. Through the development and

application of numerical algorithms and models and the

design and implementation of field studies, he endeavors

to elucidate the coupled chemical, physical, and biological processes that determine the chemical environment,

and thereby help identify pathways toward a sustainable

future. Dr. Chameides has authored or co-authored over

80 scientific publications, as well as a textbook on Biogeochemical Cycles and a National Academy of Sciences

book on Rethinking the Ozone Problem in Urban and

Regional Air Pollution.

In addition to his academic appointments, Chameides

plays a lead role in two multi-institutional, multidisciplinary research programs concerned with regional environmental change and the strategies for sustainable economic development. He is the Chief Scientist of the Southern Oxidants Study (SOS) and Director of SOS’ Southern Center for the Integrated Study of Secondary Air Pollutants (SCISSAP). Collectively, SOS and SCISSAP focus on understanding the causes and remedies for groundlevel ozone and fine-particle pollution in the Southern

United States. Chameides is the U.S.A. Study Director of

China-MAP, an international research program studying

the effects of environmental change on agriculture in

China, the world’s most populous and rapidly developing nation.

Among his various committee assignments,

Chameides also serves as Chair of: 1) the NARSTO Synthesis Team, a group of Canadian, Mexican, and U.S. scientists charged with writing the 1998 Assessment Document for the North American Research Strategy for Tropospheric Ozone; and 2) the National Research Council’s

Committee on Ozone Forming Potential of Reformulated

Gasoline, which is addressing the environmental effects

of ethanol and other oxygenates in reformulated gasoline.
184 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Co-Investigators

C. S. Kiang - Georgia Institute of Technology

G. Carmichael - University of Iowa

F. Giorgi - National Center for Atmospheric Research

Thomas Heller - Stanford University

L. Mearns - National Center for Atmospheric Research

Rosamond Naylor - Stanford University

V. Ramaswamy - GFDL, Princeton University

References

Brown, L., 1995: Who will feed China? Wake-up call for

a small planet, New York, Norton.

Chameides, W.L., P.S. Kasibhatla, J. Yienger, and H. Levy,

1994: Growth of continental-scale metro-agro-plexes,

regional ozone pollution, and world food production. Science, 264, 74-77.

Dentener, F., G. Carmichael, and Y. Zhang, 1996: The

role of mineral aerosol as a reactive surface in the global

troposphere. J. Geophys. Res., 101, 22,869- 22,889.

Elliott, S., et al., 1997: Motorization of China implies

changes in Pacific air chemistry and primary production.

Geophys. Res. Letts., 24, 2671-2674.

Giorgi, F., M.R. Marinucci, G. DeCanio, and G.T. Bates,

1993: Development of a second generation regional climate model (RegCM2). Part II: Cumulus cloud and assimilation of lateral boundary conditions. Mon. Wea. Rev.,

121, 2814-2832.

Kasibhatla, P., W.L. Chameides, and J. St. John, 1997: A

three-dimensional global model investigation of seasonal

variations in the atmospheric burden of anthropogenic

sulfate aerosols. J. Geophys. Res., 102, 3737-3759.

Mearns, L.O., and C. Rosenzweig, 1995: Formation of

climate change scenarios incorporating changes in daily

climate variability and application to crop models, In W.

Howe and A. Henderson-Sellers (eds.), Assessing climate

change: The story of the model evaluation consortium for

climate assessment, Chap. 15, Harwood Academic.

Streets, D., C. Cung, J. Krummel, and S. Haiping, Remote sensing of global change: Growth in China’s Jiangsu

Province. Int. J. Sustainable Development and World Ecology, 2, 1-10, 1995.

Investigation URLs

http://www-wlc.eas.gatech.edu

http://www-wlc.eas.gatech.edu/chinamap.html

Pollutant emissions and

crop production in China by

region. China-MAP is investigating the conflicts and

synergism between industrial activity and agriculture

in China with a special focus on the Yangtze (Region

6), a region with plentiful agriculture and pollutant emissions.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 185

Northern Biosphere Observation and Modeling Experiment (NBIOME)

Principal Investigator – Josef Cihlar

International Sponsor – Canada

Science Background

Numerous studies using general circulation models

(GCMs) have concluded that significant climate change

is likely to occur during the next century, principally as a

result of the rising concentration of anthropogenic greenhouse gases. Air temperature is predicted to increase more

at northern latitudes, and appreciable mid-continent drying has also been postulated. Such changes would strongly

influence the functioning of northern terrestrial ecosystems as well as, over time, their structure and geographic

distribution. They would in turn affect the climate because

of the biosphere-climate feedbacks, at both mesoscale and

GCM grid scales. The types and degree of likely ecosystem responses are not well understood but they will vary

with the biome under consideration (forest,

agroecosystems, wetlands, tundra) and the particular processes. In addition to climate change, natural ecosystems

are increasingly affected by human activities. A critical

issue in understanding the impact of climate change on

ecosystems is the relationship between processes operating at various spatial scales, from leaves to landscapes.

Satellite observations combined with flux data provide

the key measurement techniques to allow bridging this

range of scales for process studies and change monitoring.

Science Goal

The goal of the Northern Biosphere Observation and

Modeling Experiment (NBIOME) is to improve the understanding of the relationship between the climate and

the northern ecosystems, including their seasonal and interannual dynamics and their role in the global carbon

and hydrological cycles. The objectives of NBIOME are:

1) to develop and validate methods for the extraction of

biophysical parameters from optical and microwave satellite data for major Canadian biomes; 2) to develop methods for extending observations and model outputs across

a range of spatial scales, from stand to landscape and the

Canadian landmass; and 3) to use the satellite-derived parameters with data from other sources as input process

models for the assessment of ecosystem performance. Particular emphasis is being given to climate-related processes such as carbon uptake through photosynthesis; forest fire dynamics; the effect of climate on the terrestrial

carbon budget, especially in forests; and the changing

radiation regime over the landmass of Canada (e.g., surface radiation budget, UVB radiation, photosynthetically

active radiation, etc.)

Regarding Objective 1, the parameters of interest are

those which most closely characterize vegetation and its

functioning: land-cover type, land-cover change, leaf-area

index, absorbed photosynthetically active radiation, and

newly burned areas. Methods are being developed using

present satellite data, especially Advanced Very High

Resolution Radiometer (AVHRR) data over Canada as a

precursor of EOS MODIS data, and include refinements

of the processing techniques to compensate for subpixel

clouds and bidirectional effects. This work will enable

production of derived data sets for Canada during the prelaunch EOS period, using daily AVHRR coverage during

the growing season. Objective 2 addresses the problem

of scaling for dynamic processes, such as carbon uptake

and loss through fires, where temporal and spatial dynamics are intrinsically linked. This task has been approached through a combination of satellite-data-derived

products and spatially explicit models. The principal ecosystem variable of interest in Objective 3 is terrestrial primary productivity. To be practical, productivity models

should require a minimum of data that cannot be obtained

from satellites or cannot be cost-effectively obtained over

large areas. The focus of this study is on satellite data

sources and techniques that may be used to apply findings from the study areas at the regional level.

Current Activities

NBIOME Co-Investigators are engaged in activities related to all three objectives above. Regarding Objective

1, research has been carried out to develop and validate

algorithms for the extraction of leaf-area index, absorbed

photosynthetically active radiation, and land cover from

satellite optical data. Canada-wide products with a spatial resolution of 1 km have been produced from AVHRR

data for one or more years in the 1993-1998 period. They

include land cover (in 31 classes), leaf-area index and the

fraction of photosynhetically active radiation (at 10-day

intervals during the growing season), and forest fires (daily

hot spots during the growing season as well as total an-
186 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

nual fire scars). Various numerical simulation and inversion models have been developed in support of these products, including: an advanced bidirectional reflectance

model capable of capturing radiative-transfer processes

within a tree canopy and its generalized version suitable

for AVHRR data; a new technique for quantifying vegetation leaf area based on sub-canopy light penetration

regime; theoretically-based models for the estimation of

photosynthetically active and UVB radiation at the land

surface from satellite data; new procedures for extracting

land-cover information by optimally combining satellite

optical data at various resolutions; etc.

Objective 2 is being approached through a combination of satellite data at various resolutions (from ~30 m to

1 km), observation periods from 1 day to a growing season, and the use of the above satellite-derived products.

The third objective is pursued in two ways. Primary productivity is estimated using a detailed biogeochemical

cycling model (Boreal Ecosystem Productivity Simulator, BEPS), which computes daily net carbon uptake for

each 1 km2 of the landscape using some of the above products as well as meteorological and ancillary vegetation

data. The net forest ecosystem productivity (NEP) is estimated by considering two different conditions, old forests in which NEP is only due to climate change effects

(observed changes in the growing season length and air

temperature; observed changes in nitrogen deposition) and

disturbed forests (due to fire, insects, harvest).

Use of Satellite Data

The entire project is firmly based on the use of satellite

data. To date, the use of data from AVHRR has been emphasized. The GEOcoding and COMPositing system

(GEOCOMP) was built to produce full-resolution 10-day

composites over Canada’s landmass during the growing

season (every year since 1993), and methods have been

developed to reduce the noise resulting from the

compositing process. Higher level products have been

developed from the AVHRR data. The algorithms are

structured so that they can be transferred to EOS MODIS. A new processing system has been constructed that

will routinely generate the above higher level products.

Landsat is the principal source of fine-resolution data.

Participation in Field Programs

NBIOME Co-Investigators have actively participated in

BOREAS field campaigns (1993, 1994, 1996). In 1998

they carried out an LAI and FPAR validation program

which included 10 sites across Canada. Validation of NPP

outputs was carried out in 1997-1998 using BOREAS flux

tower measurements, and spatial validation of NPP commenced in 1999 at three sites (Quebec, Manitoba, Alberta).

A new effort is the development and validation of net ecosystem productivity data sets. Data from BOREAS and

both existing and new spatially explicit data sets are being used for this purpose.

Principal Investigator

Josef Cihlar

Josef Cihlar holds degrees in Soil Science, Physical Geography, and Remote Sensing. He is a senior research scientist at the Canada Centre for Remote Sensing where he

heads research activities in satellite data applications to

environmental issues at both large (landscape to global)

and local scales. His primary research interest has been

satellite monitoring of the characteristics and temporal

dynamics of the terrestrial biosphere.

Co-Investigators

Jean Beaubien - Canada Forest Service

Raymond Desjardins - Agriculture and Agri-Food Canada

Alain Royer - Universite de Sherbrooke

Brian Stocks - Canada Forest Service

The following are from the Canada Centre for Remote

Sensing:

Jing Chen

Wenjun Chen

Terry Fisher

Zhangqing Li

Philip Teillet

References

Chen, J.M. , and J. Cihlar, 1995: Plant canopy gap size

analysis theory for improving optical measurements of

leaf area index of plant canopies. Appl. Opt., 34, 6211-

6222.

Chen, J.M., and J. Cihlar, 1995: Quantifying the effect of

canopy architecture on optical measurements of leaf area

index using two gap size analysis methods. IEEE Trans.

Geosci. Remote Sens., 33, 777-787.

Chen, J.M., and J. Cihlar, 1996: Retrieving leaf area index in boreal forests using Landsat TM images. Rem. Sens.

Environ., 55, 153-162.

Cihlar, J., 1996: Identification of contaminated pixels in

AVHRR composite images for studies of land biosphere.

Rem. Sens. Environ., 56, 149-163.

Li, Z., J. Cihlar, X. Zhang, L. Moreau, and H. Ly, 1996:

The bidirectional effects of AVHRR measurements over

boreal regions. IEEE Trans. Geosci. Remote Sens., 34,

1308-1322.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 187

Chen, J.M., and J. Cihlar, 1997: A hotspot function in a

simple bidirectional reflectance model for satellite applications. J. Geophys. Res., 102, 25,907-25,913.

Cihlar, J., H. Ly, Z. Li, J. Chen, H. Pokrant, and F. Huang,

1997: Multitemporal, multichannel AVHRR data sets for

land biosphere studies: artifacts and corrections. Rem.

Sens. Environ., 60, 35-57.

Cihlar, J., J. Chen, and Z. Li.,1997: Seasonal AVHRR multichannel data sets and products for studies of surfaceatmosphere interactions. J. Geophys. Res. - Atmospheres,

102, 29,625-29,640.

Cihlar, J., J. Beaubien, Q. Xiao, J. Chen, and Z. Li, 1997:

Land cover of the BOREAS Region from AVHRR and

Landsat data. Canadian J. Rem. Sens., 23, 163-175.

Li, Z., L. Moreau, and J. Cihlar, 1997: Estimation of photosynthetically active radiation absorbed at the surface. J.

Geophys. Res., 102, 29,717-29,727.

Liu, J., J.M. Chen, J. Cihlar, and W. Park, 1997: A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ., 62, 158-

175.

Beaubien, J., J. Cihlar, G. Simard, and R. Latifovic, 1999:

Land cover from multiple Thematic Mapper scenes using a new enhancement - classification methodology. J.

Geophys. Res., in press.

Cihlar, J., J. Chen, Z. Li, F. Huang, R. Latifovic, and R.

Dixon, 1998: Can interannual land surface signal be discerned in composite AVHRR data? J. Geophys. Res. -

Atmospheres, 103, 23,163-23,172.

Cihlar, J., Q. Xiao, J. Beaubien, K. Fung, and R. Latifovic,

1998: Classification by Progressive Generalization: a new

automated methodology for remote sensing multichannel data. Int. J. Remote Sens., 19, 2685-2704.

Cihlar, J., R. Latifovic, J. Chen, and Z. Li, 1999: Nearreal time detection of contaminated pixels in AVHRR

composites. Canadian J. Remote Sens., in press.

Cihlar, J., J. Beaubien, R. Latifovic, and G. Simard, 1998:

Land Cover of Canada 1995 Version 1.1. Digital data set

documentation. Natural Resources Canada, Ottawa,

Ontario.

Cihlar, J., R. Latifovic, J. Chen, J. Beaubien, and Z. Li,

1999: Selecting high resolution sample in land cover studies. Part 1: algorithm. Remote Sens. Environ., accepted.

Cihlar, J., R. Latifovic, J. Chen, J. Beaubien, and Z. Li,

1999: Selecting high resolution sample in land cover studies. Part 2: application to estimating land cover composition. Remote Sens. Environ., accepted.

Li, Z., S. Nadon, and J. Cihlar, 1999: Satellite detection

of boreal forest fires, Part I: Algorithm development and

application. Int. J. Remote Sens., in press.

Li, Z., S. Nadon, J. Cihlar, and B.J. Stocks, 1999: Satellite detection of boreal forest fires, Part II: Algorithm validation and comparison. Int. J. Remote Sens., in press.

Li, Z., P. Wang, and J. Cihlar, 1999: A simple and accurate algorithm for retrieving surface UV-B irradiance from

satellite, Part I: Model development and simulation results. J. Geophys. Res., accepted.

Chen, J.M., S.G. Leblanc, J. Cihlar, R. Desjardins, and

J.I. MacPherson, 1999: Extending aircraft and towerbased CO2 flux measurements to a boreal region using a

Landsat TM landcover map. J. Geophys. Res.-Atmospheres, in press.

Chen, J.M., J. Liu, J. Cihlar, and M.L. Goulden, 1999:

Daily canopy photosynthesis model through temporal and

spatial scaling for remote sensing applications. Ecological Modeling, accepted.

Chen, W., J.M. Chen, D.T. Price, J. Cihlar, and J. Liu,

1999: Potential carbon benefit and cost of forest management options in Canada. Mitigation and Adaptation Strategies for Global Change, submitted.

Liu, J., J.M. Chen, J. Cihlar, and W. Chen, 1999: Net

primary productivity distribution in the BOREAS study

region from a process model driven by satellite and surface data. J. Geophys. Res., accepted.

Investigation URL

The results of NBIOME research have been published

in various international journals. A partial list can be

found at:

http://www.ccrs.nrcan.gc.ca/ccrs/eduref/ref/

biblioe.html

Examples of products derived by NBIOME Co-Investigators can be found at:

http://www.ccrs.nrcan.gc.ca/ccrs/tekrd/rd/apps/em/

cchange/ccemse.html
188 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Retrieval, Assimilation, and Modeling of

Atmospheric Water Vapor from Ground- and

Space-Based GPS Networks: Investigation of

the Global and Regional Hydrological Cycles

Principal Investigator – Jean O. Dickey

Science Background

Uncertainty over the response of the atmospheric hydrological cycle (particularly the distribution of water vapor

and cloudiness) to anthropogenic forcing is a primary

source of doubt in current estimates of global climate sensitivity (e.g., Lindzen 1994); conversely, the lack of detailed information regarding the effects of global change

on regional land-surface hydrology raises severe difficulties in evaluating its likely societal impact. Current satellite observations of the atmospheric watervapor field suffer from a number of restrictions which limit their usefulness for hydrological studies. At the same time, the lack

of a suitable global database forces assimilation schemes

to fall back on model-adjusted moisture fields which incorporate idealized physical parameterizations, greatly

limiting their value for climate research (e.g., Trenberth

and Guillemot 1995). For these reasons an intensive investigation of the hydrological cycle has become a centerpiece of the Earth Science Enterprise (ESE) and EOS,

both to acquire a robust database for theoretical and modeling studies of the relevant physical processes, and to

detect and monitor critical ongoing changes in the functioning of the climate system.

Fortunately, a variety of advanced techniques and sensors are beginning to shed new light on the atmospheric

hydrological cycle. One of the most promising of these

new approaches makes use of the sensitivity of the Global Positioning System (GPS) to the thermodynamic state,

and in particular the water vapor content, of the atmosphere through which the radio signals propagate (e.g.,

Bevis et al., 1992; Businger et al., 1996). This decade has

seen an explosion in the number of applications of GPS,

ranging from precise surveying (at the millimeter level)

to the landing of airplanes with positioning uncertainty

of a few centimeters. GPS offers a unique opportunity to

the atmospheric sensing community in that the extensive

system of satellites, receivers, and software has been put

in place primarily for purposes of geodetic positioning,

navigation, and tectonic studies. Thus, a large part of the

expense of installing and operating these networks is

shared with the geodetic community, sharply reducing the

marginal cost of atmospheric data obtainable from GPS

relative to that incurred by dedicated sensing systems.

Determinations from down-looking receivers and dedicated satellites placed in low Earth orbit (LEO) can also

be used to increase the vertical resolution and global coverage of the meteorological database provided by GPS.

Science Goal

The goal of this proposal is to lay the groundwork for the

successful exploitation of this unique resource by the atmospheric-sensing and modeling communities during the

lifetime of the EOS mission. Previous studies have shown

the ability of ground-based (e.g., Bevis et al., 1994;

Businger et al., 1996; Duan et al., 1996) and space-based

(Hajj et al., 1994; Ware et al., 1996) receivers to derive

accurate atmospheric data from GPS signals, and their

potential value to atmospheric analysis and forecasting

has been demonstrated by the assimilation of synthetic

GPS determinations into mesoscale models (Kuo et al.,

1993, 1995; Zou et al., 1995). Our strategy to derive the

maximum benefit for hydrological studies from the rapidly increasing GPS data stream will proceed in three

stages. Specifically, we propose to: 1)al GPS networks

on both regional and global scales, and from LEO receivers when they become available, using state-of-the-art

techniques; 2) employ both currently available and innovative assimilation procedures to incorporate these determinations into advanced regional and global atmospheric

models, and assess their effects on the simulation of the

hydrological cycle; and 3) apply the results from parts

(1-2) to investigate selected scientific issues of relevance

to regional and global hydrological studies.

Current Activities

The advent of the Global Positioning System offers a

unique opportunity to increase our knowledge of the atmospheric moisture budget through its sensitivity to the

water vapor content along the ray path. Our regional modeling effort will initially utilize data from all sites (40 at

the time of writing) of the Southern California Integrated

GPS Network (SCIGN), as well as down-looking receiv-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 189

ers to be situated on topographic features above the boundary layer (where most of the water vapor resides).

 We plan to retrieve and assimilate estimates of the

tropospheric zenith path delay at each SCIGN site as well

as occultations of rising and setting GPS satellites from

down-looking receivers, together with surface meteorology from suitably equipped sites, into a version of the

fifth-generation Penn State/NCAR mesoscale model

(MM5) adapted to Southern California to: 1) optimize

retrievals of precipitable water vapor (PWV), i.e., water

vapor integrated through the atmosphere, as well as vertical water vapor profiles; 2) assess the improvement in

the modeling of water vapor and other atmospheric variables that will result from the inclusion of the GPS measurements into the mesoscale model; and 3) enhance our

understanding of the regional dynamics of precipitation

and water vapor transport, and their interaction with topographic and surface features.

The first year saw the establishment of an archive of

GPS-based estimates of total zenith delay (TZD) data and

water vapor where applicable; the development of an automated quality-control capability is underway. The accuracy of the GPS estimates is being monitored, and the

investigation of systematic errors is ongoing using comparisons with water vapor radiometers. Meteorological

packages have been purchased and implementation is

underway. The accuracy and utilization of the TZD estimates has been improved by implementing a troposphere

gradient model. Development of an algorithmic capability to extract path-delay information from the downwardlooking space-based receivers is underway; two codes, a

ray-tracing code and an inversion code, are now being

tested with synthetic data sets. The MM5 mesoscale model

is being adapted for Southern California and OSSE experiments are underway. A forward model for the computation of TZD from the model’s prognostic variables

has been developed, and testing of the direct assimilation

of TZD into a version of MM5 incorporating the

orthometric heights of the GPS ground-based receivers

has begun, using the linearized adjoint of the forward

model. These results will be compared with the assimilation of zenith wet delay (ZWD) and PWV data, which

will become available once the meteorological packages

are installed at the GPS sites.

In our application of GPS determinations to global

hydrological studies, we will make use of the Goddard

Space Flight Center’s (GSFC) Data Assimilation Office’s

(DAO) physical space statistical-assimilation scheme

(PSAS) to assimilate retrievals of ground-based GPS data

from the global IGS and regional networks as well as occultation data from GPS low-Earth orbiters into GSFC’s

GEOS-1 global general circulation model. The current

IGS network consists of over 150 globally distributed sites,

whose number is rapidly increasing. The low-Earth orbiters which track GPS in an occultation geometry are

expected to retrieve accurate refractivity profiles in regions where water vapor is dense. Missions currently

planned which include space-GPS capabilities are Oersted, SAC-C, CHAMP, Sunsat and GRACE. The development of a quality-controlled database from these determinations will allow us to assimilate water-vapor-sensitive data with high vertical resolution into GEOS-2, to

optimize the retrieval of precipitable water as well as water

vapor and boundary-layer profiles, and to investigate the

ability of current climate models to simulate the global

hydrological cycle. Concomitant retrievals of temperature profiles in the upper troposphere, where water vapor

is scarce, will also benefit the GEOS-2 analysis.

Use of Satellite Data

The optimum use of satellite-derived data is the central

feature of the investigation. We will be utilizing the Global Positioning System, which consists of a constellation

of 24 Earth-orbiting satellites, global and regional networks of ground resources, and hardware, software, and

infrastructure for retrieving and analyzing the data collected by both ground- and space-based receivers. Traditionally used for high-precision geodesy, the GPS system

has recently emerged as an equally powerful tool in atmospheric studies, in particular climatology and meteorology. In fact, the geodetic applications and the atmospheric applications of the GPS system cannot be separated; in order to get the precise location of the receiver,

the delay suffered by the GPS signal while traversing the

atmosphere must be accurately known. The GPS-based

estimate of PWV, i.e., the total amount of water vapor in

the atmospheric column above a ground-based receiver,

can be inferred from a direct estimate of the TZD, with

the help of some ancillary information. We also plan to

access determinations from down-looking receivers and

dedicated satellites placed in low Earth orbit to increase

the vertical resolution and global coverage of the meteorological database provided by GPS. The refractivity profile can be derived using the assumption of hydrostatic

equilibrium, and calculated as a function of height. Temperature can be derived from density and pressure using

the equation of state for dry air. In regions where water

vapor is appreciable, some independent knowledge of temperature can be used to derive a water-vapor profile.

Intercomparisons of GPS products with those derived from

GOES/GMS, AIRS, MODIS, and AMSU-B are planned.

Participation in Field Activities

To more-carefully investigate systematic errors in the

measurement of atmospheric water vapor by GPS and

water vapor radiometer (WVR) instruments, a long-term

comparison of these two techniques was begun in June of

1996 at the Goldstone Deep Space Network tracking station located in the Mojave desert north of Barstow, CA.

During the course of this test, a GPS receiver equipped

with a high-precision pressure sensor recorded data continuously along-side a state-of-the-art WVR. This test has
190 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

so far yielded over 10,000 independent measurements of

atmospheric water vapor by the two techniques over a

wide range of atmospheric conditions. This large data set

represents an invaluable testbed for investigation of improved analysis strategies for both techniques. Systematic comparisons have also been made at an additional

number of sites. Particular emphasis is being placed on

the sites in SCIGN.

Principal Investigator

Jean O. Dickey

Jean O’Brien Dickey earned a Ph.D. in Physics from

Rutgers University (New Brunswick, NJ) and is currently

a Principal Member of the Technical Staff and Technical

Group Supervisor of the Space Geodetic Science and

Applications Group at the Jet Propulsion Laboratory (JPL)

California Institute of Technology. She has held research

positions at Caltech since 1977 [Research Faculty Appointment (1977-1980) on campus, JPL since 1980, Group

Supervisor beginning 1983]. Areas of interest include interdisciplinary studies involving the application of the

geodetic data to atmospheric problems, Space Geodesy,

Geodynamics and Atmospheric Dynamics, Angular Momentum Budget Studies of the Earth, Solid Earth-Atmosphere Interactions, Climate Studies, Earth Rotation and

Polar Motion. She has published over 100 articles. She

has served as the Chair on the National Research Council

Committee, Earth’s Gravity from Space, as President of

the Geodesy Section of the AGU, and as a member of

several editorial boards. She is active in international affairs and is currently the second Vice-President of the International Association of Geodesy (IAG). Honors include

Fellowships, in both AGU and IAG, Invited Discourse

(XXIInd International Astronomical Union General Assembly), Bowie Lecture (AGU), and Invited Lecture,

Frontiers in Geophysics (AGU).

Co-Investigators

John R. Anderson - University of Wisconsin, Madison

Yoaz Bar-Sever - Jet Propulsion Laboratory

Michael G. Bevis - University of Hawaii

Steven Businger - University of Hawaii

George Hajj - Jet Propulsion Laboratory

Arthur Y. Hou - NASA/Goddard Space Flight Center

Y.-H. Kuo - National Center for Atmospheric Research

E. Robert Kursinski - Jet Propulsion Laboratory

Steven L. Marcus - Jet Propulsion Laboratory

John Porter - University of Hawaii

David A. Randall - Colorado State University

Siegfried D. Schubert - NASA/Goddard Space Flight Center

Xiaolei Zou - National Center for Atmospheric Research

References

Bevis, M., S. Businger, T.A. Herring, C. Rocken, R.A.

Anthes, and R.H. Ware, 1992: GPS Meteorology: Remote

sensing of atmospheric water vapor using the global positioning system. J. Geophys. Res., 97,15,787-15,801.

Bevis, M., S. Businger, S.Chiswell, T.A. Herring, R.A.

Anthes, C. Rocken, and R.H. Ware, 1994: GPS Meteorology: mapping zenith wet delays onto precipitable water. J. Appl. Meteor., 33, 379-386.

Businger, S., S.R. Chiswell, M. Bevis, J. Duan, R.A.

Anthes, C. Rocken, R.H. Ware, M. Exner, T. VanHove,

and F.S. Solheim, 1996: The promise of GPS in atmospheric monitoring. Bull. Amer. Meteor. Soc., 77, 5-18.

Duan, J., M. Bevis, P. Fang, Y. Bock, S. Chiswell, S.

Businger, C. Rocken, F. Solheim, T. Van Hove, R. Ware,

S. McClusky, T. Herring, and R.W. King, 1996: GPS Meteorology: Direct Estimation of the Absolute Value of Precipitable Water. J. Appl. Meteor., 35, 830-838.

Hajj, G.A., K.R. Hardy and E.R. Kursinski, 1994: Assessment of GPS occultations for atmospheric profiling,

7th conference on satellite meteorology and oceanography, June 6-10, Monterey, CA, American Meteorology

Society.

Kuo, Y.-H., Y.-R. Guo, and E.R. Westwater, 1993: Assimilation of Precipitable Water into a Mesoscale Numerical Model. Mon. Weather Rev., 121, 1215-1238.

Lindzen, R.S., 1994: Climate dynamics and global change,

Annu. Rev. Fluid Mech., 26, 353-378.

Trenberth, K.E., and C.J. Guillemot, 1995: Evaluation of

the global atmospheric moisture budget as seen from

analyses. J. Climate, 8, 2255-2272.

Ware, R., M. Exner, D. Feng, M. Gorbunov, K. Hardy, B.

Herman, Y. Kuo, T. Meehan, W. Melbourne, C. Rocken,

W. Schreiner, S. Sokolovskiy, F. Solheim, X. Zou, R.

Anthes, S. Businger, and K. Trenberth, 1996: GPS sounding of the atmosphere from low Earth orbit: Preliminary

results. Bull. Amer. Meteor. Soc., 77, 19-40.

Zou, X., Y.-H. Kuo, and Y.-R. Guo, 1995: Assimilation of

atmospheric radio refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 123, 2229-2249.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 191

Project to Interface Modeling on Global and

Regional Scales With EOS Observations

Principal Investigator – Robert E. Dickinson

Science Background

Climate models have several important roles that require

their further improvement. They are the major tool in projecting future climate change from increasing greenhouse

gases, thus providing a basis for planning adaptation to

future climate change and possible limitations on the production of greenhouse gases by international convention.

They also provide useful predictions of interannual climate variability resulting from El Niño and other mechanisms. Finally, they are the scientific basis for the 4-dimensional data assimilation technology used for analysis

of many of the EOS remote-sensing products. Land processes and their interaction with the atmosphere are important elements of climate models and EOS observations.

The various activities in this investigation are directed

toward improving the interaction of land processes with

the atmosphere in climate models, hence improving the

use of climate models for the prediction of global change

and for data assimilation through the application of EOS

data. The analysis and comparison of these data to model

results improve the formulation of processes in current

climate models and give a better understanding of the

underlying physical processes.

Science Goals

The primary foci of this investigation are to: 1) develop

new methods for using EOS observations to assess and

improve climate-model treatments of surface-atmosphere

interactions and the hydrological cycle; 2) develop and

apply methods to obtain, archive, and enhance geophysical parameters from EOS sensors that will improve those

components of climate models; and 3) analyze and improve those aspects of climate models most related to the

coupling between land and the atmosphere, including the

numerical simulations required to design and test such

improvements.

Current Activities

Specific tasks currently being addressed to help meet the

overall objectives are:

Development of algorithms and data sets: Appropriate treatments are being developed for: an hourly skin

temperature from the twice-daily MODIS skin-temperature product; a roughness-length data set which will use

MODIS land cover information along with observations

of past field studies to estimate the aerodynamic roughness length and displacement height; a fractional vegetation-cover product based on the observed skin temperatures along with NDVI, LAI, and vegetation type; and an

albedo for use in climate models derived from the MODIS albedo and BRDF products and allowing for required

spectral and solar-zenith dependencies. Questions related

to the most suitable methods for scaling-up of the various

surface parameters to the resolution of climate models

are being addressed.

Modeling issues: Data sets needed for climate model

boundary conditions are being developed from EOS observations on a 0.1o spatial mesh. Prior to the availability

of such observations, preliminary such data are derived

from the 1-km AVHRR product of the land DAAC and

from intermediate products derived by various EOS participants. Software is developed that scales the observations on the 0.1o grid to various resolutions used by climate models. Studies are done with versions of the NCAR

Community Climate Model to test the boundary conditions so derived, to determine what model resolutions can

make most effective use of EOS observations, to establish the nature of climate-simulation improvement provided by EOS data, and to prototype the use of EOS observations for model improvement. Working in the context of the BATS and other land models, specific

parameterizations are being improved related to the use

of EOS observations that involve model surface temperatures and water and energy fluxes.

Use of Satellite Data

Various data (including snow cover, surface skin temperature, land cover, surface BRDF, surface albedo, LAI, and

NDVI) from EOS Terra instruments (especially MODIS

and MISR) will be used to derive skin-temperature diurnal cycle, roughness length, albedo, and vegetation fractional cover. These EOS data will also be used to validate

and improve surface processes in climate models. Currently, one year global 10-day average 1-km AVHRR data

(including all channels and derived NDVI) and global 1-

km land cover data (with a total volume of about 200

GB) have been obtained form EROS DAAC to prototype

our research efforts and to test our scientific computing

facility.
192 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Participation in Field Activities

We are contributing to various field activities (e.g.,

BOREAS, SALSA, CASES, and EOS instrument validation efforts) by providing modeling guidance and applications (e.g., selection of sites and timing, measurement

accuracy requirements, use of the data for modeling parameterization) through presentations at related workshops/meetings and research involvement.

Product Dissemination

In collaboration with other groups, we are developing

web-based archival systems to provide the products of

our investigation to any users that may require them.

Principal Investigator

Robert Dickinson

Robert Dickinson has been contributing to the fields of

climate modeling and global change research for over 30

years. He received his Ph.D. from the Massachusetts Institute of Technology in 1966 and shortly thereafter joined

the staff of NCAR. In 1975, he became Head of the Climate Section and, in 1981, Deputy Director of the Climate and Global Dynamics Division. He joined the faculty of the Department of Atmospheric Sciences at the

University of Arizona in 1990 and currently holds the

position of Regents Professor. He has been active in many

capacities as a member of the U.S. National Academy of

Sciences, the American Geophysical Union, and the

American Meteorological Society, as an editor for the

Journal of Climate and through active participation in

committees, panels, and working groups of the National

Research Council, the International Geosphere Biosphere

Programme, the World Climate Research Programme, and

the Intergovernmental Panel on Climate Change. Awards

received by Dr. Dickinson include: the AMS Meisinger

Award in 1973, the AMS Jule G. Charney Award in 1988,

the AMS Walter Orr Roberts lecturer in Interdisciplinary

Sciences in 1995, the AMS Rossby Award in 1996, the

AGU Roger Revelle Medal in 1996 and the G. Unger

Vetlesen Prize from the Lamont-Doherty Earth Observatory of Columbia University in 1995.

Co-Investigators

William Emery - University of Colorado

References

Arain, A.M., W.J. Shuttleworth, Z.-L. Yang, J. Michaud,

and A.J. Dolman, 1997: Mapping surface cover parameters using aggregation rules and remotely-sensed cover

classes. Quart. J. Roy. Meteor. Soc., 123, 2325-2348.

Dickinson, R.E., 1999: Interannual Variability of Climate

-A Review. Global Biogeochem. Cycles-Special Issue, in

press

Dickinson, R.E., M. Shaikh, R. Bryant, and L. Graumlich,

1998: Interactive canopies for a climate model. J. Climate, 11, 2823-2836.

Jin, M., and R.E. Dickinson, 1999: Interpolation of surface radiation temperature measured from polar orbiting

satellites to a diurnal cycle, Part 1: Without clouds. J.

Geophys. Res., 104, 2105-2116.

Dickinson, R.E., and K.J. Schaudt, 1998: Analysis of

timescales of response of a simple climate model. J. Climate, 11, 97-106.

Schaudt, K.J., 1998: A new method for estimating roughness parameters and evaluating the quality of observations. J. App. Meteor., 37, 470-476.

Seth, A., R. Bales, and R.E. Dickinson, 1999: A framework for the study of seasonal snow hydrology and its

interannual variability in the alpine regions of the Southwest. J. Geophys. Res., in press.

Seth A., and F. Giorgi, 1999: The effects of domain choice

on summer precipitation simulation and sensitivity in a

regional climate model. J. Climate, in press.

Shuttleworth, W.J., Z.-L. Yang, and A.M. Arain, 1997:

Aggregation rules for surface parameters in global models. Hydro. Earth Sys. Sci., 2, 217-226.

Yang, Z.-L., R.E. Dickinson, W.J. Shuttleworth, and M.

Shaikh, 1999: Treatment of soil, vegetation and snow in

land-surface models: A test of the Biosphere-Atmosphere

Transfer Scheme with the HAPEX-MIBILHY,

ABRACOS and Russian data. J. Hydrol., in press.

Zeng, X., and R.E. Dickinson, 1998: Effect of surface

sublayer on surface skin temperature and fluxes. J. Climate, 11, 537-550.

Zeng, X., Y.-J. Dai, R.E. Dickinson, and M. Shaikh, 1998:

The role of root distribution for land climate simulation

over land. Geophys. Res. Let., 25, 4533-4536.

Zeng, X., 1999: The relationship between precipitation,

cloud-top temperature, and precipitable water over the

tropics. J. Climate, in press.

Investigation URL

http://www.atmo.arizona.edu/land/uofa_land.html
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 193

The Global Soil Wetness Project

Principal Investigator – Paul A. Dirmeyer

Science Background

The Global Soil Wetness Project (GSWP) is an ongoing

modeling activity of the International Satellite Land-Surface Climatology Project (ISLSCP), a contributing project

of the Global Energy and Water Cycle Experiment

(GEWEX). The GSWP is charged with producing a 2-

year global data set of soil moisture, temperature, runoff,

and surface fluxes by integrating one-way uncoupled landsurface process models (LSPs) using externally specified

surface forcings and standardized soil and vegetation distributions, namely, the ISLSCP Initiative I CD-ROM data

(Sellers et al. 1996a). Approximately one dozen participating LSP groups in five nations have taken the common ISLSCP forcing data to execute their state-of-the-art

models over the 1987-1988 period to generate global data

sets. See IGPO (1995) or Dirmeyer et al. (1999) for further details.

The motivation for GSWP stems from the paradox

that soil wetness is an important component of the global

energy and water balance, but it is unknown over most of

the globe. Soil wetness is the reservoir for the land-surface hydrologic cycle, it is a boundary condition for the

atmosphere, it controls the partitioning of land-surface

heat fluxes, affects the status of overlying vegetation, and

modulates the thermal properties of the soil. Knowledge

of the state of soil moisture is essential for climate predictability on seasonal-to-annual time scales. However,

soil moisture is difficult to measure in situ, remote-sensing techniques are only partially effective, and few longterm climatologies of any kind exist.

Science Goals

The goals of GSWP are fourfold. The project will produce state-of-the-art global data sets of soil moisture, surface fluxes, and related hydrologic quantities. It is a means

of testing and developing large-scale validation techniques

over land. It serves as a large-scale validation and quality

check of the ISLSCP Initiative I data sets. GSWP is also

a global comparison of a number of LSPs, and includes a

series of sensitivity studies of specific parameterizations

which should aid future model development.

Current Activities

The GSWP consists of three components: the Production

Group, the Validation Group, and the Inter-Comparison

Center. The Production Group consists of land-surface

modelers who conduct offline integrations of land-surface models over a global 1 ̊ grid for 1987-1988 using

prescribed atmospheric forcing based on observations, remote sensing, and analyses. Each member of the production group produces global time-mean and instantaneous

fields of surface-energy and water-balance terms three

times per month using his/her model. These data are produced in a standard format and sent to the Inter-Comparison Center. In addition, each model is used to perform

specific sensitivity studies. The sensitivity experiments

are intended to evaluate the impact of uncertainties in

model parameters and forcing fields on simulation of the

surface-water and energy balances.

There is also a Validation Group which assembles

data sets and coordinates studies to validate the global

products, either directly (by comparison to field studies

or soil-moisture measuring networks) or indirectly (e.g.

use of modeled runoff to drive river-routing schemes for

comparison to streamflow data). The soil-wetness data

produced are being tested within a general circulation

model (GCM) to evaluate their quality and their impact

on seasonal-to-interannual climate simulations. The

Winand Staring Centre has volunteered to lead the validation process.

An Inter-Comparison Center (ICC) has been established at the Center for Climate System Research, University of Tokyo, for evaluating and comparing data from

the different models. Comparison among the model results is used to assess the uncertainty in estimates of surface components of the moisture and energy balances at

large scales, and as a quality check on the model products

themselves.

Use of Satellite Data

The project relies heavily on the ISLSCP Initiative I data

sets, produced and stored at the NASA/Goddard DAAC.

Many aspects of these data are based on remote-sensing

data. Virtually all of the vegetation-cover data are derived

from Fourier-adjustment, solar-zenith-angle-corrected, In
194 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

terpolated Reconstructed (FASIR) Normalized Difference

Vegetation Index (NDVI) products derived from the Advanced Very High Resolution Radiometer (AVHRR), as

described by Sellers et al. (1996b). In addition, the highresolution surface shortwave and longwave radiation

fluxes used to drive the models were calculated from a

hybrid of ISCCP-C1 data (Darnell et al. 1992) and

ECMWF analyses, prepared at NASA/Langley Research

Center.

Principal Investigator

Paul A. Dirmeyer

Dr. Dirmeyer received his Ph.D. from the University of

Maryland in 1992 and joined the research staff at the Center for Ocean-Land-Atmosphere Studies shortly thereafter. He has conducted research into the role of the land

surface in climate variability and predictability, as well

as in land-surface model development. He is chair of the

GEWEX Global Soil Wetness Project (GSWP), a member of the International Satellite Land-Surface Climatology Project (ISLSCP) Science Panel, and the NCAR Climate System Model – Land Model Working Group. He

has been a member of the American Meteorological Society since 1985, and a member of the American Geophysical Union since 1990. He has served on panels of

the NOAA Office of Global Programs, GEWEX Continental-scale International Project (GCIP), NASA Earth

Science Enterprise, and the Intergovernmental Panel on

Climate Change.

Co-Investigators

Pavel Kabat - Winand Staring Centre

A. J. Dolman - Winand Staring Centre

References

Darnell, W.L., W.F. Staylor, S.K. Gupta, N.A. Ritchey,

and A.C. Wilber, 1992: Seasonal variation of surface radiation budget derived from ISCCP-C1 data. J. Geophys.

Res., 97, 15,741-15,760.

Dirmeyer, P.A., A.J. Dolman, and N. Sato, 1999: The Global Soil Wetness Project: A pilot project for global land

surface modeling and validation. Bull. Amer. Meteor. Soc.,

80, 851-878.

International GEWEX Project Office, 1995: Global Soil

Wetness Project, 47 pp.

Sellers, P.J., B.W. Meeson, J. Closs, J. Collatz, F. Corprew,

D. Dazlich, F.G. Hall, Y. Kerr, R. Koster, S. Los, K.

Mitchell, J. McManus, D. Myers, K.-J. Sun, and P. Try,

1996: The ISLSCP Initiative I global datasets: Surface

boundary conditions and atmospheric forcings for

land-atmosphere studies. Bull. Amer. Meteor. Soc., 77,

1987-2005.

Sellers, P.J., S.O. Los, C.J. Tucker, C.O. Justice, D.A.

Dazlich, G.J. Collatz, and D.A. Randall, 1996: A revised

land surface parameterization (SiB2) for atmospheric

GCMs. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data. J. Climate,

9, 706-737.

Investigation URL

http://www.iges.org/gswp/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 195

Hydrology, Hydrochemical Modeling, and

Remote Sensing In Seasonally Snow-covered

Alpine Drainage Basins

Principal Investigator – Jeff Dozier

Science Background

Seasonally snow-covered areas of the Earth’s mountain

ranges are an important component of the Earth’s hydrologic cycle, even though they cover only a small fraction

of the Earth’s surface. These alpine regions are a major

source of water for runoff, ground-water recharge, and

agriculture. Moreover, these regions are sensitive to

changes in climate and to the amount and chemistry of

snowfall, because of their small ground-water reservoirs,

the predominance of intrusive igneous rocks that weather

slowly, thin acidic soils, the large amount of precipitation, and typical basin low-buffering ability. Because of

this sensitivity, changes in precipitation chemistry translate into changes in stream chemistry more rapidly than

in basins with deeper soils.

Knowledge of the hydrologic cycle in these areas is

limited by poor understanding of the processes that determine the cycle. We have imprecise knowledge about

the spatial and temporal distribution of the rate of snow

melt, water flow in the snow and its chemical concentrations, and the routing of water from the snow pack through

the drainage basin. Because of the topographically complex terrain in alpine basins, it is difficult to collect sufficient data to characterize and model these processes.

Science Goals

In an attempt to gain better understanding of Alpine Basin Hydrology, this investigation will use remotely-sensed

data from several EOS-era instruments in conjunction with

field data to study hydrologic conditions in watersheds

and to drive hydrologic models. It seeks a fundamental

understanding of the cycling of water, chemical species,

and nutrients in alpine basins, and thus an ability to identify changes caused by changing climate or changing precipitation chemistry.

Current Activities

Snow mapping at subpixel resolution with Landsat TM

and NOAA AVHRR data: We have developed automated,

unsupervised spectral-mixture analysis techniques for

mapping snow-covered area at subpixel resolution. The

mixture analysis permits estimation of fractional snow

cover for 30-m or 1.1-km pixels. The technique was verified with high-resolution (<1 m) aerial photos, is as accurate as the photos, but can be used over much larger areas

at much lower cost. The technique is being extended to

MODIS data.

Snow and grain-size mapping at subpixel resolution

and estimation of surface liquid water with AVIRIS (Airborne Visible and Infrared Imaging Spectrometer): Spectral-mixture analysis with a library of modeled snow spectral reflectances and measured spectral reflectances (vegetation, rock, soil, lake ice) facilitates estimation of the

fraction of snow in each 20-m pixel and the surface grain

size of that snow. Knowledge of the grain size allows calculation of the spectral albedo of the snow, independent

of the albedo of the other constituents in the pixel. The

algorithm is now automatic and will be portable to MODIS data. Modeling results show that we can derive liquid-water content of a thin surface layer.

Synthetic aperture radar (SAR) investigations with

data from AIRSAR and SIR-C/X-SAR: With an airborne

or spaceborne SAR, snow can be mapped in any weather

condition with an accuracy of about 85%. Although instruments in the optical wavelengths, e.g., Landsat, provide more-accurate snow maps, they are restricted to clear

weather. The liquid-water content in the top layer of the

snow pack can be estimated with an accuracy of about

2% by volume from SAR. It provides the information on

melting status of snow pack. SAR data can also estimate

the snow-water equivalence (SWE), which is the most

important parameter for hydrologic applications. Combining this information into a distributed snow-melt model

that predicts the timing and magnitude of snow-melt runoff from energy-balance parameters is one of our future

challenges. Such a model could be a powerful management tool for forecasting runoff, and, hence, maximizing

water yield and minimizing the impacts of floods.

Biogeochemical modeling: Biogeochemical modeling of 3 catchments in the Sierra Nevada has been completed and continues at two catchments in the Rocky

Mountains. The completed modeling shows that alpine
196 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

catchments are sensitive to changes in climate and atmospheric deposition. The modeling also shows that areas

of rock in alpine catchments, that were previously considered unreactive, are reactive and produce cations and

immobilize nitrogen in alpine basins. In building a model

for an alpine catchment, snow-covered area (SCA) is the

most crucial data type. SCA dominates the hydrology of

alpine basins and also has an effect on the biogeochemistry of alpine basins by insulating and thus warming the

soil during the cold winter season.

Developing data-centric information management

systems: Our studies of hydrology and hydro-chemistry

systems result in an accumulation of massive amounts of

scientific data. We are addressing the need to manage these

large, complex data sets, so that the data are effectively

and efficiently ingested, stored, maintained, retrieved, and

analyzed. Evolving systems are being used for handling

imagery, managing field data, and creating scientific products. Some capabilities of the systems include the ability

to store and retrieve data from disparate computing environments in a “seamless” fashion; generate scientific products; access a variety of analysis tools; track processes

applied to data; view imagery, field notes, and maps;

browse and select data of interest over the Internet; and

provide an intuitive user interface.

Use of Satellite Data

In the EOS era, techniques initially carried out with

Landsat TM, NOAA AVHRR, and AVIRIS data will be

extended to subpixel snow extent and grain-size mapping

from MODIS and ASTER. With such analyses, MODIS

will be useful in alpine regions. SAR investigations that

are now being pursued with advanced aircraft-mounted

systems may be continued using simplified techniques

with single-frequency, single-polarization SAR instruments such as those on ERS-2, JERS-1, and Radarsat to

provide useful snow-mapping data.

Participation in Field Programs

Examination of the biogeochemistry of mixed-conifer

catchments in the Sierra Nevada using 12 years of data

on precipitation inputs, stream discharge, and stream

chemistry has shown that precipitation over the period

varied widely, but that chemistry precipitation was similar. Solute concentrations were higher in rain than in snow,

and dry deposition constituted a major portion of the nitrogen and sulfur inputs. Although soil alkalinity buffered acidic inputs from wet deposition, brief decreases in

stream pH occurred during larger storms. These data show

that the close relationship between precipitation chemistry and stream chemistry occurs in the subalpine forested

zone, as well as in the high alpine zone with only sparse

trees and thin soils.

In the Tokopah drainage of the Sierra Nevada range,

measurements were obtained of depth and density of the

snowpack suitable for estimating the distribution and ablation of SWE throughout the 1997 melt season. The survey data, in combination with remotely sensed data (TM

and AVIRIS), are currently being used in the application

and comparison of various methods of determining SWE;

the development of basin water balances; an investigation of the relationship between SWE accumulation and

terrain attributes; the initialization, calibration, and validation of distributed hydrological and hydrochemical

models; and the development of methods for distributed

snowmelt model validation.

Field measurements in the Rocky Mountains have

investigated nitrogen-cycling processes under the snow

pack. The data show a trend in the last decade toward

nitrogen saturation in the high-elevation catchments. Normally these basins do not export nitrogen; the biota consume all the nitrogen before it leaves the basin. However,

deposition of extra nitrogen in the precipitation has apparently caused these basins to become nitrogen saturated.

A large, collaborative remote-sensing and field campaign was conducted in Spring 1996 in the Rocky Mountain National Park. Immediate uses of the campaign include snow-water-equivalence and snowmelt modeling,

and further development of algorithms to retrieve snow

surface information from remotely sensed imagery.

Principal Investigator

Jeff Dozier

Jeff Dozier, Dean of the Donald Bren School of Environmental Science and Management, University of California, Santa Barbara, received his B.A. from California State

University, Hayward in 1968 and his Ph.D. from the University of Michigan in 1973. He has taught at UC Santa

Barbara since 1974. From 1990-1992 he served as the

EOS Senior Project Scientist. He has published extensively in diverse fields of research including snow hydrology, Earth system science, radiative transfer in snow,

remote sensing and data systems, image processing, and

terrain analysis. With Dr. Ghassem Asrar he is the coauthor of EOS: Science Strategy for the Earth Observing

System (American Institute of Physics, 1994). He is a Fellow of the American Geophysical Union, a Distinguished

Visiting Scientist at the Jet Propulsion Laboratory, and

an Honorary Professor of the Chinese Academy of Sciences. From 1990-1993 he was Editor of Geophysical

Research Letters. For the National Research Council, he

is a member of the Climate Research Committee and also

serves on the Scientific and Technical Advisory Panel of

the National Intelligence Council. In 1993 he received

the NASA Public Service Medal, was the 1997 Moe I.

Schneebaum Lecturer at NASA GSFC, and now serves

on the Earth System Science and Applications Advisory

Committee (ESSAAC).
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 197

Co-Investigators

Roger Bales - University of Arizona

John Melack - University of California

Kathy Tonnessen - National Biological Service/National

Park Service

Mark Williams - University of Colorado

References

Aizen, V., E. Aizen, J.M. Melack, and J. Dozier, 1997:

Climatic and hydrologic changes in the Tien Shan, central Asia. J. Climate, 10, 1393-1404

Brooks, P.D., M.W. Williams, and S.K. Schmidt, 1996:

Microbial activity under alpine snowpacks, Niwot Ridge,

Colorado. Biogeochemistry, 32, 93-113.

Brooks, P.D., S.K. Schmidt, M.W. Williams, 1997: Winter production of CO2 and N2O from alpine tundra: environmental controls and relationship to intersystem C and

N fluxes. Oecologia, 110, 403-413.

Melack, J.M., J. Dozier, C.R. Goldman, D. Greenland, A.

Milner, and R.J. Naiman, 1997: Effects of climate change

on inland waters of the Pacific coastal mountains and western Great Basin of North America. Hydrological Processes, 11, 971-992.

Painter, T.H., D.A. Roberts, R.O. Green, J. Dozier: Improving spectral mixture analysis of snow-covered area

with AVIRIS data. Remote Sens. Environ., in press.

Rosenthal, W., and J. Dozier, 1996: Automated mapping

of montane snow cover at subpixel resolution from the

Landsat Thematic Mapper. Water Resour. Res., 32, 115-

130.

Shi, J., and J. Dozier, 1995: Inferring snow wetness using

C-Band data from SIR-C’s polarimetric Synthetic Aperture Radar. IEEE Trans. Geosci. Remote Sens., 33, 905-

914.

Shi, J., and J. Dozier, 1997: Mapping Seasonal Snow with

SIR-C/X-SAR in Mountainous Areas. Remote Sens.

Environ., 59, 294-307.

Williams, M.W., J.S. Baron, N. Caine, R.A. Sommerfeld,

and R. Sanford Jr., 1996: Nitrogen saturation in the Rocky

Mountains. Environ. Sci. Technol., 30, 640-646.

Williams, M.W., M.V. Losleben, N. Caine, and D.

Greenland, 1996: Changes in climate and hydrochemical

responses in a high-elevation catchment in the Rocky

Mountains, USA. Limnology and Oceanography, 41, 939-

946.

Williams, M., and J.M. Melack, 1997: Atmospheric deposition, mass balances, and processes regulating

streamwater solute concentrations in mixed conifer

catchments of the Sierrra Nevada, California. Biogeochemistry, 37, 111-144.

Wolford, R.A., and R.C. Bales, 1996: Hydrochemical

modeling of Emerald Lake watershed, Sierra Nevada,

California: Sensitivity of stream chemistry to changes in

fluxes and model parameters. Limnology and Oceanography, 41, 947-954.

Wolford, R.A., R.C. Bales, and S. Sorooshian, 1996: Development of a hydrochemical model for seasonally snowcovered alpine watersheds: Application to Emerald Lake

watershed, Sierra Nevada, California. Water Resour. Res.,

32, 1061-1074.

Zurk, L.M., L. Tsang, J. Shi, and R.E. Davis, 1997: Electromagnetic scattering calculated from pair distribution

functions retrieved from planar snow sections. IEEE

Trans. Geosci. Remote Sens., 35, 1419-1428.

Investigation URL

http://www.icess.ucsb.edu/hydro/hydro.html
198 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Combining Remote Sensing and Hydrological

Modeling for Applied Water and Energy

Balance Studies

Principal Investigator – Ralph Dubayah

Science Background

An improved understanding of the continental and global

water and energy cycles is crucial to our ability to predict

and plan for global change in the next century. Of particular importance is the role of the land surface in controlling the spatial and temporal dynamics of these cycles,

and the resulting effects on surface hydrology. Consequently, there has been intense research activity aimed at

improving the representation of the land surface in models used for climate simulation, weather prediction, and

water management. However, performing large-scale applications of these models is greatly complicated by the

scarcity of land-surface observations. In many areas of

the world, the data needed to drive such models do not

exist, so that water management and forecasting are

fraught with uncertainty. Many of the most data-deficient

areas are underdeveloped regions of the world that are at

high risk for water-related disasters, such as floods and

droughts.

The use of remote-sensing data from existing space

platforms, as well as those from the planned EOS suite of

sensors, promises to revolutionize our knowledge by providing alternatives to the ground observations upon which

hydrological modeling is presently based.

Science Goal

The major science goal of this investigation is to improve

hydrologic prediction capabilities for water-resource management at continental scales through the development

of coupled hydrologic and land-surface models that are

driven by remotely sensed data. As a consequence, our

research objectives involve the development and assessment of remote-sensing methods to provide input forcings

for hydrologic models, as well as strategies for using remote-sensing data to update hydrologic state variables in

these models. Through these efforts we also hope to obtain a better understanding of the spatial and temporal

variability of the water and energy balances, and the contributing role of land-surface characteristics and near-surface atmospheric dynamics.

Current Activities

In collaboration with other EOS IDS investigators, we

have undertaken an initial study of the Red River-Arkansas basin of the Mississippi, the focus of a recent Project

for the Intercomparison of Land Surface Parameterization Schemes (PILPS) model intercomparison. Our activities in this basin serve as a framework for our future

work and are focused on:

1) ground and satellite data acquisition;

2) generation of environmental forcing fields from these

data; and

3) water-and-energy balance studies using the two-layer

Variable Infiltration Capacity model (VIC-2L), a hydrologically based land-surface scheme.

The strategy is to first drive our models using in situ

observations. To that end, we are developing a method

for real-time gridding of surface precipitation and temperature fields based on station data. Subsequently, as

many of the model input fields as possible will be derived using remote-sensing methods, and model results

will then be compared to simulations using only surface

data. Based on our experience in the Red River-Arkansas

basin, we have begun similar work for the entire Mississippi basin, an area of intense modeling and field activity

within the context of the GEWEX Continental Scale International Project (GCIP).

Coincident with these specific modeling efforts, we

are engaged in general research centered around the use

of remotely sensed data in hydrological modeling. Our

first activity is the development and validation of remotesensing methods to derive input fields for hydrological

modeling by integrating satellite data from multiple platforms at varying spatial and temporal resolutions. Secondly, we are working towards evolving our hydrologic

model structure so that it can better exploit current and

EOS-era remote-sensing products. For instance, with an

appropriately designed model, remote-sensing data may

be used not only as driving inputs, but also to update model

state variables such as surface temperature, so that over

time model outputs do not diverge from observed environmental conditions.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 199

Use of Satellite Data

A central goal of this research is to combine remote sensing with hydrological modeling; therefore, our work relies heavily on satellite data. We have used a variety of

existing remote-sensing data in our investigation thus far,

including AVHRR, GOES, TOVS, Landsat, and a variety

of passive and active microwave sensors, all guided primarily by required model input fields for VIC-2L. These

fields include incoming solar radiation, surface albedo,

incoming longwave radiation, air temperature, vapor pressure deficit, precipitation, wind, and surface characteristics such as vegetation, soils, and topography. In addition, model-state-variable updating may require data on

surface temperature, soil moisture, and snow cover.

We use GOES data to derive incoming solar radiation at fine temporal resolution (30 minutes) with coarse

spatial resolution (nominal 1 km). Data from the GOES

water-vapor channel are also used to find total column

precipitable water vapor. AVHRR data are used to derive

near-surface air temperature, precipitable water vapor,

near-surface humidity, and surface temperature. AVHRR

imagery are also used to obtain vegetation data (NDVI),

and from this, seasonal changes in fractional PAR, fractional forest cover and leaf-area index (LAI). The TOVS

instrument on board NOAA polar orbiters provides coarseresolution estimates of air and surface temperature. Lastly,

we are exploring the use of radar and microwave data for

temperature, soil moisture, and snow cover from instruments such as SIR-C and SMMR-SSM/I.

Participation in Field Programs

We intend to participate in field activities planned for the

GCIP North Central (Upper Mississippi River basin) and

East (Ohio and Tennessee-Cumberland River basin Large

Scale Study Areas (LSAs). GCIP plans to move its focus

from LSA-SW (Arkansas-Red River basin) to North Central, and subsequently East, over the next two years. A

current focus of our modeling is the development of an

improved algorithm to simulate frozen soils and associated effects on infiltration and soil thermal characteristics. One aspect of this work may be in situ observations

to verify the ability of SAR to delineate the extent of frozen soils. We are also participating in CASES, the Cooperative Atmosphere-Surface Exchange Study, a surfaceboundary layer experiment initiated in the Walnut River

basin in Kansas, in the spring of 1997. With others, our

field work there is aimed at characterizing the spatial variability of soil moisture.

Overview and Objectives

The estimation of the spatial and temporal variability of

the hydrologic and energy budgets of the land surface is a

central objective of studies such as GCIP, and is crucial

for improved climate simulation, numerical weather prediction, and water resources management. Macroscale

hydrological modeling is a powerful tool with which to

develop predictive understanding of the large-scale dynamics of these budgets. However, hydrological modeling at continental scales and beyond is greatly hindered

by the scarcity of land-surface observations needed to

drive the models.

Remote sensing promises to revolutionize large-scale

hydrological modeling by providing an alternative to the

use of ground observations that historically have been the

sole model forcings. The challenge is to design hydrologic model structures and remote-sensing methodologies

that make best use of the largely untapped potential of

satellite observations for water-resources management

during the EOS era.

Principal Investigator

Ralph Dubayah

Ralph Dubayah received his B.A. (1982) in geography

from the University of California, Berkeley, and his M.A.

(1986) and Ph.D. (1990) degrees in geography from the

University of California, Santa Barbara. His research interests include land-surface energy balance, hydrology,

topographic and spatial analysis, and remote sensing. He

is principal investigator for the Vegetation Canopy Lidar

(VCL), a NASA Earth System Science Pathfinder (ESSP)

mission to map the structure of the Earth’s forests and

topography. He is currently Associate Professor at the

University of Maryland, College Park, and holds a joint

appointment in Geography and the University of Maryland Institute for Advanced Computer Studies (UMIACS).

Co-Investigator

Dennis P. Lettenmaier - University of Washington

References

Dubayah, R., E.F. Wood, and D. Lettenmaier, 1995: Combining hydrological modeling and remote sensing for large

scale water and energy balance studies. Proc. International

Geosciences and Remote Sensing Symposium (IGARSS

’95), Florence, Italy.
200 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Dubayah, R., E.F. Wood, T.E. Engman, K. Czajkowski,

and M. Zion, 1997: A remote sensing approach to

macroscale hydrological modeling. Remote Sensing in

Hydrology and Water Management, G. Schultz, and E.

Engman, Eds., Springer-Verlag, Berlin.

Liang, X., D.P. Lettenmaier, E.F. Wood, 1996: One-dimensional statistical dynamic representation of subgrid

spatial variability of precipitation in the two-layer variable infiltration capacity model. J. Geophys. Res., 101,

21,403-21,422.

Investigation URL

http://www.inform.umd.edu geog/eos

The advantage of satellite-based temperature estimation is the ability to continuously map over large regions. The images above show

surface temperature (left) and air temperature (right) retrievals for the entire Mississippi basis at the AVHRR overpass time for 19 June,

1987. Note the relative difference between the two fields and the area of considerably warmer surface temperatures to the west, and

the cooler air temperatures in the mountains forming the western border of the basin. (After Dubayah and Lettenmaier, 1997.)
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 201

Direct Use of Satellite Remote Sensing in the

Estimation of Hydrologic Transports

Principal Investigator – Dara Entekhabi

Science Goal

The key objective of this proposal is to develop the capability to directly use data from remote-sensing instruments

such as those on Terra (MODIS and CERES visible and

infrared) in hydrologic processes studies. The project will

use existing archives of satellite observations (ERBE and

SSM/I at Langley DAAC) in these spectral regions together with robust dry static energy information from reanalyses (GEOS-1 NASA DAO) in a new approach to

the estimation of hydrologic transports using these data.

The project is directed towards the development of data

products on land runoff and other components of the surface water and energy budget over the GEWEX continental scale basin experiments (GCIP, GAME, LBA, and

MAGS basins). The development of the new methodology is in response to the severe limitations on the applicability of the current archive of satellite data and future

suite of planned satellite missions in the quantitative characterization of the hydrologic cycle. It is also in response

to the need to estimate land runoff and other components

of the hydrologic cycle when instruments (river gages and

radiosondes vapor data) have large measurement errors.

The hydrologic flux data (vapor convergence and

runoff) produced by this project are essentially based on

applying coupled atmospheric energy and water budget

equations. Components of these equations are estimated

using assimilated data on thermal and wind structure, and

constraining these equations by high-quality visible and

thermal-infrared satellite observations. These estimates

form a third and independent estimate of the land and

areal runoff (in addition to river gage and atmospheric

vapor convergence estimates that may be compared to

GEWEX continental scale basin experiment estimates

based on in situ observations by river gages and vapor

transport radiosondes/reanalyses.

Principal Investigators

Dara Entekhabi

Dara Entekhabi is currently an associate professor in the

Department of Civil and Environmental Engineering and

Department of Earth, Atmospheric, and Planetary Science

at the Massachusetts Institute of Technology (MIT). His

area of research interest includes land remote sensing, hydrologic data assimilation, land-atmosphere interaction,

and groundwater-surface water interaction. He received

his bachelor’s and two Master’s degrees at Clark University (1983, 1985, 1987) and his doctoral degree at MIT.

Dara Entekhabi was awarded the American Geophysical

Union’s Macelwane young scientist award as well as the

National Science Foundation’s Presidential Young

Investigator’s award. He is currently the chair of the National Research Council Committee on Hydrologic Science.

Co-Investigators

Rafael L. Bras - Massachusetts Institute of Technology

Guido D. Salvucci - Boston University

References

Entekhabi, D., I. Rodriguez-lturbe, and R.L. Bras, 1992:

Variability in large-scale water balance with landsurfaceatmosphere interaction. J. Climate, 5, 798-813.

Brubaker, K.L., D. Entekhabi, and P.S. Eagleson, 1993:

Estimation of continental precipitation recycling. J. Climate, 6, 1077-1089.

Salvucci, G.D., and D. Entekhabi, 1995: Hillslope and

climatic controls on hydrologic fluxes. Water Resources

Res., 31, 1725-1740.

Njoku, E.G., and D. Entekhabi, 1995: Passive microwave

remote sensing of soil moisture. J. Hydrol, 184, 101-130.

Brubaker, K.L., and D. Entekhabi, 1996: Analysis of feedback mechanisms in land-atmosphere interaction. Water

Resources Res., 32, 1343-1357.

Kim, C- P., and D. Entekhabi, 1998: Analysis of feedback mechanisms in the uncoupled and coupled land surface and mixed layer energy budgets. Boundary Layer

Meteorology, 88, 1-21.

Cohen, J., and D. Entekhabi, 1999: Eurasian snow cover

variability and Northern Hemisphere climate predictability. Geophys. Res. Lett., 26, 345-348.
202 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Representing Key Phytoplankton Groups in

Ocean Carbon Cycle Models

Principal Investigator – Paul G. Falkowski

 Project Summary

A quantitative understanding of the global carbon cycle

is essential for the assessment of anthropogenic effects

on the Earth’s environment. Such an understanding requires the integration of ecological processes in mathematical models. We propose to develop and integrate

observational data with mathematical models leading to

the development of a comprehensive biogeochemical representation of key functional groups in the ocean carbon

cycle. Specifically, we propose to:

1) develop satellite-based observational approaches for

distinguishing major functional biological groups, including nitrogen fixers, diatoms, and

coccolithophores, that influence the temporal and

spatial distribution of sources and sinks for carbon

dioxide in the world ocean;

2) develop modeling approaches for incorporating these

functional groups in ecosystem models; and

3) simulate the response of functional groups to future

climate scenarios using coupled atmosphere-ocean

models.

The primary goal of this proposal is to improve ocean

carbon models by describing how physical and chemical

forcing affects the statistical distribution of key functional

phytoplankton groups. That information is critical to predicting how changes in ocean physics and chemistry will

influence total and new production in future ocean-model

scenarios. The proposed research effort will be coordinated with the Ocean Carbon-cycle Modeling

Intercomparison Project (OCMIP), an international project

initiated in 1995 by the Global Analysis, Interpretation

and Modeling (GAIM) Task Force of the International

Geosphere-Biosphere Program (IGBP). The results of the

proposed research specifically would lead to the development of algorithms that predict how ocean physics and

chemistry affect the spatial distribution of:

1) Trichodesmium sp., the major nitrogen-fixing organisms;

2) diatoms, the major group responsible for export production;

3) coccolithophores, which, as a consequence of calcification, raise pCO2; and

4) the polytaxonomic group of picoplankton, which,

while they are the major carbon fixers, contribute little

to carbon export.

The statistical distribution of these four functional

groups will be analyzed using remotely sensed information in conjunction with sea-truth data, and, based on the

statistics of their distributions, “functional group profiles”

will be generated. The “functional group profiles” give a

probability of encountering each of the four groups in each

grid cell of an ocean general circulation model (OGCM).

Based on these profiles, we can specify physical and

chemical criteria that maximize and minimize the distributions of each group, and hence prospectively infer their

distributions in climate-change scenarios. From knowledge of the distributions of each group, the forcing and

feedback between ocean circulation, chemistry, and biological processes can be represented much more realistically in OGCMs.

The proposed research will examine the relationship

between remotely sensed data products, such as ocean

color, SST, and wind stress, with the spatial and temporal

distribution of the key functional groups. We propose to

develop algorithms that represent biogeochemical processes such as nitrogen fixation, calcification, and export

production. The algorithms are intended to be included

in OGCMs in which the effects of climate change on the

spatial and temporal distributions can be explored.

This research effort combines capabilities in remote

sensing with expertise in physiological ecology and ocean

biogeochemical process models. This interaction will be

facilitated by collaborations with key researchers that specialize in one or more of the individual functional groups
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 203

Principal Investigator

Paul G. Falkowski

Paul G. Falkowski is a Professor at the Institute of Marine and Coastal Sciences, Rutgers University. His research interests include phytoplankton ecology, biophysics, biogeochemical cycles, and symbiosis.

Since 1976, Falkowski has been a principal investigator under contract to the U.S. Department of Energy, to

study primary production and the fate of phytoplankton

carbon off the east coast of the U.S. He has worked extensively in the Atlantic and Pacific Oceans and in the

Red Sea. His latest research efforts are directed towards

understanding the factors limiting biological carbon fixation on geological and ecological time scales. He was involved in the SeaWiFS primary production algorithm

development program and remote sensing of global biogeochemical cycles.

Born in 1951 and raised in New York City, Falkowski

earned his B.S. and M.Sc. degrees from the City College

of the City University of New York and his Ph.D. from

the University of British Columbia. After a post-doctoral

fellowship at the University of Rhode Island, he went to

Brookhaven National Laboratory in 1976 to join the staff

of the newly formed Oceanographic Sciences Division.

He received tenure in 1984 and served as head of the division from 1986 to 1991. In 1998 he moved to Rutgers

University. In 1992 he received a John Simon Guggenheim

Fellowship. In 1996 he was appointed as the Cecil and

Ida Green Distinguished Professor at the University of

British Coumbia. He has authored or coauthored over 150

papers in peer-reviewed journals and books, and has

coinvented and patented a fluorosensing system which is

capable of measuring phytoplankton photosynthetic rates

nondestructively and in real time.

Co-Investigators

Richard Barber - Duke University
204 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Integrating Biogeochemical, Ecological, and

Hydrological Processes in a Dynamic

Biosphere

Principal Investigator – Jonathan Foley

Science Background

The biosphere is undergoing fundamental, global-scale

changes in response to land use, increases in atmospheric

CO2 concentration, and variations in climate. It is therefore of paramount importance to improve our understanding of the terrestrial ecosystem processes on a global scale.

In particular, we must examine the dynamics of the terrestrial biosphere on a wide variety of timescales, from

seasons to centuries.

To better understand global biospheric processes, and

to evaluate their potential response to human activity, we

are developing a new integrated dynamical model of the

Earth’s biosphere. Previous computer models of the

globe’s ecosystems have typically focused on the static,

or equilibrium, state of the biosphere rather than the full

range of ecological, biophysical, and biogeochemical processes occurring across different timescales. In addition,

earlier models have traditionally focused on one particular aspect of the biosphere—either the vegetation cover

itself, its water balance, or its carbon balance.

Our new, more integrated model, called the Integrated

Biosphere Simulator (or IBIS), reconciles the disparity

of previous ecosystem models by including the following processes:

• Land-surface processes (including the energy, water and

momentum balance of the soil-vegetation-atmosphere

system);

• ecosystem physiology and carbon-balance processes;

• vegetation dynamics;

• nutrient cycling and biogeochemistry; and

• continental-scale hydrology

In addition, IBIS is one of the first models that can

simulate the long-term dynamics of vegetation and ecosystems at the global scale. Such models, often referred

to as Dynamic Global Vegetation Models (DGVMs), can

be used to investigate how the world’s ecosystems may

change over time in response to land use, long-term climatic variations, or climate change.

Science Goal

Our NASA Interdisciplinary Science Team (IDS) project

(as part of NASA’s Earth Science Enterprise) aims to further develop and validate this new integrated model of

the Earth’s biosphere. The ultimate goal of our project is

to improve our understanding of the Earth’s terrestrial

biogeochemical and hydrologic cycles and their dynamic

response to anthropogenic and natural changes in the environment.

Current Activities

Some of our current research activities include the following:

• Development and Testing of IBIS

In early 1999, we released IBIS-2, a dramatically improved version of the IBIS modeling system. IBIS-2

includes a much more comprehensive representation

of terrestrial ecosystem processes than its predecessors,

including detailed land-surface processes, ecosystem

physiological processes, vegetation growth and competition, and soil carbon and nutrient cycling. The model

has been extensively tested against site-specific biophysical measurements (mainly from flux towers), as

well as spatially extensive ecological and hydrological

data. Currently, we operate the model at both global

and regional scales; two regions of particular interest

to our group are the Amazon Basin and the Mississippi

Basin.

Future developments of IBIS will focus on two major areas. First, we will be adding managed ecosystems

to the model, including permanent croplands and pastures. Second, we will be adding explicit disturbance

and age-dependence, to account for the effects of natural or human disturbance on ecosystems and their response over time.

We are continuing to evaluate the performance of

the IBIS model against a hierarchy of data sets, including site-level flux measurements, regional syntheses of

ecological or hydrological measurements, and globalscale remote-sensing products.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 205

• Development of a New Terrestrial Hydrological Systems Model: Rivers, Lakes, and Wetlands

Another part of our IDS project is focused on the linkages between surface waters (including lakes, wetlands,

and rivers) and the terrestrial biosphere.

In 1998, we completed the development of the

HYDrological Routing Algorithm (HYDRA), which is

linked to IBIS through a shared water-balance calculation. HYDRA operates at fairly high spatial resolution

(~10 km, globally) to simulate the flow of water from

land surfaces (through rivers, lakes, and wetlands) to

the ocean. HYDRA is the first global model to explicitly link rivers, lakes, and wetlands as fully dynamical

parts of the hydrologic cycle. We have also included

man-made structures (i.e., dams and reservoirs) within

HYDRA, to account for the management of terrestrial

hydrological systems.

We are actively working to evaluate HYDRA simulations against observed patterns of lakes, wetlands, and

river systems.

We have been using the IBIS and HYDRA models in the

following suite of research applications:

• DGVM Intercomparison Exercise

One recent application of IBIS has been to simulate the

possible transient changes in global vegetation cover

that may result from future climatic change. We are

currently participating in an IGBP-sponsored international project (coordinated by the Potsdam Institute for

Climate Impacts Research in Germany) to evaluate the

transient changes in global vegetation cover resulting

from CO2; and aerosol-induced climatic change, as

simulated with the U.K. Hadley Centre Coupled Atmosphere/Ocean model. There are several ecosystem

modeling groups participating in this project, including our EOS-IDS project, Sheffield University (UK),

the Hadley Centre (UK), the Potsdam Institute for Climate Impacts Research (Germany), the Institute for

Terrestrial Ecology (UK), and the Max Planck Institute

for Biogeochemical Cycles (Germany).

In this comparison, we are emphasizing the possible

transient changes in global vegetation cover and terrestrial carbon storage resulting from climate change

and CO2 fertilization. At the present time, the preliminary results of the comparison show that the models

have a fair degree of agreement, but many unexplained

differences remain.

• Effects of Land Use on the Terrestrial Biosphere

We are beginning to examine how changes in land cover

can affect the behavior of different ecosystems across

the world. Specifically, we are interested in how land

use may change terrestrial hydrological processes and

the ability of terrestrial ecosystems to store carbon. We

have already compared IBIS simulations against detailed measurements made at the University of Wisconsin Agricultural Experimental Station for different

land-use practices (e.g., restored prairie versus several

corn growing practices). Currently, we are conducting

sensitivity studies with IBIS at regional and global

scales, to investigate the potential changes in biogeochemical and hydrological processes that may accompany land-use and land-cover change.

We are also developing a new historical database

of global land-use and land-cover change. To reconstruct spatially-explicit land-use and land-cover change

over the last 100-200 years, we are developing a statistical land-cover data-assimilation technique that combines contemporary satellite data with historical landuse inventory data and other environmental data. Our

first data set, representing the global distribution of permanent croplands from 1992 to 1700 at ~10-km resolution, was completed in early 1999.

In the immediate future, we will be working to incorporate the dynamics of human land use activities

within IBIS. Because IBIS is a mechanistic, integrated,

and fully dynamic ecosystem model (including dynamic

representations of vegetation regrowth)—it is ideally

suited for this purpose. We will use this modeling framework along with geographically-explicit data on

changes in land use and land cover (along with historical climate and CO2-concentration records) to examine changes in terrestrial carbon exchange over the last

century.

• Spatial & Temporal Variability in the Hydrological

Systems of the Midwest

Using our new modeling tools, we have been investigating the effects of atmospheric and terrestrial processes on the water balance and hydrology of the Upper Midwest. In this study, we are applying IBIS and

HYDRA across the Upper Midwest, to examine the

influence of climate variability on land-surface processes, the surface water balance, and changes in river

discharge.

We are currently testing the performance of the IBIS

and HYDRA models across the Mississippi Basin, using a combination of detailed in situ measurements

(from long-term soil-moisture recording stations and

flux towers) and spatially extensive hydrographic data

(gauging station data collected by the USGS).

• Exploring Climate and Vegetation Interactions

In a related NSF-funded project, we have incorporated

IBIS directly within the GENESIS atmospheric GCM

in collaboration with David Pollard at Penn State Uni-
206 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

versity and Starley Thompson at NCAR. With this fully

coupled climate-vegetation model, we are evaluating

the potential for vegetation feedbacks on the Earth’s

climate. In particular, we have found that scenarios of

future climate change may need to be re-evaluated to

consider the potential for vegetation feedbacks. Some

specific questions we are considering include the following:

1. What might be the combined impacts of tropical deforestation and doubled CO2 concentrations (including both radiative and physiological effects) on climate?

2. Are vegetation feedbacks likely to contribute to

changes in future climate associated with a doubling

of CO2 concentrations?

3. Did vegetation feedbacks alter the climate of the

Last Glacial Maximum? If so, what were the possible physiological effects of lower CO2 concentrations on the climate and ecosystems?

Currently, we are actively engaged in an effort with

NCAR scientists to couple IBIS into the NCAR Climate Systems Model (CSM). The CSM is a state-ofthe-art climate model that combines an atmospheric

general circulation model, a land-surface package, an

ocean general circulation model, and a dynamical seaice model. By including IBIS within the NCAR CSM

framework, we will provide the scientific community

with an excellent framework to explore both the equilibrium and transient behavior of the coupled atmosphere-biosphere-ocean system, and its sensitivity to

human activities.

Use of Satellite Data

We plan to use a variety of EOS-related satellite data in

pursuit of our science goals. In particular, we will be using data from MODIS to evaluate our model results for a

variety of biophysical and ecological parameters. In addition, we hope to incorporate data from other platforms

into our project, including vegetation structure data from

the VCL and improved rainfall data sets from TRMM.

Participation in Field Activities

Our group will be providing modeling and data analysis

support to the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) through NASA’s LBA-Ecology program. Our LBA project focuses on long-term

changes in the ecology, biogeochemistry, and water resources of the Amazon Basin, and how they may be affected by climatic variations and land-use practices.

Initial versions of IBIS have already been used to

investigate ecological and hydrological processes within

the Amazon, and their sensitivity to land use, climate

change, and CO2 fertilization. Working with other LBAEcology investigators, we plan to develop improved versions of our integrated terrestrial biosphere models, and

use them to better understand the changing environmental conditions of Amazonia.

Principal Investigator

Jonathan Foley

Jonathan Foley’s research focuses on the interdisciplinary

interface between climate, global ecology, and human

activities. In particular, his work is focused on the use of

computer models to analyze and simulate changes in climate, global ecosystems, and natural resources.

Foley is currently the Director of the Climate, People

and Environment Program (CPEP) at the University of

Wisconsin. In addition, he holds the Reid A. Bryson Professorship at Wisconsin.

Foley earned his doctoral degree in Atmospheric Sciences at the University of Wisconsin in 1993. His graduate work was supported by a National Science Foundation Fellowship, and was recognized with a Sigma Xi

Doctoral Research Award. In addition, Foley was awarded

a Presidential Early Career Award for Scientists and Engineers in 1997 (nominated by NASA), and a National

Science Foundation Faculty Career Development award

in 1995.

Co-Investigators

John Norman - University of Wisconsin

I. Colin Prentice - Lund University, Sweden

References

Coe, M.T., 1998: A linked global model of terrestrial hydrologic processes:Simulation of modern rivers, lakes, and

wetlands. J. Geophys. Res., 103, 8885-8899.

Coe, M.T., 1999: Modeling terrestrial hydrologic systems

at the continental scale: Testing the accuracy of an atmospheric GCM. J. Climate, in press.

Costa, M.H., and J.A. Foley: Combined effects of deforestation and doubled atmospheric CO2 concentrations on

the climate of Amazonia. J. Climate, accepted.

Costa, M.H., and J.A. Foley, 1997: The water balance of

the Amazon basin: Dependence on vegetation cover and

canopy conductance. J. Geophys. Res., 102, 23,973-

23,990.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 207

Delire, C., and J.A. Foley: Evaluating the performance of

a land surface/ecosystem model with biophysical measurements from contrasting environments. J. Geophys.

Res., accepted.

Foley, J.A., I.C. Prentice, N. Ramankutty, S. Levis, D.

Pollard, S. Sitch, and A. Haxeltine, 1996: An integrated

biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global

Biogeochem. Cycles, 10, 603-628.

Foley, J.A., S. Levis, I.C. Prentice, D. Pollard, and S.L.

Thompson, 1998: Coupling dynamic models of climate

and vegetation. Global Change Biology, 4, 561-579.

Foley, J.A., S. Levis, M.H. Costa, R. Doherty, J.E.

Kutzbach, and D. Pollard: Vegetation and an interactive

part of global climate models. Ecological Applications,

submitted.

Kucharik, C.J., J.A. Foley, C. Delire, V.A. Fisher, M.T.

Coe, S.T. Gower, J. Lenters, C. Molling, J.M. Norman,

and N. Ramankutty: The IBIS-2 dynamic global biosphere

model: Model formulation and validation. Global

Biogeochem. Cycles, submitted.

Kucharik, C.J., K.R. Brye, J.M. Norman, J.A. Foley, S.T.

Gower, and L.G. Bundy: Measurements and modeling of

carbon and nitrogen dynamics in managed and natural

ecosystems. Global Biogeochem. Cycles, submitted.

Levis, S., J.A. Foley, and D. Pollard: Regional scale vegetation feedbacks on a doubled CO2 climate. J. Climate,

submitted.

Levis, S., J.A. Foley, and D. Pollard: Potential high-latitude vegetation feedbacks on CO2-induced climate

change. Geophys. Res. Lett., in press.

Levis, S., J.A. Foley, V. Brovkin, and D. Pollard: On the

stability of the high-latitude climate-vegetation system in

a coupled atmosphere-biosphere model. Global Ecology

and Biogeography Letters, submitted.

Ramankutty, N., and J.A. Foley, 1998: Characterizing patterns of global land use: An analysis of global croplands

data. Global Biogeochem. Cycles, 12, 667-686.

Ramankutty, N., and J.A. Foley: Estimating historical

changes in global land cover: Croplands from 1700 to

1992. Global Biogeochem. Cycles, submitted.

Ramankutty, N., and J.A. Foley: Estimating historical

changes in land cover: North American croplands from

1850 to 1992. Global Ecology and Biogeography Letters,

submitted.

Woodward, F.I., W. Cramer, A. Bondeau, I.C. Prentice,

R.A. Betts, V. Brovkin, P.M. Cox, V. Fisher, J. Foley, A.D.

Friend, C. Kucharik, M.R. Loas, C. Molling, N.

Ramankutty, S. Sitch, and A. White: Dynamic responses

of global terrestrial vegetaiton to changes in CO2 and climate. Nature, submitted.

Investigation URL

http://cpep.meteor.wisc.edu
208 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Biosphere-Atmosphere Interactions

Principal Investigator – Inez Fung

Science Background

This investigation is directed at improving our understanding of the role of the terrestrial biosphere in global change

using models, in situ observations, and satellite data. Specifically, the science investigations in the project cover

both short-term (biophysics) interactions between the land

biosphere and the atmosphere and long-term (ecology,

anthropogenic impacts) interactions. One short-term focus of the work is to develop and use a coupled landbiosphere-atmosphere model to simulate the response of

the physical climate system to both radiative and physiological changes induced by increasing CO2 . This model

will have its surface boundary conditions largely specified from satellite data. Complementary work is focused

on the development of a range of carbon-cycle models

operating over a wide range of time scales, which will be

used to understand the follow-up response of the terrestrial biosphere to climate change.

Science Goal

The goal of the investigation is to first understand and

then to predict the response of the coupled terrestrial biosphere-global atmosphere system to global change, specifically to the increase in atmospheric CO2. In addition

to improving our understanding of the critical components

of the Earth system, this project should yield improved

products of derived surface and atmospheric parameters,

and will be directly useful in developing methodologies

to extract the maximum benefit from EOS observations.

Current Activities

The group has constructed a biophysics model (SiB2) and

a biogeochemical model (CASA), and has continued development of global climate and tracer transport models.

Versions of SiB2 and CASA models have been coupled

to different versions of the the Colorado State University

(CSU) GCM and the GISS atmospheric tracer transport

model. The flexible suite of models has been combined

with the NDVI time series to investigate biophysical and

biogeochemical interactions among energy, water and

carbon on interannual and longer time scales. The group

is also developing fundamental understanding in the use

of isotope information to elucidate water- and carbonexchange processes and to constrain interpretation of global water and carbon cycles. Time series of global gridded

satellite observations of the biosphere are produced and

analyzed. Related work is being done on improving remote-sensing calibration and other tools to derive vegetation-cover components and phenology.

Use of Satellite Data

The project will make strong use of the Terra and EOS

PM platform data. MODIS, MISR, and ASTER data will

be used to define surface properties for the SiB2 and

CASA models to replace those data sets that are currently

derived from AVHRR observations. AIRS data will be

used to check all aspects of the model’s performance including, among others, atmospheric states and radiation

fields. We have also been working with the POLDER sensor on ADEOS and the Lewis sensor. We plan to use the

data from the NPOESS sensors when the system becomes

available.

Participation in Field Programs

Many of the team members participate in field programs

which aim to further our understanding of important processes as well as teach us how to better use satellite data

in the models. These experiments have included:

FIFE: A study of land-atmosphere exchanges and remote

sensing, carried out in Kansas in the late 1980s.

BOREAS: Several investigators took part and will take

part in this large-scale, interdisciplinary study of the functioning of the boreal forest of Canada.

LBL: This experiment focuses on biosphere-atmosphere

interactions in tropical Amazonia. The ongoing analysis

of the data embraces aspects of land-surface climatology,

ecology, biogeochemistry, terrestrial ecology, and remote

sensing.

FIRE: This is a study of atmospheric radiative transfer

and the validation of remote-sensing algorithms.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 209

Principal Investigator

Inez Fung

Inez Fung is currently Director of the Center for Atmospheric Sciences and a Professor in the Department of

Geology and Geophysics and the Department of Environmental Science, Policy and Management at the University of California, Berkeley. She received her Sc.D. in

Meteorology from the Massachusetts Institute of Technology in 1977, and was a postdoctoral fellow at Goddard

Space Flight Center from 1977-1979. She was associated

with the Goddard Institute for Space Studies in various

capacities from 1979-1998. From 1993-1998, she was

Professor at the University of Victoria in Canada. She

was honored with NASA’s Medal for Exceptional Scientific Achievement (1989), election as a Goddard Senior

Fellow (1992-1997), as a Fellow of the American Meteorological Society (1994) and the American Geophysical

Union (1996).

Co-Investigators

Joe Berry - Carnegie Institution

James Collatz - NASA/Goddard Space Flight Center

A. Scott Denning -University of California at Santa Barbara

Christopher Field - Carnegie Institution

Christopher O. Justice - University of Virginia / NASAGSFC

Pamela A. Matson - Stanford University

Harold Mooney - Stanford University

David Randall - Colorado State University

Piers J. Sellers - Johnson Space Flight Center

Compton J. Tucker - NASA/Goddard Space Flight Center

Susan Ustin - University of California at Davis

Peter Vitousek - Stanford University

References

Denning, A.S., G.J. Collatz, C.G. Zhang, D.A. Randall,

J.A. Berry, P.J. Sellers, G.D. Colello, and D.A. Dazlich,

1996: Simulations of terrestrial carbon metabolism and

atmospheric CO2 in a general circulation model. 1. Surface carbon fluxes. Tellus, 48B, 521-542.

Denning, A.S., D.A. Randall, G.J. Collatz, and P.J. Sellers, 1996: Simulations of terrestrial carbon metabolism

and atmospheric CO2 in a general circulation model. 2.

Simulated CO2 concentrations. Tellus, 48B, 543-567.

Field, C.B., M.J. Behrenfeld, J.T. Randerson, and P.

Falkowski, 1998: Primary produciton of the biosphere:

Integrating terrestrial and oceanic components. Science

281, 237-240.

Fung, I., C.B. Field, J.A. Berry, M.V. Thompson, J.T.

Randerson, C.M. Malmstrom, P.M. Vitousek, G.J. Collatz,

P.J. Sellers, D.A. Randall, A.S. Denning, F. Badeck, and

J. John, 1997: Carbon-13 exchanges between the atmosphere and biosphere. Global Biogeochem. Cycles, 11,

507-533.

Myneni, R., C.D. Keeling, C.J. Tucker, G. Asrar, and R.

Nemani, 1997: Increased plant growth in northern high

latitudes from 1981 to 1991. Nature, 386, 698-702.

Randerson, J. T., M.V. Thompson, I.Y. Fung, T. Conway,

and C.B. Field, 1997: The contribution of terrestrial

sources and sinks to trends in the seaosnal cycle of atmospheric carbon dioxide. Global Biogeochem. Cycles, 11,

535-560.

Sellers, P.J., R.E. Dickinson, D.A. Randall, A.K. Betts,

F.G. Hall, J.A. Berry, C.J. Collatz, A.S. Denning, H.A.

Mooney, C.A. Nobre, and N. Sato, 1997: Modeling the

exchanges of energy, water, and carbon between the continents and the atmosphere. Science, 275, 502-509.

Sellers, P.J., L. Bounoua, G.J. Collatz, D.A. Randall, D.

Dazlich, S. Los, J. Berry, I. Fung, J. Tucker, C. Field, and

T.G. Jensen, 1996: A comparison of the radiative and

physiological effects of 2×CO2 on the global climate. Science, 271, 1402-1405.

Ustin, S.L., D.A. Roberts, J.E. Pinzon, S. Jacquemoud,

G. Scheer, C.M. Castaneda, and A. Palacios, 1998: Estimating canopy water content of chaparral shrubs using

optical methods. Remote Sens. Environ., 65, 280-291.

Investigation URL

http://sequoia.atmos.berkeley.edu/ids/ids.html
210 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Aerosols, Clouds, Chemistry, and Radiative

Forcing

Principal Investigator – Steven J. Ghan

Science Background

By burning fossil fuels and biomass, the human race is

altering both the composition of the atmosphere and the

radiation balance of the planet, perhaps enough to

noticably change the climate within the next few decades.

Combustion of fossil fuels and biomass yields emissions

of both CO2 and aerosols and their precursors. CO2 traps

infrared radiation and hence warms the planet, while aerosols primarily scatter sunlight and hence cool the planet.

Whether the radiative forcing due to anthropogenic aerosols dominates or is dominated by the radiative forcing

due to anthropogenic CO2 depends upon the relative emissions of these combustion products, their atmospheric lifetimes, and their radiative properties. Although anthropogenic emissions of CO2 dominate those of aerosols and

their precursors, and the atmospheric lifetimes of aerosols and their precursors are much shorter than that of

CO2, the global radiative forcing by aerosols resulting

from fossil fuel combustion is estimated to be roughly

comparable to that by CO2, per unit of fuel combusted.

However, the uncertainty in the estimates of the radiative forcing due to anthropogenic aerosols is much

greater than the uncertainty in the radiative forcing due

to increasing CO2 concentrations. This uncertainty is

partly due to the short lifetime and hence heterogeneous

distribution of anthropogenic aerosols, and partly due to

the complex manner in which aerosols affect the planetary radiation balance. Aerosols can alter the planetary

radiation balance directly by scattering, absorbing, and

emitting solar and infrared radiation, and indirectly by

serving as cloud condensation nuclei (CCN), thereby increasing cloud droplet number and cloud albedo. Direct

radiative forcing is complicated by water uptake by aerosol particles, which depends not only on ambient relative

humidity but also on the history of relative humidity encountered by the aerosol particle. Indirect radiative forcing through the role of anthropogenic aerosols as CCN

depends not only on the concentration of the aerosols,

but also on the concentration of other aerosols that compete for water when cloud droplets are formed. Reducing

the uncertainties in estimates of the radiative forcing due

to anthropogenic aerosols will therefore require methods

that can account for considerable complexity.

Science Goal

To reduce the uncertainty in estimates of the radiative forcing due to anthropogenic aerosols, this investigation focuses on the development, evaluation, and application of

an integrated global modeling system designed to provide refined physically based estimates of both direct and

indirect radiative forcing by anthropogenic aerosols. This

global modeling system, once properly evaluated through

comparison with surface, in situ, and remote measurements, can serve as an intelligent interpolator of observations, providing the ability to distinguish between natural

and anthropogenic aerosols.

Current Activities

We have coupled the Pacific Northwest National Laboratory (PNNL) global chemistry/aerosol model in-core

memory with the PNNL version of the National Center

for Atmospheric Research (NCAR) Community Climate

Model (CCM2). The PNNL global chemistry/aerosol

model simulates the sulfate, methane sulfonic acid (MSA),

carbonaceous, dust and sea salt aerosol mass for specified size distributions in both the aqueous and interstitial

phase. The PNNL version of the NCAR CCM2 simulates

mass and number concentrations of cloud droplets and

ice crystals. The two models interact through the influence of aerosols on radiative heating and cloud droplet

number and through the influence of clouds on aqueous

chemistry and wet removal of aerosol. Nudging of the

simulated winds toward observations is applied so that

the simulated aerosol can be evaluated on timescales of

days as well as months.

Estimates of direct radiative forcing by aerosols have

generally either relied upon field measurements or classical Kohler theory to treat the dependence of water uptake on relative humidity. However, field measurements

cannot distinguish the influence of different aerosol compositions, and Kohler theory cannot account for hysteresis. To improve upon these treatments, we are developing a dynamic aerosol growth model suitable for global

simulations. Depending on the composition, ambient RH,

and particle history, the aerosol may be completely solid,

completely liquid, or mixed-phase.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 211

The treatment of a variety of aerosols is motivated

by the hypothesis that aerosols compete for water when

cloud droplets form, so that any estimate of the indirect

radiative forcing by a particular aerosol species will depend upon the concentration of all other aerosol species.

To test this hypothesis, we are conducting global experiments with several different values of a prescribed background aerosol. We are also using a detailed aerosol activation model to test the hypothesis for a variety of aerosol types, and are developing a refined parameterization

of aerosol activation for multiple aerosol types.

Measurements of the composition of CCN in remote

locations have indicated the presence of considerable organic material. We are therefore developing a model of

tropospheric chemistry that treats organic chemistry and

sulfur chemistry in much more detail. Parallel simulations

with the present simple chemistry mechanism and with

the more-detailed mechanism will be compared to determine the impact of the more-detailed chemistry on the

estimated radiative forcing.

Aerosol size distribution is presently prescribed in

terms of log-normal distributions for Aitken, accumulation, and coarse modes. Such a treatment lacks the flexibility needed to properly treat aerosol activation, in which

a larger mass fraction than number fraction is typically

activated for each aerosol mode. To distinguish between

the activation of aerosol number and mass, we are exploring the prediction of number as well as mass for each

aerosol mode.

Recent work with regional models has shown that

heterogenous reactions on aerosol surfaces can have a significant impact on tropospheric ozone. We are using our

model to investigate this problem in a global atmosphere.

Use of Satellite Data

We use satellite data primarily to evaluate model performance. We are presently relying on AVHRR data to evaluate the simulated aerosol optical depth. Using daily analyses of AVHRR data by NOAA and by Brookhaven National Laboratory, we form composites of simulated optical depth for the same times as the AVHRR observations.

Differences between the simulated and analyzed optical

depths can reflect errors in the simulated optical depth,

but can also arise from errors in the aerosol composition

and size distribution assumed in the AVHRR analysis. To

reduce ambiguity in the interpretation, we therefore are

focusing on the “aerosol radiance” (the difference between

the radiance observed by the satellite and what the radiance would be in the absence of aerosols) as the figure of

merit.

To assess the simulation of indirect radiative forcing, we are currently relying on Qingyuan Han’s estimate

of droplet effective radius from AVHRR data, Tom

Greenwald’s estimate of cloud liquid water path from

SSM/I microwave measurements, and on the ERBE measurements of cloud radiative focing. After the launch of

the TRMM and Terra satellites, we will rely on analyses

of CERES measurements for cloud radiative forcing and

MODIS measurements for cloud optical depth and cloudtop particle size.

Global mid-tropospheric distributions of CO obtained

from the Measurement of Air Pollution by Satellites

(MAPS) experiments that took place in April and October of 1994 are being used to test the model’s performance

in simulating free tropospheric chemistry. After the launch

of the Terra satellite we will use MOPITT estimates of

tropospheric CO.

Participation in Field Programs

We have compiled a multi-year data set of aerosol optical

depths measured daily by solar radiometers and rotating

shadowband radiometers at a variety of sites across the

continental United States, Barrow, Alaska, Mauna Loa,

Barbados, Bermuda, Teneriffe, the Canary Islands, Mace

Head Ireland, Tasmania, and the South Pole.

Principal Investigator

Steven J. Ghan

Steven J. Ghan received his B.S. in Atmospheric Science

from the University of Washington in 1979 and his Ph.D.

in Meteorology from the Massachusetts Institute of Technology in 1988. From 1984 to 1990 he worked at the

Lawrence Livermore National Laboratory, coupling a global aerosol model with a global circulation model to investigate the nuclear winter hypothesis. In 1990 he became a Senior Research Scientist at Battelle Pacific Northwest Laboratory, where he has focused on improving the

treatment of clouds and cloud-aerosol interactions in global models and on representing the subgrid influence of

mountains on clouds and precipitation in regional models. He has been a member of the Department of Energy

Atmospheric Radiation Measurement Science Team since

1991, and an affiliate associate professor at the University of Washington since 1992.

Co-Investigators

Richard C. Easter - Battelle Pacific Northwest Laboratory

Rick D. Saylor - Georgia Institute of Technology
212 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

References

Ghan, S.J., C.C. Chuang, and J.E. Penner, 1993: A parameterization of cloud droplet nucleation. Part I: Single

aerosol type. Atmos. Res., 30, 197-222.

Ghan, S.J., C.C. Chuang, R.C. Easter, and J.E. Penner,

1995: A parameterization of cloud droplet nucleation. Part

II: Multiple aerosol types. Atmos. Res., 36, 39-54.

Ghan, S.J., R.C. Easter, Y. Zhang, L.R. Leung, R.D.

Saylor, L.K. Peters, R. Zaveri, and P. Lee, 1997: Radiative forcing of climate by aerosols: A physically based

modeling approach. Proceedings of the Third AMS Conference on Atmospheric Chemistry, Long Beach CA, February 1997.

Ghan, S.J., L.R. Leung, and Q. Hu, 1997: Application of

cloud microphysics to NCAR CCM2. J. Geophys. Res.,

102, 21,777-21,794.

Ghan, S.J., L.R. Leung, R.C. Easter, and H. Abdul-Razzak,

1997: Prediction of droplet number in a general circulation model. J. Geophys. Res., 102, 777-794.

Zaveri, R., 1997: Development and evaluation of a comprehensive tropospheric chemistry model for regional and

global applications. Ph.D. dissertation. Virginia Polytechnic Institute and State University, Blacksburg, Virginia,

USA.

Investigation URL

http://www.pnl.gov/atmos_sciences/as_clim.html

Clear-sky mean aerosol optical depth for August 1994 as derived from AVHRR radiance measurements and as simulated by the PNNL

global aerosol model. Data is unavailable for the Southern Hemisphere because the satellite flew in the darkness there.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 213

Use of the Cryospheric System (CRYSYS) to

Monitor Global Change in Canada

Principal Investigator – Barry E. Goodison

International Sponsor - Canada

Science Background

The cryosphere is an important component of the global

climate system, involving complex feedback mechanisms

of differing magnitude and sign. At the global scale, there

is a large body of evidence documenting an inverse relationship between the amount of snow and ice on the

Earth’s surface and global mean temperature. There are,

however, important regional exceptions to this generalization, and greater understanding of cryospheric processes

and their spatial and temporal variability is required to

reduce the uncertainties in modeling regional and global

climates and the hydrological cycle. Improved understanding of cryospheric variability is particularly relevant in

Canada where a wide range of economic activities are

sensitive to variations in cryospheric elements.

Science Goals

The basic scientific goals of CRYSYS are to:

1) develop capabilities for monitoring and understanding variations in cryospheric variables across a range

of scales;

2) develop and validate local, regional, and global models of climate/cryospheric processes and dynamics

to improve understanding of the role of the cryosphere

in the climate system; and

3) assemble, maintain, and analyze key historical, operational, and research cryospheric data sets to support climate monitoring and model development.

Current Activities

The broad goals of CRYSYS are being addressed through

five scientific themes corresponding to the main elements

of the cryosphere in Canada: glaciers and ice caps, sea

ice, lake ice, snow, and frozen ground/permafrost. There

is a CRYSYS data management activity to address data

issues and a cross-cutting cryospheric modeling component. Brief overviews of the activities of each theme follow. The theme leader is identified for each component.

Glaciers and ice caps (M. Brugman): This component

focuses on the development of new techniques for monitoring glaciers and ice caps with remotely sensed data,

complementary in situ validation, and continuing enhancement and access to conventional glacier information such

as the Canadian Glacier Inventory.

Sea ice (E. LeDrew): CRYSYS sea-ice research focuses

on field investigations for development and validation of

microwave algorithms for first-year and multi-year sea

ice, depth of snow on sea ice, and modeling of interannual variability and sea-ice-climate feedback processes.

Lake ice (A. Walker): Lake-ice studies focus on the use

of passive and active microwave satellite data to extract

geophysical information related to lake-ice processes and

the identification of freeze-up/break-up events for climate

variability and change analysis.

Snow (A. Walker): Main thrusts in CRYSYS snow-related research are the development and validation of passive and active microwave algorithms for snow-cover

properties (extent, water equivalent, wet/dry state) in varying landscapes; the synergism between active and passive microwave data for enhancing snow-cover information retrieval; generation of information products in nearreal time; and reconstruction of historical snow cover from

conventional and remotely-sensed data to document and

better understand long-term variability in snow cover.

Frozen ground/permafrost (C. Duguay): The frozenground research focuses on the development of new means

for mapping/monitoring seasonally and perennially frozen ground (permafrost), and associated features (e.g.,

thaw slumps, active-layer detachment slides, thaw lakes)

using optical and microwave remote-sensing data.

Cryospheric Modeling (G. Flato): CRYSYS research activities are contributing to the validation and improvement of the representation of the cryosphere in global climate models. To date, most of the CRYSYS modeling

activities have focused on sea ice, such as studies to simulate landfast-ice variability in the Canadian high Arctic

over a range of time scales from diurnal to interannual.
214 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Use of Satellite Data

CRYSYS requires the effective combination of data from

many conventional or ground data sets, from airborne

campaigns, and from remotely sensed information from

EOS and non-EOS platforms.

Current passive microwave data from SSM/I on the

DMSP platforms are the basis for the development of

snow, lake-ice, and sea-ice algorithms for AMSR and future SSM/I sensors. SAR data from ERS-1 and 2 and

Radarsat are critical for all components of the cryosphere

being studied under CRYSYS. AVHRR is the current sensor for large-area studies before MODIS becomes available in the EOS era. ASTER will support targeted glacier/ice cap and frozen-ground investigations. CRYSYS

team members interact directly with the NSIDC and ASF

DAAC facilities and Canadian agencies in most of their

studies.

Examples of the use of current satellite data for

CRYSYS research include: acquisition of DMSP SSM/I

data in near real-time for the development of algorithms

to derive snow-water equivalent (SWE), extent, and snowpack state for different landscape regions of Canada and

generate snow-cover information products for climate

analyses (including modeling) and water resource monitoring and forecasting (such as depicted in the figure on

the following page); development and implementation of

an SWE algorithm using Radarsat data for hydroelectric

forecasting in Northern Quebec; SSM/I 85-GHz brightness-temperature data for large lakes in northern Canada

to discriminate between ice cover and open water, for

monitoring freeze-up/break-up patterns for the entire lake;

application of SAR and Landsat TM data for improving

glacier-runoff modeling and glacier mass balance; the

practical application of SAR interferometry for topographic measurements on glaciers; and the synergism

between optical (Landsat, SPOT) and active microwave

(ERS-1/2, JERS-1, Radarsat) data for mapping frozenground and permafrost phenomena.

Participation in Field Programs

All CRYSYS components involve extensive field investigations for algorithm development and validation, often in conjunction with other international initiatives such

as BOREAS and GEWEX/MAGS (Mackenzie GEWEX

Study). Detailed measurements of geophysical properties

of first-year and multi-year ice have been taken at the

SIMMS/C-ICE (Seasonal Sea Ice Monitoring and Modeling Site/Collaborative-Interdisciplinary Cryospheric Experiment) field site near Resolute, North West Territories

(NWT), since 1990.

Extensive airborne and ground networks have been

established in major landscape target sites throughout

Canada (including prairie, boreal forest, tundra) for repeated ground-measurement and passive-microwave surveys for data acquisition in support of satellite microwave

(e.g., SSM/I, Radarsat) snow-algorithm developing, testing, and validation. Five permafrost study sites have been

established (Mayo and Old Crow, YT; Churchill, Man.;

Fosheim Peninsula, NWT; and Umiujaq, Que.) and intensive field campaigns have been mounted in the

Churchill area over the past two summers to map surface

cover, active-layer depth, and permafrost-related terrain

features. Glacier and ice-cap mass-balance measurements

continue to be made at long-term monitoring sites in western Canada and the Canadian Arctic.

Principal Investigator

Barry Goodison

Barry Goodison received his Ph.D. from the University

of Toronto and has over 30 years of exeperience in

cryosphere, precipitation measurement, and climate/

cryosphere studies as a scientist with the Atmospheric

Environment Service, Environment Canada. He has led

several national and international field studies on components of the cryosphere, especially snowfall and snow

cover. He recently led the World Meteorological Organization Intercomparison on the Measurement of Solid Precipitation, and was an investigator and organizer of the

Boreal Ecosystem Atmosphere Study (BOREAS). He

currently is a member of the WCRP Task Group on

Cryosphere and Climate. He has served on, or chaired,

many scientific committees and working groups, including several for NASA.

Co-Investigators

David Barber - University of Manitoba

Monique Bernier - INRS-EAU, Université du Québec

Ross Brown - Atmospheric Environment Service

Melinda Brugman - Columbia Mountains Institute for Applied Ecology

Claude Duguay - Centre d’études nordiques, Université

Laval

Greg Flato - Atmospheric Environment Service

Hardy Granberg - University of Sherbrooke

Roy Koerner - Geological Survey of Canada

Ellsworth LeDrew - University of Waterloo

Lawrence Mysak - McGill University

Terry Pultz - Canada Centre for Remote Sensing

Anne Walker - Atmospheric Environment Service

Ming-ko Woo - McMaster University
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 215

References

Bernier, M., and J.P. Fortin, 1998: The potential of time

series of C-band SAR data to monitor dry and shallow

snow cover. IEEE Trans. Geosci. Remote Sens., 36, 1-18.

Brown, R.D., and B.E. Goodison, 1996: Interannual variability in reconstructed Canadian snow cover, 1915-1992.

J. Climate, 9, 1299-1318.

Chang, A.T.C., J.L. Foster, D.K. Hall, B.E. Goodison, A.E.

Walker, J.R. Metcalfe, and A. Harby, 1997: Snow parameters derived from microwave measurement during the

BOREAS winter field campaign. J. Geophys. Res., 102,

29,663-29,671.

Demuth, M.N., and A. Pietroniro, 1999: Inferring glacier

mass balance using RADARSAT—results from Peyto

Glacier, Canada. Geografiska Annaler, 81A, in press).

Derksen, C., E. LeDrew, and B. Goodison, 1998: SSM/I

derived snow water equivalent data: The potential for investigating linkages between snow cover and atmospheric

circulation. Atmos.-Ocean, 36, 95-117.

De Seve, D., M. Bernier, J.-P. Fortin, and A. Walker, 1997:

Preliminary analysis of snow microwave radiometry using the SSM/I passive-microwave data: The case of La

Grande River watershed (Quebec). Annals of Glaciology,

25, 353-361.

Duguay, C.R., W.R. Rouse, P.M. Lafleur, D.L. Boudreau,

Y. Crevier, and T.J. Pultz, 1999. Analysis of multi-temporal ERS-1 SAR data of subarctic tundra and forest in

the northern Hudson Bay Lowland and implications for

climate studies. Can. J. Remote Sensing, 25, 21-33.

Flato, G.M., and R.D. Brown, 1996: Variability and climate sensitivity of landfast Arctic sea ice. J. Geophys.

Res., 101, 25,767-25,777.

Goodison, B.E., R.D. Brown, G. Flato, M. Brugman, C.R.

Duguay, E.F. LeDrew, and A.E. Walker, 1999: CRYSYS—

Use of the cryospheric system to monitor global change

in Canada: Overview and progress. Can. J. Remote Sensing, 25, 3-11.

Hanesiak, J.M., D.G. Barber, and G.M. Flato, 1998: The

role of diurnal processes in the seasonal evolution of sea

ice and its snow cover. J. Geophys. Res., in press.

Leverington, D.W., and C.R. Duguay, 1997: A neural network method to determine the presence or absence of permafrost near Mayo, Yukon Territory, Canada. Permafrost

and Periglacial Processes, 8, 205-215.

Lewkowicz, A.G., and C.R. Duguay, 1999: Detection of

permafrost features using SPOT panchromatic imagery,

Fosheim Peninsula, Ellesmere Island, N.W.T. Can. J. Remote Sensing, 25, 34-44.

Piwowar, J.M., D.R. Peddle, and E.F. LeDrew, 1997: Temporal mixture analysis of Arctic sea ice imagery: a new

approach for monitoring environmental change. Remote

Sens. Environ., 63, 195-207.

Vachon, P.W., D. Geudtner, K. Mattar, A.L. Gray, M.

Brugman, and I. Cumming, 1996: Differential interferometry measurements of Athabasca and Saskatchewan

glacier flow rate. Can. J. Remote Sensing, 22, 287-296.

Investigation URL

http://www1.tor.ec.gc.ca/crysys/

Passive microwave (SSM/I)-derived snow water equivalent for

March 1, 1988 (drought year) and March 1, 1997 (flood year) on

the Canadian prairies (shaded area).
216 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Freshwater Cycle in the Global Ocean

Principal Investigator – Sirpa Hakkinen

Science Background

The heat transport in the oceans and the global-conveyorbelt concept to explain the renewal of the deep ocean has

received more attention in the scientific literature than

the oceanic freshwater conveyor. The thermal-conveyor

circulation implies that the northern Atlantic source is the

dominant deep-water source for the global ocean. The

conversion of surface water to bottom water in the northern hemisphere occurs mainly through heat loss while the

freshwater flux tries to oppose the process. There is a small

contribution to the northern dense waters from the Arctic

water masses which form as a result of brine rejection, as

it is the only means of densification in ice-covered areas.

In the Southern Ocean, brine rejection is the main process of densification, but there are occasional polynyas

in deep water in the Ross and Weddell Seas where deep

convection may occur.

Ice-core and sediment data show that there have been

large fluctuations in the past in the thermohaline circulation which have been associated with the changes in the

freshwater storage in ice sheets. Superimposed on this

long-time-scale variability, the ice-core data show intense

shorter timescale variability which can be interpreted to

result from thermohaline circulation changes. The verylong-period variability in the hydrological cycle associated with the ice sheets is not of immediate interest in our

study. The distribution of freshwater from sea ice and precipitation minus evaporation (P-E) sources is of importance to thermohaline circulation on interannual-todecadal time scales by modifying the surface-water masses

and mixing processes at subpolar-to-polar latitudes. This

variability affects deep waters as well as mode waters (intermediate water masses), which can have a climatic impact on decadal scale because they will come into contact

with the atmosphere much faster than the deep waters.

More importantly, the basic knowledge of the freshwater

cycle in the present climate is not well known, mainly

due to the lack of good quality observational P-E data.

Assimilated P-E products from atmospheric models can

be flawed because the models can have serious biases in

their moisture-transport and boundary-layer treatment. A

manifestation of such model bias together with oceanmodel bias is the need for flux correction when the models are coupled. For instance the GFDL coupled model

(Manabe and Stouffer, 1988) shows that the largest model

drift occurs in the areas of deep-water formation, such as

in the Greenland Sea and mainly affects the surface salinity fluxes.

The sea-ice regions are sources of variability in the

freshwater cycle in the ocean through ice advection

(Hakkinen, 1993, 1995), but, more importantly, these regions also provide the connections to the other ocean basins. Thus, the freshwater cycle is truly interhemispheric

in nature with interbasin connections through the Arctic

and the Southern Ocean. The only interbasin connection

outside polar/subpolar regions is through the Indonesian

archipelago.

Poleward of 45 N/S the land and oceans receive net

precipitation which has to be returned back to the equatorial regions. The subpolar/polar regions are also source

regions for the below-thermocline and deep/bottom waters; thus a part of the freshwater route back to global

system coincides with the thermohaline circulation. The

redistribution of freshwater between the two basins is significant for the conveyor circulation as shown by several

modeling studies, e.g., Marotzke and Willebrand (1991).

However, the freshwater route from the northern Pacific

through the Arctic Ocean to the Atlantic has been neglected, and Wijffels et al. (1992) suggest that most of

the net freshwater gain (from the atmosphere) by the North

Pacific is routed through the Arctic. Considering this

northern freshwater route, a study by Shaffer and Bendtsen

(1994) is of importance: A three-box model describes the

multiple equilibria as a result of water-mass exchange

between the Pacific and the Atlantic. The general tendency

of the solutions is that with larger flow/deeper Bering Strait

the conveyor solution is suppressed while closing of the

Strait favors the conveyor solution. Besides the depth of

the Strait, two other free parameters of the model are the

freshwater transport to the northern regions and how it is

divided between the North Pacific and North Atlantic.

With increasing total freshwater transport the North Atlantic sinking would be less likely, unless the fractional

portion of the transport to the Pacific is increased. Thus

the northern freshwater route complicates the scenarios

for the variability of the thermohaline conveyor. This is

especially relevant for the global-warming scenarios

which imply enhanced moisture transport to the high latitudes.

Science Goal

The objective of this proposal is to study the freshwater

transports in the global ocean using coupled ocean and
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 217

ice models. The hydrological cycle in the oceans requires

inclusion of the polar regions for closure because the midto-high-latitude net precipitation, and runoff from continents, has to be returned to the rest of the world ocean.

The freshwater conveyor opposes the thermal conveyor

at the high latitudes where deep-water-formation regions

are located. The variability of freshwater flux is of critical importance in these areas as the freshwater fluxes influence the global thermohaline circulation and thus provide a source for long-term climate variability. The proposed effort complements the present Earth Science Enterprise (ESE) study of the global hydrological cycle and

supports the ESE goal towards understanding of mechanisms and factors which determine long-term climate

variations and trends.

Our goal is to model the freshwater conveyor as it

exists in the present climate using precipitation data from

SMMR, SMM/I, and TRMM, as well as corresponding

runoff data (from our land surface/ river model). We plan

to estimate magnitudes of disturbances and their effects

on the thermohaline cell. One such disturbance of interest is the distribution of the atmospheric freshwater transport between the N. Pacific and N. Atlantic.

Current Activities

The development of a generalized vertical-coordinate

ocean model is the first task, which will include the same

physics, such as the turbulence-closure model (which predicts the vertical diffusion of momentum, temperature,

and salinity), as in the POM (Princeton Ocean Model;

Blumberg and Mellor 1987). The latter model uses sigmacoordinates in the vertical where the model layers follow

the terrain and requires considerable smoothing of the topography with decreasing resolution. Thus, modifications

are necessary to accommodate some detail in topography

in a coarse-resolution grid (2×2 degrees) but retaining

some bottom boundary-layer physics, which is important

for deep flows, i.e., thermohaline circulation. Inclusion

of flexible vertical-layer structure could also allow the

use of density surfaces to define layers, because the layers have to be updated every time step. The generation of

a global grid that avoids the north-pole convergence and

avoids any other boundary conditions than cyclic conditions requires some consideration and effort.

The freshwater cycling in the ocean is studied first in

a diagnostic framework and later on in quasi-equilibrium

runs for a specified freshwater forcing. Given the equilibration time scale of thousands of years for oceanic thermohaline circulation, even a 2×2-degree model can be

too long to run for several experiments. However, tendencies in the model behavior can be equally illuminating of the physics and adequate for the study of the sensitivity of the interbasin freshwater export from the Pacific

to the Atlantic via the Arctic Ocean.

Use of Satellite Data

Model input requires precipitation minus evaporation data

to study the freshwater conveyor using data from SMMR,

SMM/I, and TRMM, as well as corresponding runoff data

(from our land surface/ river model).

Principal Investigator

Sirpa Hakkinen

Sirpa Hakkinen received her Bachelor of Science (1974)

and Master of Science (1976) degrees in Physics from

the University of Helsinki, Finland. Her Ph.D. is in Geophysical Fluid Dynamics from Florida State University

(1984). Since 1990 she has been a member of the Oceans

and Ice Branch at NASA Goddard Space Flight Center.

She has worked on coupled sea-ice and ocean models to

study mesoscale processes and during recent years has

investigated interannual-to-decadal variability in the Arctic and North Atlantic Oceans.

Co-Investigator

George L. Mellor - Princeton University

References

Blumberg, A.L., and G.L. Mellor, 1987: A description of

a three-dimensional coastal ocean circulation model,

‘Three dimensional coastal ocean models’ (ed. N. S.

Heaps), 1-16, Am. Geophys. Union, Wash. DC.

Hakkinen, S., 1993: An Arctic source for the Great Salinity Anomaly : A simulation of the Arctic Ice Ocean System for 1955-1975. J. Geophys. Res., 98, 16,397-16,410.

Hakkinen, S., 1995: Simulated interannual variability of

the Greenland Sea deep water formation and its connection to surface forcing. J. Geophys. Res., 100, 4761-4770.

Manabe, S., and R.J. Stouffer, 1988: Two stable equilibria of a coupled ocean-atmosphere model. J. Climate, 1,

841-866.

Marotzke, J., and J. Willebrand, 1991: Multiple equilibria of the global thermohaline circulation. J. Phys.

Oceanogr., 21, 1372-1385.

Shaffer, G., and J. Bendtsen, 1994: Role of the Bering

Strait in controlling North Atlantic ocean circulation and

climate. Nature, 367, 354-357.

Wijffels, S.E., R.W. Schmitt, H.L. Bryden, and A.

Stigebrandt, 1992: Transport of freshwater by the oceans.

J. Phys. Oceanogr., 22, 155-162.
218 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Interannual Variability of the Global Carbon,

Energy, and Hydrologic Cycles

Principal Investigator – James E. Hansen

Science Background

Global climate change has attained paramount interest in

Earth sciences because of its potential to affect human

activities and the environment. A crucial science issue is

to understand the possible anthropogenic role in observed

climate change. Mankind’s alteration of the carbon cycle,

through burning of fossil fuels and deforestation, is expected to significantly alter the planet’s temperature and

thermal-energy cycle, and perhaps the most important

impact of this will be on water distribution and the hydrologic cycle. Measurable changes in the carbon, energy,

and water cycles are occurring on a year-to-year basis.

Analysis of these changes and their relationships has great

potential to improve predictability of future climate

change.

Science Goals

The ultimate objective of our study of the combined carbon, energy, and water cycles concerns global climate

change, specifically an understanding of current and recent interannual climate variability and trends, as well as

an ability to reliably predict the future climatic impact of

anthropogenic activities. Achievement of the climate research goals is dependent upon appropriate global observations of climate forcings, feedbacks, and diagnostics,

and thus our role in EOS and the overall NASA Earth

Science Enterprise is to help define needed observations

and to use these observations in our research as they become available during the EOS flight era.

Current Activities

Our present focus is on analysis of the change of the global energy, water, and carbon cycles during the period

after the 1991 eruption of the Mount Pinatubo volcano.

The stratospheric aerosols produced by this volcano altered the thermal-energy balance by an amount comparable in magnitude to the perturbation that will be caused

by doubling of atmospheric carbon dioxide. Pinatubo thus

provides an excellent opportunity to test our understanding of the sensitivity of these global cycles to a global,

albeit short-term, forcing. Observational evidence exists

for changes of global and continental temperatures, in atmospheric carbon dioxide and methane abundances, and

patterns of precipitation. We are involved in both development of data sets to document these changes and modeling studies to interpret the changes.

Use of Satellite Data

Understanding of climate change can be achieved only if

the major global climate forcings and radiative feedbacks

are monitored with adequate precision, which accounts

for special dependence of our studies on data from several EOS instruments. ACRIM III and SOLSTICE will

provide data essential to determination of the role of solar variability in global climate change. SAGE III will

provide data on climate forcings due to changes of stratospheric aerosols, water vapor, and ozone. EOSP will measure tropospheric aerosols, the most uncertain of all anthropogenic climate forcings.

Measurements of long-term changes of cloud properties induced by aerosols and other anthropogenic effects represent a great challenge because of the needed

precision and diurnal sampling. The Earth Science Enterprise is expected to provide the possibility for these measurements through small Earth Probe satellites.

The most fundamental diagnostics for our climate

analyses are precise changes of temperature in the atmosphere, on the surface, and in the ocean, along with the

planetary radiation balance. Thus we rely on AMSU and

MHS data from operational satellites and EOS, as well as

radiosonde and meteorological station measurements.

Ocean temperatures are provided by ships and buoys;

acoustic tomography may provide information on future

trends of internal ocean temperatures over large regions.

CERES on EOS provides monitoring of the planetary radiation balance, and, in combination with MODIS and

other EOS instruments, will allow comprehensive analyses of cloud processes.

Participation in Field Programs

The greatest uncertainty in global climate forcings is the

poor knowledge of changes in anthropogenic aerosols in

the troposphere. Because of the great difficulty in measuring aerosol properties with sufficient accuracy from

space, we have helped organize a proposed international
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 219

network of sun photometers, with the principal objective

being measurement of aerosol changes. This proposed

effort would involve students centrally in the data collection and analysis, thus contributing to science education

as well as environmental studies.

Principal Investigator

James E. Hansen

James Hansen heads the Goddard Institute for Space Studies (GISS). A student of Astronomy and Physics (Ph.D.

from the University of Iowa, 1967), he has focused his

research primarily on radiative transfer in planetary atmospheres and related interpretation of remote soundings,

development of simplified climate models and three-dimensional global models, and the study of climate mechanisms. In addition to his research and administrative duties at GISS, he serves as Adjunct Professor at Columbia

University.

Co-Investigators

James K.B. Bishop - Lawrence Berkeley National Laboratory

Inez Y. Fung - University of California-Berkeley

Michael J. Prather - University of California-Irvine

Peter H. Stone - Massachusetts Institute of Technology

The following are from the NASA/Goddard Institute for

Space Studies:

Barbara E. Carlson

Anthony Del Genio

Andrew A. Lacis

Elaine Matthews

Ronald Miller

Michael Mishchenko

David H. Rind

Drew Shindell

Ina Tegen

William B. Rossow

References

Del Genio, A.D., 1996: Observational requirements for

modeling of global and regional climate change. NATO

ASI Series, 45, 31-57.

Fung, I., 1996: The global carbon cycle and the atmospheric record: “the problem definition.” NATO ASI Series, 40, 25-34.

Hansen, J., and 30 co-authors, 1996: A Pinatubo climate

modeling investigation. NATO ASI Series, 42, 233-272.

Hansen, J., M. Sato, A. Lacis, and R. Ruedy, 1997: The

missing climate forcing. Phil. Trans. Roy. Soc. Lond. B,

352, 231-240.

Hansen, J., M. Sato, A. Lacis, R. Ruedy, I. Tegen, and E.

Matthews, 1998: Climate forcings in the industrial era.

Proc. Nat. Acad. Sci., 95, 12,753-12,758.

Hansen, J., and 42 co-authors, 1997: Forcings and chaos

in interannual to decadal climate change. J. Geophys. Res.,

in press, Nov. 27 issue.

Lin, B., and W.B. Rossow, 1997: Precipitation water path

and rainfall rate estimates over oceans using special sensor microwave imager and International Satellite Cloud

Climatology Project data. J. Geophys. Res., 102, 9359-

9374.

Matthews, E., 1997: Global litter production, pools, and

turnover times. J. Geophys. Res., 102, 18,771-18,800.

Mishchenko, M.I., and L.D. Travis, 1997: Satellite retrieval of aerosol properties over the ocean using intensity and/or polarization of reflected sunlight: effect of measurement errors and aerosol absorption. J. Geophys. Res.,

102, 13,543-13,553.

Prigent, C., W.B. Rossow, and E. Matthews, 1998: Global maps of microwave land surface emissivities: potential for land surface characterization. Radio Sci., 33, 745-

751.

Rosenzweig, C., J.R. Phillips, R. Goldberg, J. Carroll, and

T. Hodges, 1996: Potential impacts of climate change on

citrus and potato production in the U.S. Agricultural Systems, 52, 455-479.

Shindell, D.T., D. Rind, and P. Lonergan, 1998: Increased

polar stratospheric ozone losses and delayed eventual recovery owing to increasing greenhouse gas concentrations.

Nature, 392, 589-592.

Shindell, D.T., S. Wong, and D. Rind, 1997: Interannual

variability of the Antarctic ozone hole in a GCM. J. Atmos.

Sci., 54, 2308-2319.

Investigation URL

http://www.giss.nasa.gov
220 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Climate Processes Over the Oceans

Principal Investigator – Dennis Hartmann

Science Background

The surface climate of Earth is strongly influenced by the

amount and distribution of water vapor, liquid water, and

ice suspended in the atmosphere. The response of water

vapor and clouds to a climate change is the single most

important feedback process determining the magnitude

of the climate change expected from forcings such as increasing carbon dioxide in the atmosphere. The processes

that control water in the atmosphere are very complex

and extend across a wide range of spatial scales from the

few-centimeter scale of turbulence in the boundary layer

to the tens of thousands of kilometers that characterize

the scale of global atmospheric circulation systems. Seventenths of the surface of Earth is covered with ocean, so

that the humidity and cloud structure of the global atmosphere are largely determined by processes occurring in

oceanic areas. The climate over land areas is in substantial measure determined by processes that occur over the

oceans.

Science Goals

The overall goal of this investigation is to achieve improved modeling of the atmosphere and its interactions

with the ocean through use of new data from satellites as

well as through use of existing data. The intent is to address the roles of circulation, clouds, radiation, water vapor, and precipitation in climate change, and the role of

ocean-atmosphere interactions in the energy and water

cycles. This investigation is contributing to a comprehensive understanding of climate and its natural variability,

and thereby to reduced uncertainty in predictions of future climate changes.

Current Activities

Available satellite observations, in situ data, and global

assimilated-data sets, and a variety of models are being

used to construct an integrated view of atmospheric climate over the oceans and to improve understanding and

modeling of climate feedback processes. The physical processes considered involve boundary-layer dynamics and

resulting fluxes, cloud-scale and mesoscale dynamics,

cloud physics, and global-scale circulations. Interactions

among clouds, water vapor, and radiation fluxes, and

among various scales of motion from small scale to planetary scale are incorporated. Important phenomena being

studied are described below:

• Boundary-layer fluxes of heat, momentum, and moisture: The vertical exchanges of heat, moisture, and energy across the planetary boundary layer are critical to

both the oceanic state and the atmospheric state. These

fluxes are being studied with observations and models.

• Marine boundary-layer clouds: Low clouds over the

ocean are extremely important for the energy balance

of Earth because they are abundant and reflect large

amounts of solar energy, but have only a small effect

on escaping longwave radiation. Albedos of low-level

clouds may be sensitive to sulfur aerosols produced by

humans. Long-term trends in low clouds and their relation to SST and other variables are being derived from

long records of surface observations. Efforts are underway to improve the ability of global climate models

to simulate marine-boundary-layer clouds.

• Tropical convective clouds: Deep convective clouds in

the tropics are the primary mechanism whereby solar

heating of the ocean is moved upward into the free troposphere where it can be transported poleward and

eventually emitted to space. The spatial organization

and temporal development of convective systems and

their relation to large-scale conditions are being studied with data from geosynchronous satellites and global meteorological analyses. Water-vapor data from

TOVS, GOES, and GMS are being used to study the

effect of deep convection and associated large-scale

circulations on the moisture budget of the upper troposphere of the tropics. Explicit simulations with regionalscale models are being compared with observations to

understand the relationships between convective cloud

properties and large-scale climate.

• Midlatitude synoptic systems: These systems produce

most of the precipitation in midlatitudes, and the clouds

associated with them comprise a rich mixture of convective, layered, and stratiform cloud structures, which

have important effects on the energy and water balances

in midlatitudes. Synoptic storms in midlatitudes are responsible for extreme modifications of the planetary

boundary layer and intense interactions with the ocean,

which are being studied with scatterometer data.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 221

Use of Satellite Data

Models of the boundary layer are being combined with

information from satellites such as ERS-1&2, SSM/I microwave measurements, global weather analyses, and in

situ measurements to estimate surface fluxes and to understand their relationship to atmospheric and oceanic

phenomena. Information about surface wind speed from

SeaWinds, combined with temperature and humidity data

from AIRS/AMSU/HSB and AMSR-E will enable muchimproved understanding and better estimates of surface

fluxes to be gained from EOS satellites. High temporal

and spatial resolution information on convective cloud

systems and upper-tropospheric water vapor from GOES,

GMS, and Meteosat are being used extensively. Moredetailed global data on cloud abundance, structure, and

optical properties can be derived from instruments such

as MODIS, CERES, and MISR within EOS. Improved

data on the abundance of tropospheric aerosols that may

affect the radiation balance and influence cloud properties will be provided by EOSP and MISR, also on EOS.

MLS and GLAS will provide unique information on upper-tropospheric water vapor and thin cirrus cloud decks,

respectively.

Participation in Field Programs

The investigators are involved in a number of field programs that are closely related to the goals of this investigation, such as TOGA/COARE, Atlantic Stratocumulus

Transition Experiment (ASTEX), TRMM surface validation, NSCAT ADEOS, QuikSCAT and SeaWinds validation and Pan American Climate Studies (PACS).

Principal Investigator

Dennis L. Hartmann

Professor Hartmann received his Ph.D. in Geophysical

Fluid Dynamics from Princeton University in 1975. He

joined the faculty of the Department of Atmospheric Sciences at the University of Washington in 1977, and has

been an adjunct faculty member of the Quaternary Research Center since 1978. His main research interests are

in stratospheric ozone, global climate, large-scale dynamics, and the radiative energy balance of Earth. He has published over 80 research papers on these topics and has

authored a textbook about global climate. Hartmann

served as a Principal Investigator in the Earth Radiation

Budget Experiment (ERBE) and the Airborne Antarctic

Ozone Experiment (AAOE), for which he received NASA

Group Achievement Awards. He is a Fellow of the American Meteorological Society and the American Association for the Advancement of Science and serves on numerous national and international service and advisory

bodies.

Co-Investigators

Christopher S. Bretherton - University of Washington

Robert A. Brown - University of Washington

Robert A. Houze, Jr. - University of Washington

Kristina Katsaros - NOAA

Conway B. Leovy - University of Washington

References

Chen, S.S., and R.A. Houze, Jr., 1997: Diurnal variation

and lifecycle of deep convective systems over the tropical Pacific warm pool. Quart. J. Roy. Meteor. Soc., 123

357-388.

Dickinson, S., and R.A. Brown, 1996: A study of nearsurface winds in marine cyclones using multiple satellite

sensors. J. Appl. Meteor., 35, 769-781.

Klein, S.A., D.L. Hartmann, and J.R. Norris, 1995: On

the relationships among low cloud structure, sea surface

temperature and atmospheric circulation in the northeast

Pacific. J. Climate, 8, 1140-1155.

Miletta, J., and K.B. Katsaros, 1995: Using coincident

multispectral satellite data to assess the accuracy of SSMI

liquid water path measurements. J. Geophys. Res., 100,

16,333-16,339

Norris, J., and C. Leovy, 1994: Interannual variability in

stratiform cloudiness and sea surface temperature. J. Climate, 7, 1917-1925.

Salathé, E.P., and D.L. Hartmann, 1997: A trajectory

analysis of tropical upper-tropospheric moisture and convection. J. Climate, 10, 2533-2547.

Su, H., S.S. Chen, and C.S. Bretherton, 1999: Three-dimensional week-long simulations of TOGA COARE convective systems using the MM5 mesoscale model. J.

Atmos. Sci., in press.

Investigation URL

http://eos.atmos.washington.edu
222 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Evaluation of Marine Productivity in the

Tropical Pacific and Atlantic Oceans Using

Satellite Ocean Color and Numerical Models

Principal Investigator – Eileen Hofmann

Science Background

The tropical ocean plays a major role in global-scale physical (oceanographic and meteorological) and biological

processes. Variability in the equatorial ocean is dominated

on interannual time scales in the Pacific and on seasonal

time scales in the Atlantic. However, because of the difficulty in making routine measurements in the great expanses of the tropical ocean, spatial and temporal variability in these regions is difficult to monitor and monitoring is possible only by using extensive mooring arrays

and satellites. Several programs have occurred and are

ongoing to obtain physical data measurements in the tropical oceans. However, similar programs designed to collect biological data are not scheduled in the near future

and thus the primary source of new biological information for these regions will be ocean color sensors, such as

SeaWiFS and MODIS. Analyses and understanding of

these data require inclusion of information from the physical and biological environments. Data-assimilative numerical models that include circulation, ecosystem, and

optical components offer one approach for doing this.

Science Goals

Our research program focuses on four general topics of

investigation in the tropical Pacific and Atlantic Oceans:

1) Interactions between physical and biological processes;

2) Evaluations of primary, new, and export production;

3) Diagnostic and predictive coupled physical-biological models; and

4) Data-assimilation techniques for model prediction skill

and ecosystem parameter estimation.

The first two objectives will be addressed through analysis of ocean-color data. The latter two will be addressed

through numerical modeling.

Specific research objectives are related to quantifying the contribution of high-frequency physical events to

nutrient, iron, and carbon fluxes in the equatorial Pacific,

understanding variability in the western, central, and eastern Pacific Ocean and ecosystem that occurs in response

to El Niño conditions, and determining the correspondence

between satellite- and model-derived estimates of primary

production in the tropical oceans.

Current Activities

A part of our current effort is directed at developing the

data-analysis tools that will provide the ocean-color and

other fields needed for the models. Concurrently, we are

developing circulation and ecosystem models that can be

used to understand processes affecting ocean-color distributions in the Tropical Pacific Ocean. Much progress

has been made on the development of a coupled mixedlayer and bio-optical model, and a model of the lower

trophic levels (nutrients, phytoplankton, and zooplankton). The ecosystem model includes dependencies of phytoplankton growth on light, temperature, and iron availability. A separate modeling effort is focused on understanding the role of Trichodesium spp. in nutrient fluxes

in tropical Pacific waters. These models will eventually

be embedded in a three-dimensional circulation model

for the Tropical Pacific Ocean.

Participation in Field Activities

This study will make considerable use of ocean-color

measurements from the SeaWiFS sensor. These data will

be processed using SeaDAS (Fu et al., 1996) to reveal

trends in the distributions and to determine correlations

with other geophysical data such as sea-surface temperature. The goal of this portion of our research is to provide

ocean-color distributions that can be used for initialization, calibration, and verification of data-assimilative ecosystem models.

Other satellite-derived data sets, such as sea-surface

temperature (from AVHRR) and surface wind and height

fields (from TOPEX and SeaWinds) will be used with the

circulation models in a data-assimilative mode. These data

will be combined with a variety of in situ oceanographic

and meteorological measurements.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 223

Use of Satellite Data

Our project is focused on data analysis and modeling activities, and, consequently, there is no explicit field program associated with our study. However, we make extensive use of field measurements, especially those obtained from the TOGA/TAO mooring array and those from

the U.S. JGOFS Equatorial Pacific (EqPac) study.

Principal Investigator

Eileen Hofman

Eileen Hofmann received her Ph.D. in Marine Sciences

and Engineering from North Carolina State University,

after which she spent time at Florida State University and

Texas A&M University and then moved to Old Dominion University in 1989, where she is presently a Professor of Oceanography. Her research interests are in the areas of descriptive physical oceanography and mathematical modeling of physical-biological interactions in marine food webs. She is presently a member of the U.S.

and International Science Steering Committees for the

Global Ocean Ecosystem Dynamics (GLOBEC) Program,

and is Chair of the GLOBEC Southern Ocean Planning

Group.

Co-Investigators

Ichio Asanuma -

Robert A. Brown - University of Washington

Antonio Busalacchi - NASA/Goddard Space Flight Center

Chester Koblinsky - NASA/Goddard Space Flight Center

Marlon Lewis - Dalhousie University

Charles R. McClain - NASA/Goddard Space Flight Center

Michael McPhaden -

Ragu Murtugudde - University of Maryland

References

Fu G., B.D. Scheiber, K.J. Settle, M. Darzi, C.R. McClain,

and K.R. Arrigo, 1996: SeaDAS: A processing package

for ocean color satellite imagery. Proc. Twelfth Int. Conf.

on Interactive Inform. and Processing Systems for

Meteorol. Oceanogr. and Hydrol., Am. Meteorolog. Soc.,

451-456.
224 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Characterizing Aerosol Forcing Over the

Atlantic Basin

Principal Investigator – Brent Holben

Science Background

A major scientific activity of the aerosol community is to

develop an improved understanding of the local and regional climatic impact of aerosol. Aerosol particles are

believed to be the major cause for observations of a smaller

than expected warming of the Earth-atmosphere-system

due to greenhouse-gas increases. The impact of aerosol

on the energy balance (and radiative transfer processes)

in the Earth’s atmosphere is expressed by a forcing, which

captures the difference between aerosol-included and aerosol-free scenarios. The uncertainty of this forcing for (not

just anthropogenic) aerosol is considerable. Many individual efforts to investigate aerosol properties and/or their

impact on radiative-transfer processes have been pursued,

yet a coordinated effort to link individual contributions

into a common picture has been missing for historic as

well as follow-on measurement systems. Such coordination for improved predictions of aerosol radiative forcing

is our major objective.

Science Goals

The main objective of the proposed research is to characterize the local and regional radiative forcing from industrial/urban aerosol (mainly sulfates), Saharan dust, and

aerosol from biomass burning transported over extensive

regions of the Atlantic basin from the nearby continents.

This objective will be achieved by a synergism between

several tools: a comprehensive database of aerosol spectral optical thickness and size distribution derived from

ongoing ground-based in situ and remote-sensing aerosol measurements currently operational in the Atlantic and

adjacent continents; satellite data; transport models; and

GCM models. By using these tools to characterize the

aerosol physical and chemical characteristics, we plan to

develop a climatology of the aerosol dynamic properties

for these aerosol types, to test approaches for characterization of aerosols and their radiative forcing from satellites on present platforms and on future EOS platforms,

and to develop and verify models for the aerosol evolution and transport and the effect of aerosols on climate.

Current Activities

To characterize the global aerosol variability in terms of

concentration and properties and estimate its impact on

climate, an integrated approach is applied, which includes

accurate spectral satellite data, detailed ground-based remote-sensing and in situ measurements, and an application of the current knowledge in global circulation and

regional transport models including aerosol chemistry. Our

initial work focuses on the Atlantic rim regions, where

repeated short-term field experiments geared towards particular aerosol types and long-term monitoring of aerosol

chemistry and aerosol-related sunlight attenuation from

individual ground locations provide a database of aerosol

ground observations. After careful intercomparisons of

redundant measurements these data are used to update

aerosol databases, to validate satellite-based aerosol products (which are used for global monitoring), to validate

(chemical) transport model results (initialized by aerosol

sources), and to simulate the associated aerosol forcing

(including impacts from uncertainties due to models, aerosol properties, surface reflectance, and the presence of

clouds).

Use of Satellite Data

This investigation will incorporate a number of data products from EOS instruments and other satellites to moreprecisely characterize aerosol source strengths for modeling radiative forcing, the temporal and spatial extent of

aerosol optical properties, and evaluating the model output. This effort will build on the long-term record from

existing systems such as TOMS, AVHRR, GOES, and

METEOSAT, and provide an interface with new moreaccurate aerosol data products from SeaWiFS, MODIS,

MISR, and CERES.

Participation in Field Programs

The IDS team has heavily participated in ACE-2,

TARFOX, SCAR-B, and BOREAS, as well as smaller

campaigns relating to aerosol and cloud optical properties. Because of the great diversity of aerosol types, distributions, and short lifetimes, team members anticipate

extensive field programs in regions of biomass burning

(SAFARI-2000, LBA-CLAIRE), Desert Dust (ACE-3),
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 225

and urban marine mixtures (INDOEX) to name a few.

This research by a highly interdisciplinary team with expertise in ground and satellite observations, and modeling provides a unique opportunity to combine data measurements from diverse sources with global-modeling resources.

Principal Investigator

Brent N. Holben

Brent Holben (M.S. Watershed Sciences, Colorado State

University 1975 ) has worked at NASA’s GSFC for 20

years performing research in both ground-based and satellite remote sensing of vegetation and aerosols. He is the

project leader for the AERONET sun-sky radiometer network that is providing aerosol optical properties for a variety of globally distributed aerosol regimes.

Co-Investigators

Olivier Boucher - Laboratoire de Meteorologie

Dynamique

G. J. Collatz - NASA/Goddard Space Flight Center

Jay Herman - NASA/Goddard Space Flight Center

Thomas Eck - Raytheon ITSS Corporation

Rich Ferrare - NASA/Langley Research Center

Elaine Prins - CIMSS, Univ. of Wisconsin-Madison

Joseph M. Prospero - CIMAS, University of Miami,

RSMAS

Hank Margolis - CRBF Abitbi-Price

Stephen E. Schwartz - ECD, Brookhaven National

Laboratory

Geary K. Schwemmer - NASA/Goddard Space Flight

Center

Darold Ward - U.S. Department of Agriculture

References

Boucher, O., S.E. Schwartz, T.P. Ackerman, T.L. Anderson, B. Bergstrom, B. Bonnel, P. Chylek, A. Dahlback, Y.

Fouquart, Q. Fu, T. Iversen, M.J. Hayward, S. Kato, S.

Kinne, A. Kirkevag, K.R. Knapp, A. Lacis, I. Laszlo, S.

Nemesure, V. Ramaswamy, D.L. Roberts, P. Russell, M.E.

Sclesinger, G.L. Stephens, R. Wagener, M. Wang, J. Fong,

and F. Yang, 1998: Intercomparisons of models representing shortwave radiative forcing by sulfate aerosols. J.

Geophys. Res., in print.

S. Kinne, R. Bergstrom, O.B. Toon, E. Dutton, and

M.Shiobara, 1998: Clear sky atmospheric solar transmission: an analysis based on FIRE 1991 field experiment

data. J. Geophys. Res., in print.

Investigation URL

http://spamer.gsfc.nasa.gov

Regarding the plot I am suggesting

to contribute with a plot which compares the monthly averaged direct

(local) forcing for biomass burning

aerosol—based on multiyear

AERONET statistics—for South

American, African and Canadian

sites.
226 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Assessing the Impact of Expanding Urban

Land Use on Agricultural Productivity Using

Remote Sensing Data and Physically Based

Soil Productivity Models

Principal Investigator – Marc Lee Imhoff

Science Background

This project is intended to develop the tools and models

for mapping the extent of urbanization and to assess the

impact of this process on the Earth’s biosphere and for

making recommendations concerning the future food security of the human race. As more land is converted to

urban uses, the question arises as to whether or not this

represents a systematic reduction in our ability to produce food by placing our infrastructure on the most productive soil resources. Given present demographic trends,

it is important that these land-use issues be resolved, as a

rapidly growing number of regional populations are at

risk with respect to socio-political and economic instabilities and their consequent effects on the food supply.

Currently, both the magnitude and the potential effects of

urban land transformation are hotly debated due to difficulties in making accurate measurements of the area of

urban land use and assessing the impact of these changes

on agricultural land area or production. The project will

use satellite data from various sources to map the extent

and location of human habitation. Natural resource, census, and agronomic data will be acquired, digitized, and

co-registered to the satellite data in a geographic information system (GIS) for analysis and model development.

Science Goal

The goal of this investigation is to first understand and

then predict the effect of urban land transformation on

the Earth’s primary productivity and translate that understanding into meaningful applications in global climatechange and food-security studies. We will seek to improve

our understanding of the Earth’s soils as a supporting

matrix for photosynthesis and agricultural production at

regional and global scales. We will develop techniques

for determining the full extent of urbanization and relate

the urban land transformation process to demographic

data. Finally, we will improve our knowledge of how urbanization affects soil resources by calculating the impacts directly as a function of the transformed area of fertility-rated soils.

Current Activities

Within the context of global food security, this group has

determined three key regions of focus: The United States

and Mexico, Egypt and the Middle-East, and China. These

focus areas were selected for their significance in terms

of agricultural production, population, and strategic importance. Satellite data, soils maps, and demographic data

for these regions are being collected and local investigators for the international components are being contacted.

In order to develop the methodologies for mapping human habitation and making the impact assessment, this

group has conducted a test in the United States using nighttime satellite-image data from the Department of Defense,

digital soils maps from the United Nations Food and Agriculture Organization, and U.S. Census data. A preliminary assessment was made evaluating the urban mapping

methods and the amount and quality of soils being urbanized in the US.

Use of Satellite Data

The project will make use of a wide variety of EOS and

non-EOS satellite data. The primary satellite data set will

be the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS), which acquires

visible and NIR images of the Earth at night. DMSP/OLS

detects urban areas and other sites of significant human

activity by their lights. The accuracy of these data for urban mapping will be enhanced and evaluated using

Landsat ETM+ and MODIS data. Land-cover, climate,

and other satellite-derived data sets from other EOS investigators will also be used to help develop the soil-fertility rating system.

Participation in Field Programs

This team will participate in field data programs, but in a

way not usually seen in past EOS investigations. Our primary focus will be on urban and peri-urban areas and the

assessment and evaluation of the nature of the transformation of the soil. We will concentrate on soil physical
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 227

properties of both transformed and non-urbanized soils

and their surface area in order to gauge the impact of the

transformation.

Principal Investigator

Marc L. Imhoff

Marc Imhoff is a graduate of the Pennsylvania State University, received a Ph.D. from Stanford University, and is

currently based at NASA’s Goddard Space Flight Center,

Biospheric Sciences Branch. He has been extensively involved in international remote sensing and science projects

serving as a principal investigator on studies designed to

map monsoon flooding and forest biomass in Bangladesh

and wildlife habitats in Australia using a variety of remotely sensed imagery.

Co-Investigators

Christopher Elvidge - NOAA/NGDC

William T. Lawrence - Bowie State University

Gary W. Petersen - The Pennsylvania State University

Sharon Waltman - National Soil Survey Center, USDA/

NRCS

References

M.L. Imhoff, W.T. Lawrence, C.D. Elvidge, T. Paul, E.

Levine, M.V. Privalsky, and V. Brown, 1997: Using nighttime DMSP/OLS images of city lights to estimate the

impact of urban land use on soil resources in the U.S.

Remote Sens. Environ., 59, 105-117.

M.L. Imhoff, W.T. Lawrence, D.C. Stutzer, and C.D.

Elvidge, 1997: A technique for using composite DMSP/

OLS “City Lights” satellite data to accurately map urban

areas. Remote Sens. Environ., 61, 361-370.

Investigation URL

http://jhampa.gsfc.nasa.gov/index.html

Shown above is a satellite-derived “city lights” map of urbanized area for the United States being overlain on the United Nations Food and

Agriculture Organization’s Digital Soils Map. The urban map was generated directly from DMSP/OLS imagery using a technique, developed

by this project, called Spatial Integrity Thresholding of Urban Polygons (SITUPS). The thresholding technique created an urban map which

compared very well with U.S. Census estimates of urbanized area in the U.S. The soils data are rated according to the number of physical

factors present in the soil that limit agricultural production. Results of this work showed, undeniably, that many of our best agricultural soils

are being lost to urbanization.
228 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Soil Moisture Mapping at Satellite Temporal

and Spatial Scales

Principal Investigator – Thomas J. Jackson

Science Background

There has been a significant growth in the recognition of

the importance of soil-moisture information in large scale

hydrology and climate modeling. Recent publications

have made the analogy that soil moisture may have the

same role in land hydrology that sea-surface temperature

(i.e., El Niño) plays in climate, providing a seasonal

memory for the system. There is a need to reevaluate the

role that the Earth Science Enterprise (ESE) can play in

providing measurements of soil moisture. There are potential satellite observing systems that could be implemented. However, there are still some important questions that need to be answered. Unfortunately, there are

only sparse soil-moisture data sets that could in any way

represent the types of observations that a satellite observing system might provide. The limited data available, such

as Washita’92 (http://hydrolab.arsusda.gov/washita92/

wash92.htm), have produced remarkable results and insights.

Science Goals

This investigation addresses remote sensing and the scales

of temporal and spatial observation of surface soil moisture. Specific objectives are: 1) establish that higher resolution soil-moisture brightness-temperature algorithms developed using truck and aircraft sensors can be extended

to the coarser resolutions expected from satellite platforms, 2) examine the spatial and temporal dynamics of

surface soil moisture at an order of magnitude greater than

previous investigations, and 3) develop a database for soilmoisture hydrology and land-atmosphere-interaction investigations. The results of this research are expected to

establish the validity of current soil-moisture estimation

algorithms at spatial scales typical of projected satellite

systems, provide insights for the design of an observing

system with regard to temporal features, explore the integration of ground-based and remote observing systems,

and provide a unique data set to the large-scale hydrology and climate-modeling research community.

Current Activities

The core of this investigation is a large-scale aircraft soilmoisture mapping experiment, the Southern Great Plains

1997 (SGP97) Hydrology Experiment, conducted over a

one-month period in the summer of 1997. Surface soil

moisture was mapped over an area of ~10,000 km2 (an

order of magnitude larger than previously observed) of

Oklahoma at a spatial resolution compatible with known

data-interpretation algorithms (~1 km). The resulting database will allow the scaling up to projected satellite-sized

footprints (~10 km) and cover an area large enough to

provide nearly 100 of these satellite-sized pixels. These

data will allow the examination of the information content of coarse-resolution data as well as the analysis of

the spatial distribution over climate/atmospheric model

scales. Convective fronts and local feedbacks may be observable at these scales.

Data were collected using an L band passive microwave mapping instrument called ESTAR, which was

flown on a NASA P-3 aircraft. In addition to the L band

system, other ground, aircraft, and satellite measurements

were obtained concurrently. This comprehensive database

is currently being assembled and will be a valuable contribution to a broad range of science investigations, including other ESE studies. The L band ESTAR data processing is complete and soil-moisture maps have been

developed. Distinct spatial structure is quite apparent in

the results. Some of this is a function of rainfall events,

and some is related to soil and vegetation features.

Use of Satellite Data

Soil-moisture sensing requires long-wavelength microwave sensors. Within the current EOS program the longest wavelength sensor is the C band instrument that will

be part of the Advanced Microwave Scanning Radiometer (AMSR-E). A similar instrument will be part of the

Japanese ADEOS-II. Current research utilizes a wide variety of satellite data. Microwave sensors on the Russian

MIR platform were used in the 1997 experiments. All

existing radar satellites (Radarsat, JERS, and ERS) acquired data as part of SGP97 and data are being analyzed.

SSM/I, Landsat, and NOAA AVHRR data are also important components of the research. In the next phase of

research, data from the TRMM Microwave Imager will

be utilized.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 229

Participation in Field Programs

As noted, a major focus of this project revolves around

field projects. The Southern Great Plains 1997 (SGP97)

Hydrology Experiment provided a focal point for a number of collaborative EOS ESE investigations. Motivated

by wide-spread interest among hydrologists, meteorologists, soil scientists, and ecologists, in the problems of

estimating soil moisture at the continental scale and coupling between land surface and atmosphere the original

soil-moisture experiment was broadened significantly.

SGP97 was successfully completed and data analyses are

currently underway. This work will provide a foundation

for future satellite sensors and calibration/validation programs for soil moisture algorithms. A field program has

been initiated to develop and calibrate soil-moisture algorithms for the AMSR instruments that will be part of

the EOS-PM and ADEOS-II satellites. This effort will

start in the summer of 1999 and continue through the

launch of the instruments.

Principal Investigator

Thomas J. Jackson

Thomas J. Jackson obtained a Ph.D. in Civil Engineering

from the University of Maryland in 1976. He has been a

hydrologist with the USDA Agricultural Research Service Hydrology Lab since 1977. His research involves

the application and development of remote-sensing technology in hydrology and agriculture. He has conducted

research on the use of visible/near-infrared satellite data

for deriving land-cover parameters used in hydrologic

models and the use of an airborne laser profiler for measuring and monitoring soil erosion. The results of the laser-profiling research led to a paper titled “Airborne Laser Measurements of the Surface Topography of Simulated Concentrated Flow Gullies,” (1990) that received

the “paper of the year” award by the American Society of

Agricultural Engineers. His current research focuses on

the use of passive-microwave techniques in hydrology. A

recent paper titled “Diurnal observations of surface soil

moisture using passive microwave radiometers” was selected as the prize paper at the International Geoscience

and Remote Sensing Symposium for 1994. He is also a

member of the Japanese AMSR Science Team. He is a

member of AGU and IEEE and currently serves on the

Administrative Committee of The Geosciences and Remote Sensing Society.

Co-Investigators

Calvin T. Swift - University of Massachusetts

David M. Levine - NASA/Goddard Space Flight Center

Patrick J. Starks - USDA Agricultural Research Service

Peggy E. O’Neill - NASA/Goddard Space Flight Center

References

Jackson, T.J., 1993: Measuring surface soil moisture using passive microwave remote sensing. Hydrological Processes, 7, 139-152.

Jackson, T.J., D.M. Le Vine, C.T. Swift, T.J. Schmugge,

and F.R. Schiebe, 1995: Large area mapping of soil moisture using the ESTAR passive microwave radiometer in

Washita’92. Remote Sens. of Environ., 53, 27-37.

Jackson, T.J., 1997: Soil moisture estimation using SSM/

I satellite data over grassland region. Water Resources

Res., 33, 1475-1484.

Jackson, T.J., P.E. O’Neill, and C.T. Swift, 1997: Passive

microwave observation of diurnal surface soil moisture.

IEEE Trans. Geosci. Remote Sens., 35, 1210-1222.

Investigation URLs

(Project) http://hydrolab.arsusda.gov/sgp97/

(Data) http://daac.gsfc.nasa.gov/

CAMPAIGN_DOCS/SGP97/sgp97.html

Related URLs

(Washita’92 Hydrology Experiment)

http://hydrolab.arsusda.gov/washita92/wash92.htm

(ADEOS-II AMSR)

http://www.eorc.nasda.go.jp/ADEOS-II/AMSR/

amsr.html

(Microwave Remote Sensing-U of Mass.)

http://www.ecs.umass.edu/ece/labs/mirsl.html
230 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Investigation of the Coupling Between

Tropospheric Ozone, Sulfate Aerosols, and

Climate Using a General Circulation Model

Principal Investigator – Daniel J. Jacob

Science Background

The radiative forcings associated with anthropogenic perturbations to tropospheric ozone and sulfate aerosols could

have important climatic effects. Ozone and sulfate are produced in the troposphere by chemical reactions involving

precursors emitted by both anthropogenic and natural

sources. They have relatively short atmospheric lifetimes

and hence inhomogeneous atmospheric distributions. Estimates of the global mean radiative forcing at the tropopause due to changes in tropospheric ozone from pre-industrial times to today range from 0.2 to 0.6 W m-2, as

compared to 1.6 W m-2 for CO2. For sulfate aerosols, the

forcing is estimated to range from -0.3 to -3.0 W m-2. The

actual forcings from tropospheric ozone and aerosols are

regionally variable, and can be greatly affected by correlations with meteorological variables (e.g., humidity, cloud

cover, temperature), adding considerable complexity to

an assessment of climatic impact. The concentrations and

distributions of ozone and sulfate are also sensitive to

changes in climate, resulting in intricate feedbacks. Relating the emissions of ozone and sulfate precursors to

their ultimate climatic effects requires a global climate

model that includes coupled, consistent, and realistic representations of ozone and sulfate aerosols.

Science Goal

Our work is motivated by five central questions:

1) What are the climatic effects of changes in the emissions of tropospheric ozone precursors?

2) How does tropospheric ozone respond to climate

change and what are the feedbacks on climate?

3) What are the climatic effects of changes in the emissions of sulfate precursors?

4) How do sulfate aerosols respond to climate change,

and what are the feedbacks on climate?

5) What are the couplings between the climatic effects

of tropospheric ozone and sulfate aerosols?

Our approach to these questions is to incorporate processbased simulations of tropospheric ozone and sulfate aerosols into a new generation NASA/GISS general circulation model (GCM 2 ́) and into a chemical tracer model

(CTM) driven by assimilated meteorological data from

the Goddard Earth Observing System Data Assimilation

System (GEOS-DAS). The same modules for emissions,

chemistry, deposition, and aerosol processes are implemented in the GISS GCM and in the GEOS CTM. We

use the GCM to study the radiative and climatic effects

of changes in tropospheric ozone and sulfate aerosols from

pre-industrial times to today and into the future. At the

same time, we use the GCM and the GEOS CTM to improve our understanding of the processes controlling tropospheric ozone and sulfate through detailed comparisons of model results with observations. Simulations with

the GEOS CTM focus on specific field programs, affording better constraints for model evaluation.

Current Activities

We have incorporated on-line simulations of tropospheric

ozone chemistry and sulfate aerosols into the GISS GCM

2, and conducted extensive evaluations of model results

with climatological observations. We have used these

simulations to calculate radiative forcings from ozone and

sulfate aerosols over the past century, focusing on the factors that drive the heterogeneity in the forcings. We have

compared on-line and off-line calculations of the radiative forcings and interpreted the differences between the

two in terms of synoptic-scale correlations of ozone and

aerosols with clouds. We have implemented on-line simulations of ammonia and sulfate-nitrate-ammonium-water

thermodynamics in the GCM and evaluated results with

observations; this simulation has allowed us to obtain a

better understanding of the composition and water content of aerosols in different regions of the troposphere,

and of the radiative implications. Publications on all these

studies are available through our web site.

Our current work involves further development and

application of our capability for coupled chemistry-aerosol-climate GCM simulations. Specific tasks for the year

ahead include: 1) addition of aerosol types other than sulfate, and resolution of the aerosol size distribution; 2) in-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 231

vestigation of the indirect radiative effect driven by aerosol influence on cloud microphysics; 3) merging of the

ozone and sulfate-nitrate-ammonium simulations for study

of chemistry-aerosol coupling; 4) investigation of climate

forcing due to changes in tropospheric ozone from

preindustrial to present; 5) investigation of ozone chemistry in preindustrial and future atmospheres; and 6) development of an on-line tropospheric chemistry simulation capability in the high-resolution (23-layer) version

of the GISS GCM 2 ́.

In parallel to our GCM work, we have also developed capabilities for simulation of tropospheric ozone and

sulfate aerosol in the GEOS CTM driven by assimilated

meteorological observations. The sulfate model has been

applied to simulations of the ACE-1, PEM-West A and B,

and PEM-Tropics A aircraft campaigns. Results from these

simulations have led to improved modeling of the corresponding processes in the GISS GCM, notably the oceanic emission of sulfur. The ozone model is presently

being applied to a simulation of the PEM-West B campaign.

Our investigation interacts closely with space-based

observations, both in terms of using the observations to

test our models and in terms of using our model analyses

to guide the design of the next generation of satellite measurements. We plan to make particular use of SAGE III

for upper tropospheric and lower stratospheric ozone,

MOPITT for CO, and the CHEM instrument ensemble

for ozone and related species. In addition we plan to examine ERBE, CERES, and AIRS observations of radiation at the top of the atmosphere for ozone and aerosol

effects.

Use of Satellite Data

Detailed evaluation with observations will be essential

for assessing the capabilities of our chemistry-aerosolclimate models. Space-based data to be used for this purpose include SAGE III for upper tropospheric ozone;

TOMS and SAGE III for tropospheric ozone residuals;

and MAPS and MOPITT for CO. In addition, ERBE and

CERES satellite observations of radiation at the top of

the atmosphere will be examined for ozone and aerosol

effects.

Participation in Field Activities

We have applied our ozone and sulfate models based on

the GEOS CTM to simulation of the ACE-1, PEM-West

A and B, and PEM-Tropics A aircraft campaigns. We plan

over the next few years to apply these models to simulation of the SONEX aircraft campaign over the North Atlantic and the PEM-Tropics B aircraft campaign over the

South Pacific. These campaigns include concurrent measurements of a large suite of chemical species over a large

spatial domain and are thus particularly well-suited for

testing a global model driven by assimilated meteorological observations. Results from these simulations will be

used on an ongoing basis to improve the descriptions of

ozone and sulfur chemistry in the GISS GCM.

Principal Investigator

Daniel J. Jacob

Daniel J. Jacob is the Gordon McKay Professor of Atmospheric Chemistry and Environmental Engineering at

Harvard University. He holds degrees in Chemical and

Environmental Engineering (Ph.D., California Institute

of Technology, 1985). His research focuses on improving

knowledge of the chemistry of the troposphere and addresses problems ranging from urban air pollution to global environmental change. He contributes to several EOS

committees and has chaired two recent NASA workshops

on atmospheric chemistry measurements from space. He

is Mission Scientist of the Pacific Exploratory MissionTropics aircraft campaigns and is a recipient of the AGU

Macelwane Medal (1994).

Co-Investigators

Mian Chin - NASA/Goddard Space Flight Center

Dorothy M. Koch - NASA/Goddard Institute of Space

Studies

Jennifer A. Logan - Harvard University

Michael J. Prather - University of California at Irvine

David Rind - NASA/Goddard Institute of Space Studies

John H. Seinfeld - California Institute of Technology

Anne M. Thompson - NASA/Goddard Space Flight Center

References

Adams, P.J., J.H. Seinfeld, and D.M. Koch: Global composition of tropospheric sulfate aerosol simulated in a general circulation model. J. Geophys. Res., submitted.

Chin, M., R.B. Rood, D.J. Allen, M.O. Andreae, A. M.

Thompson, S.A. Yvon-Lewis, R.R. Atlas, and J.V.

Ardizzone, 1998: Processes controlling dimethyl sulfide

over the ocean: Case studies using a 3-D model driven by

assimilated meteorological fields. J. Geophys. Res., 103,

8341-8353.

Koch, D.M., D. Jacob, I. Tegen, D. Rind, and M. Chin:

Tropospheric sulfur simulation and sulfate direct radiative forcing in the GISS GCM. J. Geophys. Res., submitted.
232 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Rind, D., J. Lerner, K. Shah, and R. Suozzo, 1999: Use of

on-line tracers as a diagnostic tool in general circulation

model development, 2. Transport between the troposphere

and stratosphere. J. Geophys. Res., in press.

Tegen, I., P. Hollrigl, M. Chin, I. Fung, D. Jacob, and J.

Penner, 1997: Contribution of different aerosol species to

the global aerosol extinction optical thickness: estimates

from model results. J. Geophys. Res., 102, 23,895-23,915.

Wang, Y., and D.J. Jacob, 1998: Anthropogenic forcing

on tropospheric ozone and OH since preindustrial times.

J. Geophys. Res., 103, 31,123-31,135.

Wang, Y., D.J. Jacob, and J.A. Logan, 1998: Global simulation of tropospheric ozone-NOx-hydrocarbon chemistry, 3. Origin of tropospheric ozone and effects of nonmethane hydrocarbons. J. Geophys. Res., 103, 10,757-

10,768.

Investigation URL

http://www-as.harvard.edu/chemistry/trop/ids.html
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 233

A Study of Carbon Monoxide Using Trace

Constituent Data Assimilation: A New

Approach in Global Tropospheric Chemistry

Analysis

Principal Investigator – Prasad Kasibhatla

Science Background

The global biogeochemical cycles of a number of trace

gases depend critically on their chemical processing in

the troposphere. In this context, the hydroxyl radical (OH)

is the key species in determining the chemical processing

potential of the troposphere. The tropospheric OH concentration depends non-linearly on the local concentrations of CO, nonmethane hydrocarbons, and nitrogen

oxides. The tropospheric distribution of these compounds

in turn is quite variable owing to the heterogeneous spatial and temporal distribution of their sources, as well as

due to their relatively short lifetime (days to months) in

the troposphere.

In this investigation we focus on CO, which is the

largest sink of OH in the troposphere. In recent years,

infrared absorption measurements from space have offered the promise of providing a global picture of the CO

distribution (Reichle et al. 1986; Reichle et al. 1990) and

of shedding light on the various processes that shape this

distribution (Newell et al. 1988; Connors et al. 1989;

Watson et al. 1990). More recently, a sophisticated threedimensional chemical transport model driven using assimilated meteorological fields for specific time periods

has been used to analyze certain aspects of the global CO

distribution (Allen et al. 1996). However, there has been

no attempt to combine model results with CO measurements in a systematic manner.

This investigation is directed towards developing and

applying trace-constituent data-assimilation techniques to

systematically analyze space-based, airborne, and groundbased tropospheric CO measurements. Specifically, we

will develop and apply an improved version of the NASA

GSFC/DAO CO chemical transport model (CTM, Allen

et al. 1996) in this investigation. In addition to being directly applicable to analyzing CO measurements from the

MOPITT instrument, it is anticipated that the techniques

developed as part of this project will be also be useful for

interpreting future measurements of other tropospheric

species from the TES instrument.

Science Goals

The scientific goals of this investigation are to: 1) develop methodologies to synthesize results from numerical chemical transport models with in situ and remote

trace-gas measurements; 2) develop a comprehensive picture of the spatial CO distribution and temporal variability in the troposphere; and 3) elucidate the factors that are

responsible for shaping the tropospheric CO distribution.

Current Activities

Major modifications have been made to the NASA GSFC/

DAO CO chemical transport model to incorporate interactive CO-OH chemistry. This represents a significant

advance over the original formulation, in which prescribed

OH fields were used and no feedback was allowed between modeled CO and OH fields. The modifications involved incorporating a parameterized tropospheric OH

calculation scheme into the CTM. In addition, other data

sets required for the parameterized chemical calculations

were acquired and processed for use in the CTM. These

include global distributions of nitrogen oxides, ozone,

water vapor, and total-column ozone, global climatologies

of low-, middle-, and high-level cloud frequencies, and

global albedo and land/ocean data.

The fossil-fuel combustion emission inventory for

CO was updated based on an up-to-date emission inventory. In this inventory, CO emission rates are calculated

using an energy database from the United Nations that

gives consumption statistics for the end use of each fuel

in 32 categories, along with emission factors for particular processes derived from EPA reports and the European

CONAIR inventory. CO production from the oxidation

of anthropogenic hydrocarbons, which was neglected in

the original formulation of the model, is included by scaling the fossil-fuel CO source by a factor of 1.2. In addition, CO emissions from the burning of wood fuel and an

up-to-date inventory of biomass-burning CO emissions

will soon be incorporated into the CTM.

In parallel with the model development activities, the

compilation of a comprehensive global observational

dataset for CO has also been initiated. Preliminary data
234 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

files for sites in the Climate Monitoring and Diagnostics

Laboratory (CMDL) cooperative air-sampling network

and the in situ measurements from Pt. Barrow, AK, and

Mauna Loa, HI, have been prepared. In particular,

monthly-mean mixing ratios for 1994 at these surface sites

have been compiled. In addition, preliminary data files of

surface and airborne correlative CO measurements made

during the April and October 1994 MAPS missions have

been prepared. An important feature of these observation

data sets is that all measurements are referenced to the

NOAA/CMDL CO reference scale. We have also acquired

the April and October 1994 MAPS CO measurement data

files.

The CO distribution during the 1993-1994 time period has been simulated using the updated model. Results

of these calculations have been compared to monthly mean

CO measurements at the NOAA/CMDL surface sites.

With a few exceptions, the updated model appears to capture the spatial and seasonal distribution of CO during

1994.

Further analysis is underway to identify the causes

of specific shortcomings in the model, and to evaluate

the model results against the airborne and MAPS CO measurement data sets as well. It is anticipated that a simulation with an updated biomass-burning source function will

be completed shortly. In addition, enhancements to the

model are being developed to characterize the budget of

CO in various regions of the globe.

Use of Satellite Data

Prior to the deployment of the EOS sensors, this project

involves the use of space-based CO measurements made

during the 1994 SRL-1 and SRL-2 space-shuttle flights.

Subsequent to the launch of the EOS Terra platform, model

results will be evaluated against tropospheric CO measurements from MOPITT.

Principal Investigator

Prasad Kasibhatla

Prasad Kasibhatla received his undergraduate degree from

Bombay University and his M. S. and Ph.D degrees from

the University of Kentucky. He has 15 years of experience in regional and global tropospheric chemistry research. He is particularly interested in the effects of anthropogenic emissions on atmospheric chemical composition. From 1988 to 1995, he was a research scientist at

the Georgia Institute of Technology. During this period

he was also a visiting scientist at NOAA/GFDL from 1988

to 1993, and at NASA/GSFC from 1994 to 1995. From

1995 to 1996 he was a research scientist at MCNC/Environmental Programs. He is currently an assistant research

professor at Duke University, where he also teaches a

graduate-level course in atmospheric chemistry. In addition to his research and teaching responsibilities, he is

currently serving as co-convener of the IGAC/Global Integration and Modeling (GIM) Activity and is a member

of the organizing committee of the Fourth World Climate

Research Programme Workshop on Chemical Transport

Modeling. He has received a NASA Group Achievement

Award for his role as a member of the MAPS Science

Team.

Co-Investigators

Vickie S. Connors - NASA/Langley Research Center

Jennifer A. Logan - Harvard University

Richard Menard - University of Maryland Baltimore

County/JCEST

Paul C. Novelli - NOAA/Climate Monitoring and Diagnostics Laboratory

Henry G. Reichle - North Carolina State University

References

Allen, D.J., P. Kasibhatla, A.M. Thompson, R.B. Rood,

B.G. Doddridge, K.E. Pickering, R.D. Hudson, and S.-J.

Lin, 1996: Transport-induced interannual variability of

carbon monoxide using a chemistry and transport model.

J. Geophys. Res., 101, 28,655-28,669.

Connors, V.S., T. Miles, and H.G. Reichle, Jr., 1989:

Large-scale transport of a CO-enhanced air mass from

Europe to the Middle East. J. Atmos. Chem., 9, 479-496.

Newell, R.E., S.T. Shipley, V.S. Connors, and H.G.

Reichle, Jr., 1988: Regional studies of potential carbon

monoxide sources based on space shuttle and aircraft

measurements. J. Atmos. Chem., 6, 61-81.

Reichle, H.G., Jr., V.S. Connors, J.A. Holland, W.D.

Hypes, H.A. Wallio, J.C. Casas, B.B. Gormsen, M.S.

Saylor, and W.D. Hesketh, 1986: Middle and upper tropospheric carbon monoxide mixing ratios as measured

by a satellite-borne remote sensor during November 1981.

J. Geophys. Res., 91, 10,865-10,887.

Reichle, H.G., Jr., V.S. Connors, J.A. Holland, R.T.

Sherrill, H.A. Wallio, J.C. Casas, E.P. Condon, B.B.

Gormsen, and W. Seiler, 1990: The distribution of middle

tropospheric carbon monoxide during early October 1984.

J. Geophys. Res., 95, 9845-9856.

Watson, C.E., J. Fishman, and H.G. Reichle, Jr., 1990:

The significance of biomass burning as a source of carbon monoxide and ozone in the southern hemisphere tropics: A satellite analysis. J. Geophys. Res., 95, 16,443-

16,450.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 235

Southern Ocean Seasonal Net Production

From Atmosphere and Ocean Data Sets

Principal Investigator – R. F. Keeling

Scientific Background

As it is not possible to directly observe many of the key

quantities needed for adequately understanding the biogeochemical cycling of materials on the Earth, it therefore is crucial to develop methods for estimating these

quantities from those we can observe. Specifically needed

are methods that improve our capability to extrapolate

local observations to the larger spatial scales. One of the

significant components that is under detailed study by the

Joint Global Ocean Flux Study (JGOFS) is the net photosynthesis of the oceanic photic zone and its relationship

to surface CO2 partial pressure and air-sea CO2 flux. While

models and extrapolations of ocean total and net primary

production are available, there has been limited use of

global chemical data sets to constrain the estimates.

Over the past few years several large data sets have

been gathered by JGOFS and other programs for the purpose of determining processes that control the partitioning of carbon in the ocean and exchanges between the

ocean and the atmosphere and for developing the capability to predict how changes in the environment will influence this partitioning (Sarmiento and Armstrong 1997).

Several of these data sets, including the JGOFS/WOCE

survey of ocean carbon concentrations (Takahashi et al.

1997), the climatology of seasonal O2 variability in surface waters (Najjar and Keeling 1997), observations of

variations in the atmospheric O2 concentration (Keeling

et al. 1996; Bender et al. 1996; Keeling et al. 1997), and

satellite observations of ocean color (Feldman et al. 1989),

provide unprecedented opportunities for characterizing

and interpreting chemical fluxes on large spatial scales.

Science Goals

An analysis of the relationships between the large-scale

chemical data sets, their relationship to ocean productivity, and linkages to the ultimate physical, biological, and

chemical controls on productivity is our primary objective. Our study will focus on using chemical budgets to

constrain productivity and carbon fluxes at middle and

high latitudes in the Southern Hemisphere. We choose to

focus on these regions because of their importance in controlling exchanges with the deep ocean (Sarmiento and

Toggweiler 1984; Siegenthaler and Wenk 1984; Broecker

1991), because the high degree of zonal symmetry in both

the ocean and the atmosphere presents a natural testbed

for models, and because the new data sets provide unprecedented opportunities for improving flux estimates

in these regions.

The biological production and deep mixing of the

Southern Ocean lead to significant exchange of O2 with

the atmosphere on seasonal time scales. These exchanges

are most graphically illustrated in the seasonal variations

in O2 concentration that have been observed at surface

stations at middle and high latitudes of the southern hemisphere (Keeling and Shertz 1992; Bender et al. 1996;

Keeling et al., 1998). The oceans tend to be a source in

the spring and summer months when light levels are higher

and the water column is well stratified, while they are a

net sink in the winter time. The changes in atmospheric

O2 concentration are dispersed throughout the southern

hemisphere on time scales of week to months, although

the southern hemisphere as a whole remains largely isolated from the northern hemisphere on these time scales

due to slow mixing across the intertropical convergence

zone (Keeling and Shertz 1992). Superimposed on these

biologically-mediated fluxes are additional O2 fluxes

driven by temperature-induced changes in solubility in

the water. This thermal component is relatively small and

can be reasonably well estimated from the air-sea heat

flux allowing the larger biologically mediated component

to be computed from the total flux minus the thermal flux.

It is also possible that the biological component of the

flux may be closely associated with the net air-heat flux,

a possibility that was first suggested in Keeling et al.

(1993), and which will be exploited further in our studies.

The seasonal variations in atmospheric O2 concentration place constraints on the magnitude of net ingassing

and outgassing of O2 with the ocean on a seasonal time

scale. While the atmospheric data alone constrain the

magnitude of the air-sea fluxes only over large scales due

to atmospheric mixing, additional information on the patterns of air-sea O2 exchange are provided by the climatology of dissolved O2 saturation in surface waters and

climatological estimates of the air-sea gas exchange velocity (Keeling et al. 1997; Najjar and Keeling 1997). In

the Southern Ocean, where the O2 climatology suffers

from sparseness of observations, the resolution is effec-
236 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

tively limited to seasonal time scales and zonal averages

over broad (~10°) latitude bands. Importantly, however,

the possibility exists of improving the O2 flux climatology based on more-recent surface-dissolved O2 measurements and by using the air-sea heat flux to extrapolate

into data-poor regions. Using heat fluxes for extrapolation may be advantageous because the heat fluxes are

available in various forms with much higher spatial and

temporal resolution than the near-surface dissolved O2

data.

The biological component of the O2 flux is closely

linked to the net community production of organic carbon in the upper ocean (Keeling and Shertz 1992; Keeling et al. 1993; Bender et al. 1996). We plan to use the

air-sea O2 flux maps to derive estimates of community

production in the mixed layer by combining the O2 flux

data with additional data on the seasonal variations of O2

in and below the mixed layer and with rates of vertical

transport. We expect to carry out this analysis with

monthly time resolution and with spatial resolution corresponding to zonally averaged bands with 5°-to-10° resolution. Following this analysis, and taking advantage of

ongoing programs to document changes in atmospheric

O2 concentration , radiative forcing, SST, and air-sea heat

flux, we will expand this analysis to examine patterns of

interannual variability of productivity, carbon, and oxygen fluxes. The annual and interannual production and

flux fields which we derive will also facilitate collaborative studies of the relationship between these quantities

and satellite observations of ocean color.

An additional application of our approach is testing

for consistency between surface O2 maps and surface maps

of CO2 partial pressure (Takahashi et al. 1997). It was

shown in Keeling et al. (1993) that if there exists locally

a tight relationship between seasonal variations in oxygen flux and heat flux, then there must also exist a tight

relationship between SST and surface-dissolved inorganic

carbon (which is closely related to CO2 pressure). We plan

to explore whether these relationships actually hold in

the real world using our O2 flux maps and the surface

inorganic carbon data sets (e.g., Takahashi et al. 1997) as

the basis for comparison. If the approach works well

enough, we can use the O2 flux maps to provide improved

estimates of seasonal carbon variations in the ocean and

also to provide improved estimates of the net seasonal

air-sea CO2 flux.

Use of Satellite Data

We require surface wind and net air-sea heat-flux fields,

derived in part from satellite observations, to estimate surface oxygen flux. More generally, our goal is to develop

data products that will facilitate collaborative studies of

ocean productivity based on ocean color.

Current Activities

As a preliminary study of O2/carbon linkages, we are reexamining the framework Keeling et al. (1993) for estimating seasonal O2 fluxes using estimates of variations

of dissolved inorganic carbon in the water and heat flux.

We are exploring whether using the enlarged carbon data

sets from Takahashi et al. (1997), lead to more-successful predictions of the variations in atmospheric O2 using

this framework. This will provide a very broad-scale check

of the level of consistency between ocean carbon and atmospheric oxygen data sets. We are also gathering together relevant global and southern hemisphere data sets

to begin exploratory studies of possible relationships between seasonal O2 flux and seasonal net air-sea heat flux.

These will then be used to derive improved estimates of

surface water O2 variations and air-sea O2 flux in datasparse regions. These in turn will be used to provide estimates for net community production. This project is still

in its beginning phases.

References

Bender, M., J.T. Ellis, P.P. Tans, R.J. Francey, and D.

Lowe, 1996: Variability in the O2/N2 ratio of southern

hemisphere air, 1991-1994: implications for the carbon

cycle. Global Biogeochem. Cycles, 10, 9-21.

Broecker, W.S., 1991: The great ocean conveyor. Oceanography, 4, 79-89.

Feldman, G., N. Kuring, et al., 1989: Ocean Color: Availability of the global data set. EOS, 70, 634-645.

Keeling, R.F., and S.R. Shertz, 1992: Seasonal and interannual variations in atmospheric oxygen and implications

for the global carbon cycle. Nature, 358, 723-727.

Keeling, R.F., R.G. Najjar, M.L. Bender, and P.P. Tans,

1993: What atmospheric oxygen measurements can tell

us about the global carbon cycle. Global Biogeochem.

Cycles, 7, 37-67.

Keeling, R.F., S.C. Piper, and M. Heimann, 1996: Global

and hemispheric CO2 sinks deduced from changes in atmospheric O2 concentration. Nature, 381, 218-221.

Keeling, R.F., B.B. Stephens, R.G. Najjar, S.C. Doney,

D. Archer, and M. Heimann, 1998: Seasonal variations in

the atmospheric O2/N2 ratio in relation to the kinetics of

air-sea exchange of O2. Global Biogeochem. Cycles, 12,

141-163.

Najjar, R.G., and R.F. Keeling, 1997: Analysis of the mean

annual cycle of the dissolved oxygen anomaly in the world

ocean. J. Mar. Res., 55, 117-151.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 237

Sarmiento, J.L., and R.A. Armstrong, 1997: U.S. JGOFS

Implementation Plan for Synthesis and Modeling, The

Role of Oceanic Processes in the Global Carbon Cycle,

U.S. JGOFS Planning Office, Woods Hole.

Sarmiento, J.L., and J.R. Toggweiler, 1984: A new model

for the role of the oceans in determining atmospheric

PCO2. Nature, 308, 621-624.

Siegenthaler, U., and T. Wenk, 1984: Rapid atmospheric

CO2 variations and ocean circulation. Nature, 308, 624-

626.

Takahashi, T., R.A. Feely, R. Weiss, et al. 1997: Global

air-sea flux of CO2: an estimate based on measurements

of sea-air pCO2 difference. Proc. Nat. Acad. Sci.
238 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The Hydrologic Cycle and Climatic Processes in

Arid and Semi-Arid Lands

Principal Investigator – Yann Kerr

Lead U.S. Investigator – Soroosh Sorooshian

International Co-Sponsor – France

Science Background

Remotely sensed and other kinds of EOS data will allow

scientists to monitor the changes in hydrologic fluxes

brought about by a variety of forcings. The integration of

such data with robust hydrologic models will make possible a better understanding of the processes that control

changes in hydrologic storages and fluxes. This knowledge will allow scientists to better assess the role of the

hydrologic cycle in a global context and to predict the

effects of natural or human-induced climate change. Such

information is particularly critical in the southwestern U.S.

and Mexico, and in Sahelian Africa, where the quality of

life and agricultural productivity are especially sensitive

to changes in the hydrologic cycle and where space-based

remote sensing is particularly effective.

Science Goals

The major objective of this research is to monitor and

study the hydrological cycle and climatic processes in arid

and semi-arid areas with the use of EOS data applied to

temporally and spatially distributed models. This objective is addressed in terms of the following four major

goals:

1) Identify the dominant hydrologic processes and understand how they change as a function of time/space

scale in arid/semi-arid regions;

2) Develop a modeling framework that is capable of assimilating remote-sensing data to capture the interactions, at multiple spatial and temporal scales, between

land-surface characteristics, meteorologic conditions,

regional climate, and land-surface water and energy

fluxes and state variables in arid/semi-arid regions;

3) Assess, through process studies and modeling exercises, the magnitudes of spatially and temporally distributed water and energy fluxes and state variables

and their interactions with surface characteristics and

regional climate in arid/semi-arid regions, particularly

in the Lower Colorado River basin; and

4) Demonstrate the utility of remote-sensing-enabled

models in regional/subregional water resources assessment, particularly within the Lower Colorado

basin.

Our strategy is to approach similar problems from

different time and space scales and at different levels of

model complexity in order to find the most robust and

accurate description of the hydrologic cycle across the

world’s vast arid/semi-arid regions.

Current Activities

Our research aims to significantly improve the human

ability to both monitor (measure) and simulate (model)

land-surface hydrologic processes across a range of spatial and temporal scales. These parallel themes are both

critical to our success. One thrust is, therefore, to develop

algorithms that efficiently and accurately convert electromagnetic signals obtained from EOS (and other) sensors into hydrologic parameters and variables. The parallel thrust is to understand and model the way in which

fundamental hydrologic processes operate and how they

interact with each other.

Our activities include: calibration and validation of

optical, thermal, and microwave satellite data derived from

simultaneous ground/satellite measurements across highly

instrumented watersheds in the U.S., France, and the Sahel

region of Africa; aggregation and dis-aggregation of modeled and observed variables at General Circulation Model

(GCM) scales; development of a distributed land-surface

model (LSM) of the hydrology and hydro-meteorology

in semi-arid regions for coupling with mesoscale and

GCM atmospheric circulation models; and multi-criteria

methods for calibration of land-surface models. These

activities are coordinated between two teams, one in

France and the other in the U.S.

The French Team seeks to quantify and monitor natural and anthropogenically induced changes in hydrologically relevant surface parameters at mesoscales. Work performed to date has dealt mainly with investigating the

extraction of geophysical parameters from remotely

sensed data. First, sophisticated radiometric models are

developed that include various perturbing factors (atmosphere, directional effects, canopy structure). After validation, these models are re-parameterized to derive moretractable and robust inversion algorithms, which are subsequently validated using ground experiments. Similarly,

flux-assessment algorithms are being developed and tested

together with models of the scaling factors. In order to
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 239

assess CO2 fluxes, net primary production models are

being developed. They rely on vegetation-growth models and thus couple water and energy budgets with generic vegetation models under an assimilation scheme.

The U.S. team is focused on the understanding and

modeling of hydrologic processes at the sub-watershed,

watershed, basin, and regional scales. Satellite data are

used to derive distributed basin characteristics and the

inputs to water/energy simulation models. Progress to date

has included: multiple-scale studies of hydrologic variability, satellite validation, and the behavior of sparse

desert canopies; development of a semi-arid distributed

hydro-meteorology model which couples the SiB landsurface scheme with the Regional Atmospheric Modeling System (RAMS) in a manner which facilitates the

assimilation of various types of remote-sensing data and

products; development of multi-criteria sensitivity-analysis/parameter-estimation/model-evaluation methods that

show potential for significantly improving the performance of LSMs; development of improved rainfall-estimation algorithms that incorporate TRMM satellite data;

and development and initial testing of an improved snow

model for coupling with regional climate/weather models, LSMs, and GCMs. In addition, members of our team

have conducted and participated in several experiments

aimed at refining soil-moisture-estimation algorithms,

understanding scaling and aggregation issues, watershed

characterization, vegetation response to large-scale circulation, and evaluation of soil/water-retention models.

Use of Satellite Data

The hydrological sciences and the entire investigation

team look forward to well-calibrated, atmosphericallycorrected and geo-referenced EOS-era satellite products

to better characterize sparse canopies and soils (ASTER),

seasonal vegetation and bidirectional reflectance (MODIS, MISR), radiation (CERES), and precipitation and

soil moisture (AMSR-E). Equally important are non-EOS

sensors operated by NOAA and ESA, particularly with

regard to diurnal radiation, clouds, and active microwave

measurements. We are involved at different levels in several EOS instrument teams (MODIS, AMSR-E, ASTER)

as well as other instrument teams for satellite instruments

(POLDER, Vegetation Monitoring Instrument (VMI) [on

SPOT 4], TRMM) and for airborne instruments [Microwave Imaging Radiometer with Antenna Synthesis

(MIRAS), PORTOS, ESTAR]. (PORTOS is an airborne/

ground passive microwave radiometer [6 frequencies from

1.4-to-90 GHz, dual polarized]).

Participation in Field Programs

From the onset, members of our teams have played leading roles in the organization and support for a number of

field experiments. The HAPEX-Sahel experiment took

place in 1991-1993, with an intensive observation period

in 1992 over a GCM-size grid square. (HAPEX -Sahel is

the Hydrologic Atmosphere Pilot Experiment in the

Sahel.) The USDA-ARS Walnut Gulch watershed in

Southeast Arizona has also been the focus of several field

campaigns such as the MONSOON 90, where observations were made at a range of scales (1-10000 km2 ). Team

members participated in several intensive-observationperiod field-scale experiments over the Maricopa Agricultural Center (Arizona, USA) in 1995-96, an aircraft

campaign over Landes Forest near Bordeaux (France) in

1996, and an intensive field campaign near Toulouse

(France) in 1996. The field work is now primarily focused

on the Upper San Pedro (Arizona, USA) in conjunction

with the Semi-Arid Land Surface Atmosphere program

(SALSA). Several of us have also been involved with other

international initiatives related to global change such as

IGBP and GEWEX.

Principal Investigator

Yann Kerr

Yann Kerr received his Ph.D. from the Université Paul

Sabatier, Toulouse, France, and his M.S. from Glasgow

University, U.K. From 1980 to 1985, he was with the

Centre National d’Etudes Spatiales (CNES) in Toulouse.

He joined the Laboratoire d’Études et de Recherches en

Télédétection Spatiale (LERTS) when it was established

in 1985. From 1987 to 1988, he took a leave of absence

to work at the Jet Propulsion Laboratory in Pasadena, CA.

Kerr has worked mainly with the METEOSAT, Nimbus

7 Scanning Multispectral Radiometer (SMMR), ERS-1

Wind-scatterometer, and the Advanced Very High Resolution Radiometer (AVHRR) systems in order to improve

the use of thermal infrared, microwave, and visible/nearinfrared data for assessing surface fluxes related to the

hydrological cycle. He has been involved in several field

experiments in Sahelian Africa, in the U.S., and in Europe. Kerr has served as a principal investigator on various projects and has helped organize the HAPEX-Sahel

experiment.

Lead U.S. Investigator

Soroosh Sorooshian

Prof. Sorooshian’s primary research is in surface hydrology, with particular emphasis on precipitation-runoffmodeling utilization of remote-sensing information in the

hydrology of arid/semi-arid regions, as well as water-resources management issues. His research activities are

funded primarily by NASA, NSF, and NOAA. Sorooshian

is a member of several National Research Council (NRC)

committees and is currently the Chair of the National

Academy’s Global Energy and Water cycle Experiment

(GEWEX) panel. He is also serving on various advisory

panels in agencies at both the national and international
240 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

levels; in particular he is a member of the science advisory board of NOAA and incoming chair of GEWEXSSG. He has been an active member of several professional societies and has served in various capacities

(former Head of the Department of Hydrology and Water

Resources, University of Arizona; former Editor of Water Resources Research, published by the American Geophysical Union; former member of the Council of the

American Meteorological Society; etc.) He is currently

the special editor for hydrology of the Bulletin of the

American Meteorological Society (BAMS), and is the

President of the Hydrology Section of AGU. Sorooshian

is a Fellow of AAAS, AGU, AMS, and formerly of the

Udall Center for Public Policy during 1993-94.

Co-Investigators

Agnes Bégué - Centre de Coopération Internationale en

Recherche Agronomique pour le développement

Abdelghani Chehbouni - Institut Français de Recherche

Scientifique pour le Developpement en Coopération

Gérard Dedieu - Centre National d’Etudes Spatiales

(CESBIO)

Xiaogang Gao - University of Arizona/Hydrology and

Water Resources

David Goodrich - USDA/Agricultural Research Service

Hoshin Gupta - University of Arizona/Hydrology and

Water Resources

Bisher Imam - University of Arizona/Hydrology and Water Resources

Jacques Imbernon - Centre de Coopération Internationale

en Recherche Agronomique pour le développement

Jean-Pierre Lagouarde - Institut National de Recherche

Agronomique

M. Susan Moran - USDA/Agricultural Research Service

Bernard Seguin - Institut National de Recherche

Agronomique

James Shuttleworth - University of Arizona/Hydrology and

Water Resources

James Smith - Princeton University

Alain Vidal - International Programme on Technology and

Research in Irrigation and Drainage (IPTRID) FAO/

AGLW

Jean-Pierre Wigneron - Institut National de Recherche

Agronomique

References

Chehbouni, A., E. Njoku, J.-P. Lhomme, and Y. Kerr, 1995:

Approaches for averaging surface parameters and fluxes

over heterogeneous terrain. J. Climate, 8, 1386-1393.

Gao, X., and S. Sorooshian, 1994: A stochastic precipitation disaggregation scheme for GCM applications. J. Climate, 7, 238-247.

Gupta, H.V., L.A. Bastidas, S. Sorooshian, W.J.

Shuttleworth, and Z.L. Yang. 1999: Parameter estimation

of a land surface scheme using multi-criteria methods. J.

Geophys. Res., in press.

Kustas, W.P., and D.C. Goodrich, 1994: Preface: special

section on Monsoon ’90 Multidisciplinary Experiment.

Water Resources Res., 30, 1211-1225.

Sano, E.E., M.S. Moran, A.R. Huete, and T.R. Miura,

1998: C- and Multi-angle Ku band synthetic aperture radar data for bare soil moisture estimation in agricultural

areas. Rem. Sens. Environ., 64, 77-90.

Xu, L., X. Gao, S. Sorooshian, P.A. Arkin, and B. Imam,

1999: A microwave infrared threshold technology technique to improve the GOES precipitation index. J. Appl.

Meteor., in press.

Investigation URLs

http://www.hwr.arizona.edu/uaids_home.html

http://www.hwr.arizona.edu/cgi-bin/uadata_browse

http://www.orstom.fr/hapex/

http://www.tucson.ars.ag.gov/salsa/salsahome.html

http://www-sv.cict.fr/cesbio
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 241

Climate and Chemical Cycles: The Role of Sulfate and Ozone in Climate Change

Principal Investigator – Jeffrey T. Kiehl

Science Background

Human activities have led to dramatic changes in the

chemical composition of Earth’s atmosphere over the past

century. Projections for changes into the 21st century indicate the potential for continued changes. Previous studies of the potential climate impacts of these changes in

the chemical composition of the atmosphere have used

climate models with specified changes in composition.

Also, much of climate-change research has solely focused

on increases in carbon dioxide, methane, nitrous oxide,

and chlorofluorocarbons. Important changes have also

occurred in sulfate aerosols and atmospheric ozone over

the past. Changes in climate and changes in chemical composition are not uncoupled from one another. Chemical

processes depend on climate processes such as convective transport, the hydrologic cycle, and radiation. Thus,

to comprehensively study climate and chemistry problems requires the use of both climate and chemical transport models. The most complete treatment requires the

full coupling of chemistry and climate models. It is now

recognized that changes in sulfate aerosols and ozone can

potentially contribute to significant climate change. Sulfate aerosols can reflect solar radiation back to space both

directly and through the modification of cloud albedo,

the so-called indirect effect. This implies a negative forcing to the climate system. Increases in tropospheric ozone

leads to increased radiative forcing of the climate system, while decreases in stratospheric ozone lead to a reduction in radiative forcing. Changes in sulfate aerosols

and ozone lead to significant changes in the regional patterns of net forcing. These spatial patterns in net forcing

are important to regional climate change.

Science Goal

The key goal is to quantify the roles of sulfate aerosols

and ozone in the climate system. The focus is to carry out

simulations with the NCAR CCM3 climate model that

incorporates a sulfur chemistry model that simulates both

the direct and indirect effects of sulfate aerosols on the

climate system. This model will be used to simulate both

the present-day effects of sulfate aerosols and the predicted change in climate over the past 120 years due to

changes in the amount of aerosols due to anthropogenic

activity. Climate-change simulations will also be carried

out for future scenarios. Two chemical transport models

IMAGES and the Model for OZone And Related chemical Tracers (MOZART) will be used in conjunction with

the NCAR CCM3 climate model to study the climate effects of changes in ozone, both tropospheric and stratospheric over the past 120 years and potential future

changes. The accuracy of present-day simulations of aerosols and ozone will be evaluated through the use of satellite data. These studies will lead to the coupling of the

climate and chemistry model to study the non-linear interactions between chemistry and climate.

Current Activities

Studies have been carried out on the radiative forcing due

to tropospheric sulfate aerosols, tropospheric ozone, and

stratospheric ozone. The tropospheric sulfate distributions

were obtained from the latest version of the NCAR CCM3

that includes a prognostic cloud-water scheme and a sulfur-chemistry model. The model prognoses SO2, DMS,

and SO4, where the mass of sulfate is predicted. The oxidant distributions, NO3, O3, OH, and a diagnosed H2O2

are obtained from the chemical transport model, IMAGES.

Simulations have been carried out with pre-industrial

emissions and present-day emissions of sulfur; the global

annual mean direct forcing is -0.56 Wm-2. Simulations

have been carried out on the indirect effect of aerosols on

clouds. The range in the global annual mean indirect effect is -0.7 to -1.8 Wm-2, where the uncertainty is due to

uncertainties in linking aerosol mass to cloud-drop number concentration. AVHRR and SSM/I satellite data are

being used to understand the causes for these uncertainties in model-predicted cloud-drop size.

Parallel to the sulfate studies, a wide range of simulations with IMAGES and MOZART has been carried out

on tropospheric ozone for present, past, and future time

periods. For present-day conditions the model-predicted

ozone has been compared with satellite observations.

Radiative-forcing calculations have been carried out for

these cases. For the pre-industrial-to-present changes in

tropospheric ozone, a radiative forcing of 0.48 Wm-2 is

obtained. This forcing will be less when reductions in

stratospheric ozone are included.
242 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Use of Satellite Data

For the pre-launch time period, a variety of satellite data

is being used to evaluate the model-simulated distributions of sulfate aerosols and ozone. For cloud and aerosols, SSM/I, AVHRR, SAGE, and ERBE data are employed. Currently, the visible aerosol optical depth from

the model is compared to the AVHRR product. Modelpredicted cloud-drop sizes are compared against the

AVHRR-retrieved data from the Han et al. study. For

ozone, SAGE and TOMS products are used to evaluate

the model-simulated total-ozone abundance for both the

total column, and the troposphere and the stratosphere,

separately.

For the post-launch time period, MODIS and MISR

products will be used to evaluate aerosol optical depth.

MODIS will also be used to evaluate model-predicted

cloud-drop size, which should reveal aerosol indirect effects. CERES data will be used to compare the top-ofatmosphere Earth radiation budget to model simulations.

For the chemical transport model, MOPITT data will be

used to evaluate the simulated CO and CH4 fields.

Participation in Field Programs

The investigators are involved in a number of field programs that are linked to the goals of this project. The PI is

a member of the steering committee of the Indian Ocean

Experiment (INDOEX), which is focused on satellite and

in situ measurements of the direct and indirect effects of

sulfate aerosols, and also the measurements of ozone.

Principal Investigator

Jeffrey T. Kiehl

Jeffrey Kiehl received his Ph.D. in Atmospheric Science

from the State University of New York at Albany in 1981.

He is currently the head of the Climate Modeling Section

at the National Center for Atmospheric Research. His main

research interests are in climate modeling, cloud-radiation interactions, and climate effects of aerosols. His current research is on the climate effects of aerosols and the

interaction between chemistry and climate. As co-chair

of the Climate System Model working group on Chemistry and Climate Change, he has worked toward providing

new estimates of climate-forcing factors for the past 120

years. These factors are being used in the National Assessment of Climate. He has also worked on radiativedynamical interactions in the stratosphere. His research

employs models, satellite, and in situ observations. He is

the co-director of the Center for Clouds, Chemistry and

Climate, and a past member of the Climate Research Committee.

Co-Investigators

Guy Brasseur - National Center for Atmospheric Research

D. Hauglustaine - National Center for Atmospheric Research

C. Granier - NOAA Aeronomy Laboratory

B.A. Ridley - National Center for Atmospheric Research

References

Brasseur, G.P., D. A. Hauglustaine, S. Walters, P. J. Rasch,

J.F. Muller, C. Granier, and X.X. Tie: MOZART: a global

chemical transport model for ozone and related chemical

tracers, part 1, model description. J. Geophys. Res., submitted.

Brasseur, G.P., J.T. Kiehl, J.F. Muller, T. Schneider, C,

Granier, X.X. Tie, and D.A. Hauglustaine, 1998: Past and

future changes in global tropospheric ozone: impact on

the radiative forcing. Geophys. Res. Lett., 25, 3807-3810.

Han, Q., W.B. Rossow, and A.A. Lacis, 1994: Near-global survey of effective droplet radii in liquid water clouds

using ISCCP data. J. Climate, 7, 465-497.

Hauglustaine, D. A., G.P. Brasseur, S. Walters, P. J. Rasch,

J.F. Muller, L.K. Emmons, and M.A. Carroll: MOZART:

a global chemical transport model for ozone and related

chemical tracers, part 2, model results and evaluat. J.

Geophys. Res., submitted.

Kiehl, J.T., T.L. Schneider, P.J. Rasch, M.A. Barth, and J.

Wong: Radiative forcing due to sulfate aerosols from

simulations with the NCAR community climate model

(CCM3). J. Geophys. Res., submitted.

Kiehl, J.T., T.L. Schneider, R. Portmann, and S. Solomon:

Climate forcing due to tropospheric and stratospheric

ozone. J. Geophys. Res., submitted.

Investigation URL

http://www.cgd.ucar.edu/cms/eos/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 243

Urban Metabolism and Trace Gas Respiration

Principal Investigator – Charles E. Kolb

Science Background

Cities and their associated industrial areas are dynamic

entities which consume and metabolize fuels, foodstuffs,

and industrial and commercial chemicals in the course of

daily urban activities. This consumption of organic and

inorganic materials leads directly to respiration of a wide

range of trace gases from urban areas. Many of these respiration products play a major role in urban and regional

air pollution, while the longer lived gases can be a significant input to global atmospheric chemical budgets.

Analyses of the trace-gas levels found in urban atmospheres demonstrate that cities are major sources of

greenhouse gases such as carbon dioxide (CO2), nitrous

oxide (N2O), methane (CH4), and halocarbons (e.g.,

CFCl3, CF2Cl2, CH3CCl3). The latter also lead to stratospheric ozone destruction. Our previous work has quantified significant CH4 emission fluxes from urban features

such as natural-gas distribution systems, municipal-wastewater treatment plants, and waste-disposal landfills. Of

course, fossil-fuel-combustion-exhaust sources associated

with industrial boilers, commercial and industrial space

heating, and transportation systems have long been identified as major sources of carbon dioxide emissions. In

addition, combustion sources, most particularly fluidizedbed coal combustors and automobiles equipped with

modern catalytic converters, are sources of nitrous oxide

(N2O). Since each of these directly forcing greenhouse

trace gases has a disproportionate impact upon the Earth’s

radiation budget, urban respiration products are an important aspect of potential global warming.

In addition to the emission of long-lived greenhouse

and ozone-depletion source gases, urban/industrialized

areas are also major sources of precursor species for tropospheric aerosols, including: condensation nuclei (CN),

sulfur dioxide (SO2) and volatile organic compounds

(VOCs); and the key precursor gases for tropospheric

ozone and associated oxidants, including: nitrogen oxides (NO, NO2), carbon monoxide (CO), and VOCs.

New and efficient methods are needed to characterize trace-gas emission fluxes from urban and industrialized areas, to connect these fluxes to quantitative measures of the urban and industrial activities which create

them, and to develop urban/industrial activity parameters

accessible to characterization and quantification by remote sensing which can predict trace-species emissions

and represent the factors which control them.

Science Goals

This project addresses the development and utilization of

better in situ experimental measurement techniques based

on sensitive, accurate, real-time, trace-gas and particulate sensors deployed on mobile platforms, coupled with

innovative models of urban/regional atmospheric chemistry and transport. Together, these experimental and modeling methods will be used to design better measurement

strategies and to analyze trace-gas concentration and flux

data. This project also involves the use of urban/industrial geographic information systems and databases to

correlate observed trace-gas-emission fluxes (urban respiration) with urban and industrial activity and consumption factors (urban metabolism). Finally,where possible,

statistically meaningful correlations between measured

trace-gas emissions and urban/industrial activity/consumption factors will be used to identify parameters accessible to air- and satellite-borne remote-sensing systems

in order to enable automated estimates of urban and industrial trace-gas emissions relevant to global change and

regional pollution issues.

Current Activities

Initial project activities are focused on developing and

deploying the tools required to perform the required field

measurements and concomitant data analysis and interpretation activities. These include: a series of sensitive,

specific, real-time (~1-second response) sensors for greenhouse, aerosol precursor, and ozone-precursor trace gases

and fine particulates; a global positioning system (GPS)-

equipped step-van mobile laboratory for trace gas/fineparticulate-concentration mapping and flux measurements; a tethered balloon-borne sampling system for performing vertical trace-gas profile measurements; a calibrated SF6 tracer gas release and monitoring system for

urban plume flux measurements; a set of urban air quality and transport models designed to aid in field-measurement design and inversion of concentration maps and

plume flux data to quantify urban-area trace-gas and par-
244 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

ticulate-emission flux distributions; and a geographical

information system (GIS) urban-activity-factor database

for our test urban areas (Manchester, NH and Boston,

MA).

The proposed measurement methods are based upon

techniques we previously developed to measure methane

emissions from natural-gas distribution systems in urban

areas. These techniques are being extended to map the

concentration of a set of gases plus fine particulates and

to measure emission rates of these gases from urban areas. The main experimental advance involves the use of

tunable infrared laser differential-absorption spectrometer

(TILDAS) trace-gas monitors installed in a mobile laboratory to survey urban emissions. Because the instruments

can be tuned for specific gases, a range of different species can be measured simultaneously in real-time. Use of

GPS receivers, GIS databases, and computer algorithms

allows the automated conversion of real-time TILDAS

measurements into concentration maps for selected pollutants. Continuous high-accuracy trace-gas measurements can be coupled with area atmospheric tracer releases to provide a basis for estimating area emission rates.

The area-flux determination is accomplished through the

use of a real-time tracer analyzer also installed in the

TILDAS survey vehicle. Further information needed to

characterize the mix of urban emissions can be obtained

from canister samples collected along survey traverses

and from tethered-balloon vertical profiles. These latter

samples can be analyzed with the TILDAS instruments

as well as with gas-chromatography methods which can

identify hundreds of true VOC species.

Participation in Field Programs

Initial field measurements were planned for late 1997/

early 1998. They will extend through calendar 1998 and

1999 to allow determination of seasonal variations in urban trace-gas and fine-particulate emission patterns. Current plans are to use Manchester, NH (population 100,000)

as an initial testbed to hone measurement and analysis

tools and then to study the metropolitan Boston area (population 2,870,000) as an ongoing field laboratory to assess

seasonal emissions variations. We may extend measurements to other U.S. cities chosen as major field sites by

the North American Regional Strategy for Tropospheric

Ozone (NARSTO) program, if schedule and funding considerations allow.

Use of Satellite Data

Satellite data from Landsat and other surface-imaging

satellite systems will be used, as appropriate, to help prepare GIS urban activity maps of the test urban areas. These

maps will be compared with measured trace-gas/fine-particulate emissions maps obtained from the project’s field

data to investigate correlations between pollutant-emission patterns and urban activity maps. The goal of this

part of the investigation is to identify surrogate urbanarea remote-sensing observables which track and predict

urban-pollution emission levels.

Principal Investigator

Charles E. Kolb

Charles Kolb has been involved in atmospheric chemistry and physics studies for over 25 years. He received his

undergraduate degree in chemical physics from the Massachusetts Institute of Technology (1967) and masters

(1968) and doctoral (1971) degrees in physical chemistry

from Princeton University. He joined Aerodyne Research,

Inc. in 1971 and founded its Center for Chemical and Environmental Physics in 1977. He has served as the

company’s president and chief executive officer since

1985. His research interests include the homogeneous and

heterogenous chemical kinetics of atmospheric and industrial processes and the development and utilization of

advanced trace-gas and aerosol measurement techniques.

He has served on a wide range of NASA and National

Research Council panels, boards, and committees dealing with environmental issues; he received the 1997 Award

for Creative Advances in Environmental Science and

Technology from the American Chemical Society. He is

currently Atmospheric Sciences Editor for Geophysics Research Letters.

Co-Investigators

Joseph Ferreira, Jr. - Massachusetts Institute of Technology

Brian K. Lamb - Washington State University

Gregory J. McRae - Massachusetts Institute of Technology

Robert W. Talbot - University of New Hampshire

References

Blake, D.R., V.H. Woo, S.C. Tyler, and F.S. Rowland,

1984: Methane concentrations and source strengths in

urban locations. Geophys. Res. Lett., 11, 1211-1214.

Blaha, D., B. Mosher, R.C. Harriss, C.E. Kolb, J.B.

McManus, J.H. Shorter, and B. Lamb, 1994: Mapping

urban sources of methane. Geo. Info. Systems, (October),

34-38.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 245

Czepiel, P.M., P.M. Crill, and R.C. Harriss, 1993: Methane emissions from municipal wastewater treatment processes. Environ. Sci. Technol., 27, 2472-2477.

Czepiel, P.M., B. Mosher, J.H. Shorter, J.B. McManus,

C.E. Kolb, E. Allwine, B.K. Lamb, and R.C. Harriss, 1995:

Landfill methane emissions by static enclosures and atmospheric tracer methods. J. Geophys. Res., 101, 16,711-

16,719.

Kolb, C.E, J.C. Wormhoudt, and M.S. Zahniser, 1995:

Recent Advances in Spectroscopic Instrumentation for

Measuring Stable Gases in the Natural Environment.

Methods in Ecology: Trace Gases, P.A. Matson and R.C.

Harriss, Eds. 259-290.

Lamb, B.K., J.B. McManus, J.H. Shorter, C.E. Kolb, B.

Mosher, R.C. Harriss, E. Allwine, D. Blaha, T. Howard,

A. Guenther, R.A. Lott, R. Siverson, H. Westberg, and P.

Zimmerman, 1995: Development of atmospheric tracer

methods to measure methane emissions from natural gas

facilities and urban areas. Environ. Sci. Technol., 29, 1468-

1479.

Milford, J.B., A.G. Russell, and G.J. McRae, 1989: A new

approach to photochemical pollution control: Implications

of spatial patterns in pollutant responses to reductions in

nitrogen oxides and reactive organic gas emissions.

Environ. Sci. Technol., 23, 1290-1301.

Mulholland, M., and J.H. Seinfeld, 1995: Inverse air pollution modelling of urban-scale carbon monoxide emissions. Atmos. Environ., 26A, 113-123.

NRC, 1991: Rethinking the Ozone Problem in Urban and

Regional Air Pollution. National Research Council, National Academy Press, Washington, DC.

Rowland, F.S., N.R.P. Harris, and D.R. Blake, 1990: Methane in cities. Nature, 347, 432-433.

Zahniser, M.S., D.D. Nelson, J.B McManus, and P.L.

Kebabian, 1995: Measurement of trace gas fluxes using

tunable diode laser spectroscopy. Phil. Trans. Royal Soc.,

A351, 371-382.

Investigation URLs

http://www.aerodyne.com

http://ortho.mit.edu/nasa

Relationship of NO2 to NOx in an urban area. Data collected with a mobile TDL spectrometer on city and highway roads of Manchester,

NH, 2:30-9 pm EDT on 26 August 1998. The darker points are those with corresponding CO2 < 400 ppm and thus are not a result of

directly sampling a combustion source such as vehicle exhaust.
246 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The Land Surface Component of the Climate

System: (i) Improved Representation of

Subgrid Processes and (ii) Analysis of Land

Surface Effects on Climate Variability

Principal Investigator – Randal D. Koster

Science Background

Droughts, floods, and other manifestations of a region’s

hydroclimatology can have tremendous social and economic impacts. Coupled models of the land-atmosphere

system allow an understanding of hydroclimatological

variability that transcends what can be learned from a

strictly observational analysis. Assuming that the coupled

system includes realistic feedbacks between the land surface and the overlying atmosphere (an assumption that

must be constantly critiqued and tested against observations whenever possible), the system can be artificially

manipulated to isolate and characterize the fundamental

physical controls on the variability.

The land-surface models (LSMs) used in such

coupled systems are typically one-dimensional representations of land-surface processes that include such features as a vegetation canopy for explicitly controlling transpiration and multiple soil layers for moisture storage.

The formulations are quite complex in some LSMs, and

several perform well against point measurements. What

most LSMs lack, however, is a proper treatment of the

extensive subgrid variability known to exist over the large

length scales resolved by typical coupled systems. Many

LSMs, for example, include thin soil-moisture layers that

are assumed homogeneously wet across hundreds of kilometers. Given the nonlinear response of evaporation to

soil moisture, vegetation type, surface aspect, and other

spatially varying properties, an improper treatment of

subgrid variability may overwhelm any improvements that

can be made in the one-dimensional physics. This suggests a sensible path for LSM development.

Science Goal

The goal of this project is to improve our understanding

of land-atmosphere feedbacks and their influence on

hydroclimatic variability through model development and

application. The specific objectives are twofold: 1) to produce a land-surface model that explicitly models subgrid

soil-moisture variability and its effects on evaporation and

runoff, and 2) to perform simulation experiments with an

LSM coupled to a general circulation model that characterize land-atmosphere interaction and isolate the mechanisms underlying regional precipitation statistics.

Current Activities

Model development: In a break from traditional modeling strategies, the continental surface is separated into a

mosaic of hydrological catchments with boundaries that

are not constrained by the grid of the overlying atmospheric model. A land-atmosphere-communication algorithm handles the existence of numerous catchments

within a single GCM grid cell and the straddling of some

catchments across grid cells.

Within each catchment, the land-surface model being developed for this project solves the relevant energy

and water-balance equations at every simulation time step.

This model is partly based on existing catchment hydrological models that use topographical indices to treat

subgrid soil-moisture variation explicitly. The treatment

also includes, however, a root-zone-moisture variable to

allow for soil-wetting fronts following storms and to avoid

some of the limitations of the topographic-index approach

in regions of little-to-moderate orography. We avoid a distributed modeling approach within each catchment by

deriving preprocessed relationships that relate average

catchment soil-moisture content to the aspects of spatial

variability relevant to the surface energy and water budget. Global topographic data are being analyzed to derive

the parameters needed for the preprocessed functions.

Model application: Coupled-model simulations are being designed that address various issues related to landatmosphere feedback; some are logical and important extensions of previous work. One set of multi-decade simulations illustrates the role of SST variability in controlling the timing of continental precipitation anomalies and

the concurrent role of land-surface processes in amplifying the anomalies. Another focuses on the predictability

of precipitation when all surface boundary conditions–

over both land and ocean–are known. The large-scale

structures of evaporation and soil-moisture fields are be-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 247

ing examined, as is the effect of improving the land-surface fluxes in a data-assimilation system.

Use of Satellite Data

The Mosaic LSM is currently being incorporated into the

data assimilation system of NASA/GSFC’s Data Assimilation Office. By increasing the realism of the LSM

through sensible model development, we should eventually be able to increase the realism of the atmospheric

model output and thereby increase the value of the assimilated satellite inputs. The sensitivity of the assimilation model fields to land-surface fluxes will, in any case,

be quantified as part of this project.

The Mosaic LSM (and, eventually, the catchment

model) is also a part of NASA’s Seasonal-to-Interannual

Prediction Project (NSIPP), a modeling and data assimilation project aimed at translating satellite ocean data (e.g,

altimetry) and land data (e.g., soil moisture) into longterm predictions. An improved LSM and an improved

understanding of land-atmosphere interactions should, in

principle, lead to improved predictions and thus should

add value to the original satellite data.

Participation in Field Programs

Field measurements of surface-energy and water-balance

fluxes lie at the heart of the LSM validation exercises

performed as part of the international Project for the

Intercomparison of Land-surface Parameterization

Schemes (PILPS) and Global Soil Wetness Project

(GSWP) model-intercomparison projects. Through extensive participation in these projects, the investigators are

learning much about LSM behavior and overall modeling strategy.

Principal Investigator

Randal Koster

Randal Koster joined the Hydrological Sciences Branch

at the NASA/Goddard Space Flight Center upon receiving an Sc.D. from the Massachusetts Institute of Technology in 1988. His research has focused on the development of land-surface schemes for climate models, the

behavior of the coupled land-atmosphere system, and the

global geochemistry of stable water isotopes.

Co-Investigators

Praveen Kumar - Department of Civil Engineering, University of Illinois (Urbana-Champaign)

Max Suarez - Climate and Radiation Branch, NASA/

Goddard Space Flight Center

References

Ducharne, A., R.D. Koster, M.J. Suarez, P. Kumar, and

M. Stieglitz, 1999: A catchment-based land surface model

for GCMs and the framework for its evaluation. Physics

and Chemistry of the Earth, in press.

Koster, R.D., and M.J. Suarez, 1999: A simple framework

for examining the interannual variability of land surface

moisture fluxes. J. Climate, in press.

Koster, R.D., M.J. Suarez, and M. Heiser: Variance and

predictability of precipitation at seasonal-to-interannual

timescales. J. Hydrometeorology, submitted.

Koster, R.D., T. Oki, and M.J. Suarez, 1999: Assessing

success in the offline validation of land surface models.

J. Meteor. Soc. Japan, in press.

Koster, R.D., and P.C.D. Milly, 1997: The interplay between transpiration and runoff formulations in land surface schemes used with atmospheric models. J. Climate,

10, 1578-1591.

Koster, R.D., and M.J. Suarez, 1996: The influence of

land surface moisture retention on precipitation statistics.

J. Climate, 9, 2551-2567.

Koster, R.D., and M. Suarez, 1996: Energy and Water

Balance Calculations in the Mosaic LSM. NASA Tech.

Memo. 104606, Vol. 9.

Koster, R.D., and M.J. Suarez, 1995: The relative contributions of land and ocean processes to precipitation variability. J. Geophys. Res., 100, 13,775-13,790.
248 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Regional Land-Atmosphere Climate Simulation

System (RELACS) for the Asian Monsoon

Region

Principal Investigator – William K. M Lau

Science Background

The Asian monsoon region is the home for over 60% of

the world population. More than half of the population of

the Asian monsoon countries reside within the Southeast

Asian monsoon region. Agricultural productivity and

socio-economic development in Southeast Asia are highly

dependent on the vagaries of the monsoon climate, often

associated with disastrous floods and droughts occurring

from year to year. Recently urban growth and deforestation have further compounded the problems already

caused by natural variability of the monsoon climate.

Because of its unique geographical location, the regional hydrologic cycle of Southeast Asia is very complex, being affected by basin-scale moisture transports

associated with the El Niño, as well as moisture recycling processes within the land-ocean-atmosphere of the

Asian monsoon region. During an average year, from April

through the beginning of May, deep convection migrates

northward along the “land bridge” of the maritime continent from Indonesia, the Malay Peninsula to southern

Thailand. During the early part of the monsoon season

(around middle of May), heavy monsoon rain abruptly

shifts from the land region of Indochina to the South China

Sea, signaling the first stage of the onset of the Asian summer monsoon. Subsequently, the monsoon convection

vacillates between the land region of East Asia and the

South China Sea and tropical western Pacific region. In a

given year, the above scenario may fail to develop or develop with different timing, resulting in delayed or early

onset of the monsoon, at times accompanied by severe

floods or droughts conditions. The physical underpinnings

of the abrupt transitions and interannual variability of the

Southeast Asian monsoon precipitation regimes are unknown and are of great importance in better understanding the mechanism of the regional hydrologic cycle in

the Southeast Asian monsoon region.

On the regional scale, the natural climate variability

associated with atmosphere-land-surface interactions is

much larger than that compared to global or continental

scales. As a result the signal-to-noise ratio is very low,

making regional climate signals very difficult to detect.

To assess the influence of global climate signals on

regional scales, it is necessary to downscale the global

signals and translate them into regional and local forcing

functions for regional climate variability. This is one of

the most challenging problems of climate-change research.

This project will be initially focused on developing

downscaling techniques in the southeast Asian monsoon

region. The methodology developed, with proper modification, will be applicable to different climate regimes.

Science Goals

Our goals are:

1) to provide a better understanding of the physical processes involved in regional atmospheric-land-surface

interactions and their linkages to other components

of the climate system;

2) to enable experimental predictions and studies of regional climate variability due to natural variability,

land use, and global change with application to the

southeast Asia region; and

3) to provide special land-surface data sets and assimilation products for validation of land-atmosphere

models and satellite algorithms.

Key scientific tasks are:

1) To acquire the temporal and spatial distribution of

precipitation, evaporation, moisture storage, and runoff in southeast Asia before and during the monsoon

rainy seasons;

2) to understand the roles of land-surface-atmosphere

feedbacks vs. large-scale remote forcing, in particular, sea-surface temperature, in giving rise to the observed characteristics of land-locked vs. oceanic precipitation in the southeast Asian monsoon region; and

3) to assess the response of regional precipitation and

streamflows in major river basins in Southeast Asia

to natural climate fluctuations and to land-use changes

and different global-change scenarios.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 249

Current Activities

The current research is focused on the downscaling of

climate forcings to regional and local scales via a multiple nesting modeling and satellite-retrieval approach. The

research tasks are divided into three main components:

development of RELACS; validation data-set development and analysis for the GEWEX Asian Monsoon Experiment-Tropics (GAME-T); and climate-downscaling

experiments using RELACS. RELACS has five interlinked modular components: a) a nested mesoscale model

(MM5), b) a coupled land-surface model (LSM), c) a regional 4DDA component d) a GCM/4DDA component,

and e) a macro-hydrologic model component for riverbasin-scale water-resource applications (see figure on

following page). Basic components of the nested regional

model and the GCM component exist at GSFC. The

macro-hydrologic model for GAME-T is provided by Drs.

S. Herath and T. Oki from the University of Tokyo, Japan. This investigation will focus on developmental work

needed to provide a robust interface linking all the existing submodels and infrastructures to develop an integrated

end-to-end climate-prediction system for regional (subcontinental scale) climate applications for GEWEX.

Use of Satellite Data

One of the key attributes of this project is the building of

an end-to-end regional climate-simulation capability at

GSFC that can easily adopt future model improvements

and incorporate new satellite data. The strongest link to

the ESE satellite program is TRMM, which will provide

rainfall and latent heating information for validation, assimilation, and diagnosis for all the research tasks. GMS

radiation data will be used to derive surface radiation budgets over GAME-T. Other satellite data used include SSM/

I, TOVS pathfinder, and AVHRR, for estimation of atmospheric moisture, precipitation, vegetation indices, and

other relevant hydrologic parameters. With the launch of

Terra, data from MODIS and CERES will provide additional information on clouds and land-surface characteristics for re-processing of the data sets to be developed in

this investigation.

Participation in Field Programs

Investigators on this project are actively involved in the

planning, execution, and data analyses of international

field experiments over the southeast Asian region. GAMET is the one of four components of GEWEX, conducting

quantitative monitoring of vapor flux, precipitation,

evapotranspiration, radiative flux, and their seasonal, intra-seasonal and interannual variations over the southeast

Asia with intensive observations over Thailand. GAMET’s role is to observe and investigate the energy and water cycle in the warm humid areas of the Asia Monsoon

region, from tropics to sub-tropics. Another important experiment is the South China Sea Monsoon Experiment

(SCSMEX), which provides enhanced radar rainfall observations over the South China Sea including a vast array of oceanic observations. SCSMEX is jointly sponsored by the WMO/M1 Committee of Atmospheric Sciences, WCRP CLIVAR Monsoon Program, and the Pacific Science Association. It involves the participation of

all major countries and regions of East and Southeast Asia,

as well as Australia and the U.S. Both experiments will

be carried out in conjunction with TRMM.

Principal Investigator

William K.-M. Lau

William Lau received a Ph.D. in Atmospheric Sciences

from the University of Washington in 1977. He was Assistant Professor at the Naval Postgraduate School until

1981. Since then he has been a Senior Research Meteorologist in the Goddard Laboratory for Atmospheres

(GLA) at Goddard Space Flight Center. Currently, he is

Head of the Climate and Radiation Branch of GLA. His

research expertise includes empirical data analysis and

modeling in climate dynamics, tropical and monsoon

meteorology, and ocean-atmosphere interaction. He has

published over 120 research papers in the refereed literature. He is currently the co-chair of the CLIVAR AsianAustralia Monsoon Panel, Chief Scientist for the South

China Sea Monsoon Experiment (SCSMEX), and guest

editor of the Special Issues of the Journal of Climate on

TRMM. He served as Chairman of the American Meteorological Society (AMS) Committee on Climate Variations, member of the U.S. Science Working Group for

TOGA/COARE, chief scientist of the U.S.-People’s Republic of China bilateral research on monsoons, and as a

science team member of TRMM. He was awarded the

AMS Meisinger Award, the NASA John Lindsay Memorial Award for excellence in research, and the Mausum

prize for best research paper (Mausum is a Hindi word

meaning season [or monsoon]). Dr. Lau is a Senior

Goddard Fellow and a fellow of the AMS.

Co-Investigators

S. Herath - University of Tokyo, Japan

T. Oki - University of Tokyo, Japan

The following are from NASA/Goddard Space Flight Center:

M.-D. Chou

W.-K. Tao

Y. Sud

P. Wetzel
250 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

References

Chou, M.-D., 1991: The derivation of cloud parameters

from satellite-measured radiances for use in surface radiation calculations. J. Atmos. Sci., 48, 1549-1559.

Hewitson, B.C., and R.G. Crane, 1996: Climate

downscaling: techniques and application. Climate Research, 7, 85-95.

Bony, S., K.-M. Lau, and Y. Sud, 1997: Sea surface temperature and large scale circulation influences on tropical

greenhouse effect and cloud radiative forcing. J. Climate,

10, 2055-2077.

Lau, K.-M., J.H. Kim, and Y. Sud, 1996: Intercomparison

of hydrologic processes in AMIP GCMs. Bull. Amer.

Meteor. Soc., 77, 2209-2227.

Lau, K.-M., and S. Yang, 1996: The Asian monsoon and

the predictability of the tropical ocean-atmosphere system. Quart. J. Royal. Met. Soc., 122, 945-957.

Lau, K.-M., and S. Yang, 1997: Climatology and interannual variability of the southeast Asian monsoon. Adv.

Atmos. Sci., 14, 141- 162.

Lau, K-M., and W. Bua, 1997: Monsoon-Southern Oscillation Coupling. Climate Dynamics, submitted.

Investigation URL

http://climate.gsfc.nasa.gov/~kim/relacs/

The conceptual framework of RELACS. The core component of the system is represented inside the hatched box.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 251

The Role of Air-Sea Exchanges and Ocean

Circulation in Climate Variability

Principal Investigator – W. Timothy Liu

Science Background

The ocean is forced at the surface largely through the exchanges of water, momentum, and heat. Without surface

forcing, the ocean would just be a static pool of water.

The exchanges drive the transport and change the storage

of heat, water, and greenhouse gases and thus moderate

the world’s climate. The ocean feedback to climate

changes must be manifested through these exchanges,

without which the Earth would be a hostile or less-suitable habitat. We need to study ocean circulation and airsea exchanges to understand natural global changes and

to discern the anthropogenic effects.

The ocean is an under-sampled turbulent fluid with

non-linear interactions; processes at one scale affect processes at other scales. Adequate observations at significant temporal and spatial scales can only be achieved from

the vantage point of space. The life span of a spaceborne

sensor is conducive to the study of seasonal-to-interannual variation. While our focus has been on the variability and predictability in this range of time scale, we have

started to examine how such variability is affected by

shorter (intraseasonal) and longer (decadal) time-scale

changes.

All spaceborne sensors measures various part of the

same electromagnetic spectrum and are intrinsically

complementary. A suite of complementary spaceborne

sensors is needed to unravel the complex processes of

ocean-atmosphere interaction. Our study will demonstrate

that the value of flying the suite of sensors together continuously far outweighs the sum of the benefits of flying

individual sensors one at a time, the essence of EOS.

Spaceborne sensors, however, cannot probe the deep

ocean and, therefore, in situ measurements are also

needed. Ocean general circulation models (OGCM) have

the potential of providing the dynamic interpolation and

integration of these data. Our study will take advantage

of the historic opportunity created by the advance of computer technology and the maturity of ocean general circulation models to assimilate the variety of data available

during the EOS era.

Science Goals

The goal is to improve diagnosis and prognosis of global

changes through the understanding of the coupled oceanatmosphere system. The objectives are:

1) To improve existing, and to develop new, methodologies for estimating global ocean-atmosphere

fluxes in momentum, energy, water, and carbon dioxide;

2) To study the changes in the transport and storage of

heat, water, and greenhouse gases by the ocean in

response to surface forcing; and

3) To understand the energy and hydrologic balances

of the atmosphere and their relation to ocean surface

fluxes.

Current Activities

The strategy of our investigation evolves over time, but it

is be based largely on the synergistic and interdisciplinary approaches of applying satellite data, ground-based

measurements, and numerical models to our research. Our

current activities support our three objectives. We are

improving the bulk-parameterization method for estimating turbulent fluxes and deriving relevant parameters from

satellite observations. We are developing new methodologies for estimating hydrologic forcing using satellite

data. We are studying ocean-surface momentum balance

and wind-driven ocean circulation using Lagrangian drifters and wind-speed data obtained by scatterometer. We

are relating sea-level changes to both ocean dynamics and

storage of heat and water. We are studying how the cloud

forcing, convection, and surface heat flux are related to

sea-surface temperature changes, at intraseasonal, seasonal, and interannual time scales. We are examining the

relation between atmospheric water vapor and greenhouse

warming. We are studying the variability of tropical cyclones, monsoons, and El Niño that have strong economic

and environmental impacts.

Our modeling effort has focused in the improvement

of surface forcing and mixing parameterization in an

OGCM. Realistic surface forcing derived from satellite

data is being used to force the OGCM, and the model

responses are being compared with observations both from

spaceborne and ground-based sensors. We will learn to

interpret the differences in terms of specific physical processes and model weaknesses. Surface flux derived inversely by constraining the model with data will also be

examined. An eddy-resolving model in the North Atlantic with 1/6° spatial resolution has been successfully run.
252 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

We plan to extend our study to coupled ocean-atmosphere

models, and the incorporation of biology in the physical

model is being explored. Our efforts in satellite data application and ground-based measurements are described

below.

Use of Satellite Data

Our team has strong experience in estimating ocean surface forcing using satellite data. We are actively using

NSCAT and TOPEX/Poseidon data to study wind forcing and ocean dynamic response. We are currently using

SSM/I and AVHRR to estimate evaporation and latent

heat; ISCCP to compute solar irradiance; GPCP (Global

Precipitation Climatology Project) to provide rain. We are

using MLS and SSM/I to estimate upper tropospheric and

integrated water vapor and ERBE data to estimate greenhouse warming. In the near future, we will continue to

use operational data from AVHRR, TOVS, SSM/I, SSMT2

(humidity sounding), ISCCP, and GPCP; from

scatterometers and altimeters on ERS2; from SeaWiFs

(ocean productivity); from TRMM; from GLI and AMSR

on ADEOS-2. We are actively preparing for the increase

in accuracy and resolution of expected EOS sensors, such

as, SeaWinds, QuikSCAT, Jason-1, AMSR-E, AIRS

(HSB), MODIS, and CERES at the turn of the century.

Participation in Field Campaigns

Our team members have participated in the design of in

situ monitoring programs and the execution of field campaigns for the Tropical Ocean Global Atmosphere

(TOGA) Program and the World Ocean Circulation Experiment (WOCE). We shall continue in the analysis of

data from experiments, such as TOGA-COARE (Coupled

Ocean Atmosphere Response Experiment) and are actively

planning and will participate in new programs, such as,

the Global Drifter Program and the Atlantic Climate

Change Experiment.

Principal Investigator

W. Timothy Liu

W. Timothy Liu holds M.S. and Ph.D. degrees in Atmospheric Sciences from the University of Washington. He

has been a Principal Investigator on studies concerning

air-sea interaction and satellite oceanography since he

joined JPL in 1979. He is currently a Senior Research

Scientist, the leader of the Air-sea Interaction and Climate Team, and the NSCAT/QuikSCAT Project Scientist. He received the NASA Medal for Exceptional Scientific Achievement for his pioneering work in ocean surface heat flux, a NASA Group Achievement Award for

TOPEX, and a number of NASA Certificates of Recognition. Liu was selected as a member of the science investigator teams of NSCAT, TOPEX/Poseidon, TRMM,

and ERS Projects. He has served on the Earth Science

and Applications Division Advisory Subcommittee and

various science working groups of NASA. He has also

served on numerous science working groups and advisory panels of the World Climate Research Program and

editorial boards of scientific journals.

Co-Investigators

Catherine Gautier - University of California at Santa Barbara

William Holland - National Center for Atmospheric Research

Paola Malanotte-Rizzoli - Massachussetts Institute of

Technology

Pearn P. Niiler - Scripps Institute of Oceanography

The following are from the Jet Propulsion Laboratory:

Lee-Leung Fu

Ichiro Fukumori

William Patzert

Wenqing Tang

Victor Zlotnicki

References

Baturin, N.G., and P.P. Niiler, 1997: Effects of instability

waves in the mixed layer of the equatorial Pacific. J.

Geophys. Res., 102, 27,771-27,794.

Gautier, C., P. Peterson, and C. Jones, 1996: Global estimation of freshwater fluxes and oceanic transport from

satellite data. World Resources Review, 8, 505-514.

Liu, W.T., A. Zheng, and J. Bishop, 1994: Evaporation

and solar irradiance as regulators of the seasonal and interannual variabilities of sea surface temperature. J.

Geophys. Res., 99, 12,623-12,637.

Liu, W.T., W. Tang, and R. Atlas, 1996: Responses of the

tropical Pacific to wind forcing as observed by spaceborne

sensors and simulated by model. J. Geophys. Res., 101,

16,345-16,359.

Liu, W.T. and W. Tang, 1997: The spaceborne

scatterometer in studies of atmospheric and oceanic phenomena from synoptic to interannual time scales. Space

Remote Sensing of Subtropical Oceans. 113-126, C.T. Liu

(ed.), Pergamon, New York.

Moison, J.R., and P.P. Niiler, 1998: The seasonal heat budget of the North Pacific: Net heat flux and heat storage

rates (1950-1990). J. Phys. Oceanogr., 28, 401-421.

Investigation URL

http://airsea-www.jpl.nasa.gov/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 253

Spatial and Temporal Variability of Soil

Moisture and Its Relation to Water and Energy

Balances in a Monsoon Region

 Principal Investigator – Yongqiang Liu

Science Background

Soil moisture is an extremely important factor for the continental-scale water and energy balances through its roles

in providing available water for evapotranspiration and

in determining the partition of radiative energy absorbed

on the land surface into sensible and latent-heat fluxes.

Our understanding of these balances is mostly based on

numerical simulations, but is limited due to lack of soilmoisture measurements. Although models are powerful

tools to investigate the various processes involved in the

water and energy balances, observations are necessary for

evaluating the performance of land-surface

parameterizations and land-atmosphere coupled climate

models, and for providing initial conditions to such models. Therefore, using a combination of soil-moisture observations and numerical modeling seems the most appropriate method to study the variability of soil moisture,

and water and energy balances. In fact, a great effort is

being made as part of the Global Energy and Water cycle

Experiment (GEWEX) Continental-Scale International

Project (GCIP) to collect in situ and remotely sensed observations of soil moisture, as well as develop and apply

mesoscale models in the Mississippi River Basin.

To provide a more-global view of the water and energy budgets, this investigation expands GCIP to a monsoon region (East China) by using soil-moisture observations in that region as well as a regional climate model.

This study is expected to provide useful insights on the

spatial and temporal variability of soil moisture and its

role in the water and energy balances of this monsoon

region. Using studies performed in the GCIP region, we

will be able to provide a comparison between these two

regions.

Science Goals

The objectives of this investigation are: 1) to identify the

major scales and patterns in spatial and temporal variability presented in soil-moisture observations by using

various analysis techniques, as well as possible relations

between these scales and patterns, and between soil moisture and other land-atmosphere variables; 2) to simulate

soil moisture and other land-atmosphere hydrological and

energy components with the NCAR Regional Climate

Model version 2 (RegCM2), and to analyze water and

energy budgets; and 3) to conduct a number of experiments with RegCM2 to investigate the impacts of soilmoisture variability on the water and energy balances,

and to provide simulation evidence and physical interpretation of possible relations between the scales and patterns of soil moisture and other land-atmosphere variables

obtained from the observation study. The observation and

simulation analyses will focus on differences of soil-moisture variability, and the water and energy budgets during

various stages of development of monsoons, and differences during normal, anomalously strong, and anomalously weak monsoon events.

Current Activities

A complete data set of soil moisture is needed to achieve

the objectives of this investigation. We are currently in

the process of building up such a data set, which consists

of soil-moisture observations and corresponding atmospheric observations at over 500 sites in China during the

past decade. This is done in cooperation with Chinese

colleagues. Part of this data set is being used to analyze

the persistence of soil moisture and its role in land-atmosphere variability. It is also used to evaluate the performance of the Biosphere-Atmosphere Transfer Scheme

(BATS), which will be adopted for our simulations.

We are planning to perform our numerical simulations with RegCM2. However, the climate version of the

Regional Atmosphere Modeling System (ClimRAMS) developed at the Colorado State University is also available

to us for this study. Because this model presents some

unique features, we are also conducting test simulations

with it to evaluate which one is most appropriate for our

needs.

Use of Satellite Data

The appropriate specification of land types should considerably improve our simulations of land-surface processes. In RegCM2, the only land types available for the

region of interest are natural vegetation (mainly conifer-
254 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

ous and deciduous forest). However, forest covers less

than 20% of that region, and agriculture is a significant

part of the landscape. Furthermore, both forest and agriculture crops have significant annual cycles. We will use

the EOS satellite observations to better specify land cover

and its annual cycle.

Principal Investigator

Yongqiang Liu

Yongqiang Liu received a Ph.D. in Atmospheric Dynamics from the Institute of Atmospheric Physics, Chinese

Academy of Sciences, in 1990. He was a visiting scientist at NCAR during 1992-1993, and a faculty member at

Rutgers University during 1995-1998. He is currently a

Senior Research Scientist at Georgia Institute of Technology. His research areas include land-atmosphere interactions, regional climate modeling, and parameterization of precipitation induced by land-surface heterogeneity. He received the Youth Research Award of the National Committee of the Natural Science Foundation of

China (1991-1993) and the Science and Technology

Achievement Award of the National Meteorological Administration of China (1994). He served as an editor for

“Climate Research Newsletter of China” during 1993-

1994.

Co-Investigator

Roni Avissar - Rutgers University

References

Liu, Y.-Q., and R. Avissar, 1999: A study of persistence in

the land-atmosphere system with a general circulation

model and observations. J. Climate, in press.

Liu, Y.-Q., and R. Avissar, 1999: A study of persistence in

the land-atmosphere system with a fourth-order analytical model. J. Climate, in press.

Investigation URL

http://www.envsci.rutgers.edu

One month-lag autocorrelation coefficients in China, indicating the strongest persistance in soil moisture, and in increasing

tendency in persistance from moist to dry climate regimes.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 255

Interannual Variability of Ocean Color: A

Synthesis of Satellite Data and Models and

Participation in the Ocean Carbon Cycle

Model Intercomparison

Principal Investigator – John C. Marshall

Scientific Background

1) Interannual variability of ocean color in the North Atlantic – In situ-time series observations of biogeochemical properties of the surface ocean, such as chlorophyll

and zooplankton concentrations, have been shown to vary

significantly on interannual and decadal timescales. Correlations with indicators of regional climate change, such

as the NAO index, have also been found suggesting large

scale structure to the variability. The ongoing remote ocean

observation program (SeaWiFS, MODIS, TOPEX/

Poseidon) will provide a database with which to examine

the relationships which link physical and biological variability in the ocean. Understanding these relationships will

provide insight into the nature of biogeochemical responses and feedbacks to climate change.

We are studying these relationships using ocean circulation models which are driven by observed winds and

heat fluxes, and constrained to be consistent with remotely

sensed altimetry, coupled with ecological models. Initial

modeling studies have demonstrated that winter-time nutrient supply to the surface ocean is modulated largely by

changes in convective mixing, and hence linked to surface meteorogical forcing. A coupled ecological model,

however, shows that interannual changes in chlorophyll

concentration does not directly reflect nutrient supply, but

has a more complex, regionally varying response to

anomalous mixing. This regional dependence is captured

in a simple analytical model which is shown to be consistent with CZCS and in situ observations of chlorophyll

time-series.

2) Participation in the Ocean Carbon Cycle Model

Intercomparison – Marshall and Follows are also participants, using the MIT ocean model, in the Ocean Carbon

Model Intercomparison Project (OCMIP), details of

which can be found in the OCMIP group entry (see under

Najjar).

Principal Investigator

John C. Marshall

John Marshall is a Professor in the Department of Earth,

Atmospheric and Planetary Sciences at MIT. His research

is directed at the understanding of key components of the

general circulation of the atmosphere and oceans, and the

role of ocean circulation on global biogeochemical cycles.

A key component of this work is the development of high

performance oceanic and atmospheric models. These

models are used to study fluid mechanical problems, ranging from rotating convection to the global circulation; and

biogeochemical cycles, ranging from interannual variability of the North Atlantic to the oxygenation of the

Panthalassic ocean in the late Permian.

Co-Investigators

Mick Follows - Massachusetts Institute of Technology

Watson Gregg - NASA/Goddard Space Flight Center

References

Follows, M.J., R.G. Williams, and J.C. Marshall, 1996:

The solubility pump of carbon in the subtropical gyre of

the North Atlantic. J. Marine Res., 54, 605-630.

Marshall, J.C., A.J.G. Nurser, and R.G. Williams, 1993:

Inferring the subduction rate and period over the North

Atlantic. J. Phys. Oceanog., 23, 1315-1329.

Marshall, J.C., C. Hill, L. Perelman, and A. Adcroft,

1997a: Hydrostatic, quasi-hydrostatic, and nonhydrostatic

ocean modeling. J. Geophys. Res., 102(C3), 5733-5752

Marshall, J., A. Adcroft, C. Hill, L. Perelman, and C.

Heisey, 1997b: A finite-volume, incompressible Navier

Stokes model for studies of the ocean on parallel computers. J. Geophysical Res., 102(C3), 5753-5766.

Williams R.G., and M.J. Follows, 1998: Estimating new

production over the North Atlantic due to the climatological Ekman supply of nutrients. Deep-Sea Res., 45,

461-489.

Williams R.G., and M.J. Follows, 1998: Eddies make

ocean deserts bloom. Nature, 394, 228-229.
256 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Physical-Biological Interactions in the Tropical

Pacific & Atlantic Equatorial Surface Layers

 Principal Investigator – Charles R. McClain

Science Background

The tropical ocean plays a major role in both global-scale

physical (oceanographic and meteorological) and biological processes. Much of the global meridional heat transport to northern latitudes is oceanic transport from the

tropics. Programs such as TOGA (Tropical Ocean/Global Atmosphere) have been conducted to understand better the influence of the tropical Pacific on weather and

climate, although many processes and interactions remain

unresolved. Progress in understanding ENSO (El NiñoSouthern Oscillation) has helped define the future directions of the World Climate Research Programme, the U.S.

Global Change Research Program and the NASA Earth

Science program with seasonal-to-interannual climate

variability being a top priority. Biologically, the equatorial ocean is: a) the site of much of the world ocean primary productivity, i.e. the creation of organic matter

through plant photosynthesis, b) a primary source of CO2

flux to the atmosphere and c) a major commercial fishing

ground. Consequently, the eastern tropical Pacific was the

site for the Joint Global Ocean Flux Study (JGOFS) EqPac

program in 1992 to investigate carbon cycling and transport. Physical and biological processes are linked. The

vertical flux of subsurface nutrients into the surface euphotic zone controls ocean primary production. On the

other hand, light attenuation by marine phytoplankton

modulates the flux of visible light absorbed in the surface

mixed layer and, therefore, may have significant feedbacks on sea surface temperature and air-sea heat flux.

Science Goals

The research program focuses on three general topics of

investigation:

1) Interactions between physical & biological processes

in tropical Pacific and Atlantic Oceans. The primary

emphasis will be to perform empirical and diagnostic studies using various basin-scale meteorological,

altimetric, SST, and in situ data for time-space correlation analyses with the surface photosynthetic pigment fields.

2) Coupled physical-ecological models for predictive

and diagnostic studies. The models will be used to

provide a more-complete interpretation of the observed fields and correlations identified in Objective

1). The models will also be used to conduct sensitivity studies on the effects of spatial (horizontal and

vertical) and temporal variability in light absorption

on heat fluxes, mixed-layer depth, and circulation.

Also, the ecosystem models currently under development include iron-uptake kinetics and competition

between phytoplankton and zooplankton groups so

as to address the effects of temporal variability in

nutrient (micro- and macronutrients) supply on ecosystem structure and productivity.

3) Data-assimilation techniques for model prediction

skill and ecosystem parameter estimation. Given that

the various ecosystem processes, e.g., phytoplankton growth rate, are time dependent and vary as a

function of light and nutrient history, data-assimilation methods may provide improved estimation of

these quantities better than current parameterization

schemes (including simple constant value assumptions).

Current Activities

Work has proceeded along five lines of investigation, as

itemized below. Most of the work to date has been in development of 3-D tropical ocean circulation models, 1-D

coupled physical-biological ecosystem models, 1-D biological data assimilation schemes, and the analysis of historical tropical-ocean data sets.

Historical Studies – These studies have primarily evolved

around the Coastal Zone Color Scanner (CZCS) data from

the tropical Pacific and Atlantic. The Pacific study focused on interannual variability and the impact of the

1982-1983 El Niño on pigment (biomass) concentrations

and showed the strong correlation between sea level and

surface pigment concentrations. The Atlantic study looked

at the pronounced seasonal variation in pigment concentrations in the Gulf of Guinea and suggested that secondary circulation cells associated with the complex equatorial flow patterns prolong the bloom for several months

after the cessation of summertime equatorial upwelling.

Data Analysis – With the recent launch of SeaWiFS in

September 1997, global chlorophyll fields are routinely

available for the first time. These data along with basin-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 257

scale sea-surface temperature, TOPEX sea level, and TAO

(TOGA Atmosphere-Ocean) subsurface hydrographic data

are being analyzed as the tropical Pacific phases from the

1997-1998 El Niño to La Niña.

1-D Modeling – The development of ecosystem models

is critical to understanding the observed fluctuations in

phytoplankton concentrations, which occur in response

to changes in the physical environment. Ecosystem models, forced by physical models, have been developed and

tested at Ocean Weather Station P and both the eastern

equatorial Pacific “Cold Tongue” and the western Pacific

“Warm Pool.”

3-D Modeling – A 3-D circulation model for the tropics

has been developed which incorporates an ocean surface

mixed layer model and an atmospheric marine-boundarylayer model. The model also accommodates precipitation

and evaporation effects on salinity and density, which are

critical processes in regions like the Warm Pool. An ecosystem model is presently being integrated into this circulation model.

Data Assimilation – In parallel with the general circulation and ecosystem-model development activities, methodologies for assimilating satellite estimates of phytoplankton, i.e., chlorophyll-a, concentrations into 1-D

models are being examined. Once the coupled 3-D model

is completed, the assimilation studies will utilize it.

Use of Satellite Data

Satellite data will be used extensively as many of the primary physical and biological quantities of interest can be

derived from remote-sensing data. Only satellite sources

can provide data on the space and time scales required

for this investigation. In particular, ocean chlorophyll-a

estimates from SeaWiFS, the ADEOS-I/OCTS, and MODIS will be used in conjunction with SST products derived from the NOAA AVHRR and sea-level variability

fields from TOPEX. Cloud-cover data, such as products

from ISCCP, are used for computing surface irradiance

which is required for estimation of phytoplankton growth

rates and radiative heat fluxes.

Participation in Field Studies

For the past several years, as part of the international

JGOFS program, Marlon Lewis and Ichio Asanuma have

been conducting annual hydrographic surveys of the central and western equatorial Pacific. The data collection

includes surface-layer temperature, salinity, nutrients, primary production, chlorophyll-a, and spectral irradiance.

Mike McPhaden manages the TAO buoy array in the equatorial Pacific.

Principal Investigator

Charles R. McClain

Chuck McClain received a B.A. degree in 1970 from

William Jewell College in Liberty, MO., with a major in

physics and a minor in mathematics and a Ph.D. in marine sciences from North Carolina State University in

1976. He worked for two years as a National Research

Council postdoctoral associate at the Naval Research

Laboratory (NRL) in Washington, D.C. where he used

airborne laser profilometry to validate GEOS-III altimeter estimates of surface wave heights. He has worked at

NASA/Goddard Space Flight Center since 1978. Since

joining the research staff at NASA/GSFC, his research

has focused on the utilization of satellite ocean-color observations and numerical models to study the interactions

between physical and biological processes in the oceans.

He is presently serving as the SeaWiFS (Sea-viewing Wide

Field of View Sensor) Calibration and Validation Manager, Project Scientist, and Project Manager. He also

serves as the Project Manager of the SIMBIOS (Sensor

Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies) Project, which is co-located

with the SeaWiFS Project.

Co-Investigators

Eileen Hofmann - Old Dominion University

Marlon Lewis - Dalhousie University

Ragu Murtugudde - University of Maryland

Antonio Busalacchi - NASA/Goddard Space Flight

Center

Chester Koblinsky - NASA/Goddard Space Flight

Center

Michael McPhaden - NOAA/Pacific Marine Environmental Laboratory

Ichio Asanuma - Japan Marine Science and Technology

Center

References

Kessler, W.S., and M. J. McPhaden, 1995: The 1991-1993

El Niño in the central Pacific. Deep Sea Res., 42, 295-

333, .

Lawson, L. M., E. E. Hofmann, and Y. H. Spitz, 1996: A

Data assimilation technique applied to a marine ecosystem model. Deep Sea Res., 43, 625-651.

Leonard, C. L., and C. R. McClain, 1996: Assessment of

interannual variation (1979-1986) in pigment concentrations in the tropical Pacific. Int. J. Remote Sens., 17(4),

721-732.
258 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Lewis, M.R., M.-E. Carr, G.C. Feldman, W.E. Esaias, and

C.R. McClain, 1990: Satellite estimates of the influence

of penetrating solar radiation on the heat budget of the

equatorial Pacific Ocean. Nature, 347, 543-545.

Monger, B., C.R. McClain, and R. Murtugudde, 1997:

Seasonal phytoplankton dynamics in the eastern tropical

Atlantic. J. Geophys. Res., 102, 12,389-12,411.

McClain, C.R., A.R. Arrigo, K.S. Tai, and D. Turk, 1996:

Observations and simulations of physical and biological

processes at OWS P, 1951-1980. J. Geophys. Res., 101,

3697-3713.

Murtugudde, R.G., R. Seager, and A. Busalacchi, 1996:

Simulations of tropical oceans with an ocean GCM

coupled to an atmospheric mixed layer model. J. Climate,

9, 1795-1815.

SeaWifs surface chlorophyll concentration (mg/m3) for the Indo-Pacific region. Note the low values of Chl-a in the equatorial Pacific

during El Nino (November ‘97), and the extensive Chl-a bloom during La Nina (June ‘98). The large bloom in the eastern equatorial

Indian Ocean during November 1997 was caused by extremely anomalous winds. The 0.1 mg/m3 contour is superimposed for clarity.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 259

Modeling Mesoscale Biogeochemical

Processes in a TOPEX/Poseidon Diamond

Surrounding the U.S. JGOFS Bermuda Atlantic

Time-series Study

Principal Investigator – Dennis McGillicuddy

Science Goal

The overall goal of the proposed research is to investigate the role of mesoscale dynamics and upper-ocean processes on biogeochemical fluxes in the Sargasso Sea. The

general approach is to use a three-dimensional coupled

physical and biological model together with in situ observations and a full complement of remotely sensed information (altimetry, ocean color, scatterometry, and

AVHRR) to study the biological and chemical ramifications of spatially and temporally intermittent physical

processes. The coupled model system will be configured

in a “TOPEX/Poseidon (T/P) Diamond” surrounding the

U.S. JGOFS Bermuda Atlantic Time Series Study (BATS)

site. This implementation will make it possible to prescribe the necessary physical model boundary conditions

directly from T/P altimetry. Assimilation of additional data

available in the interior (from moorings, BATS hydrography, and ERS altimetry) will facilitate the construction

of optimal estimates of the three-dimensional structure

of the water column as it evolves. These space-time continuous representations of oceanic fields will constitute a

novel basis for interpretation of SeaWiFS and OCTS imagery by providing the ability to analyze ocean-color

variations in the context of the underlying circulation patterns.

A nitrogen-based planktonic ecosystem model, which

has been incorporated into the circulation model, will serve

as a vehicle for the analysis of the biogeochemical response to physical forcing. The specific process of interest here is the role of mesoscale eddies in nutrient supply

to the upper ocean. Recent modeling studies

(McGillicuddy et al. 1995; McGillicuddy and Robinson

1997) indicate substantial nutrient flux associated with

the formation of cyclonic eddies and subsequent intensification caused by interaction with adjacent features.

Long-term simulations in the Sargasso Sea based on statistically realistic mesoscale flow fields suggest that this

eddy-upwelling mechanism is the dominant mode of nutrient transport in the annual budget for the region. Datadriven coupled physical-biological simulations of the type

proposed here will be used to test this hypothesis and thus

should help to reconcile the longstanding controversy

concerning nutrient supply in the oligotrophic waters of

the open ocean.

In addition, these hindcast simulations will be used

to conduct a retrospective analysis of the BATS data to

help differentiate between spatial and temporal variability in the time-series record. The possibility of using this

interdisciplinary-model system in a nowcast/forecast

mode to contribute to optimal resource deployment in

future observational activities will be evaluated.

Principal Investigator

Dennis J. McGillicuddy Jr.

Dennis McGillicuddy Jr. earned both his M.S. degree in

Applied Physics in 1989 and his Ph.D. in Earth and Planetary Sciences in 1993 from Harvard University. His research interests include physical-biological interactions;

influences of circulation dynamics on planktonic ecosystems; mesoscale ocean dynamics; interaction of the near

surface and deep ocean; numerical modeling; and data

assimilation.

References

McGillicuddy, D.J., A.R. Robinson, and J.J. McCarthy,

1995: Coupled physical and biological modeling of the

spring bloom in the North Atlantic: II. Three dimensional

bloom and post-bloom processes. Deep Sea Res., 42,

1359-1398.

McGillicuddy, D.J., and A.R. Robinson, 1997: Eddy-induced nutrient supply and new production in the Sargasso

Sea. Deep Sea Res., 44, 1427-1450.

McGillicuddy, D.J., A.R. Robinson, D.A. Siegel, H.W.

Jannasch, R. Johnson, T.D. Dickey, J. McNeil, A.F.

Michaels, and A.H. Knap, 1998: Influence of mesoscale

eddies on new production in the Sargasso Sea. Nature,

accepted.
260 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Analysis of the Effect of Changing Climate

Variability on Crop Production in the

Southeastern United States: An Integration of

Stochastic Modeling, Regional Climate

Modeling, Crop Modeling, and Remote

Sensing Techniques

Principal Investigator – Linda O. Mearns

Science Background

New concerns have emerged regarding possible impacts

of climate perturbations on agricultural resources. One

such concern is the role of changing climatic variability

effects on crops, in addition to changes in mean climate

states. Failure to account for variability change (on dailyto-interannual time scales) effects on resource systems

was recognized as a serious limitation for studies conducted for the EPA Report on Potential Effects of Climate Change on the United States. More recently, the research needed to determine possible effects of changes in

variability, was highlighted in the IPCC 1995 Working

Group II Report.

In the past few years there has also been an intense

flurry of activity regarding seasonal forecasts of El Niño/

Southern Oscillation (ENSO) and the value of such forecasts to various economic sectors, especially agriculture.

This heightened interest resulted both from clearer evidence of robust relationships between ENSO events and

agricultural production (e.g., Cane et al. 1994) and improvements in climate/forecast models leading to better

forecasts of ENSO events (e.g., Chen et al. 1995). The

most-recent El Niño episode, the duration of which caused

some alarm in climate and impacts communities, lasted

more than four years, and some scientists suggested that

its duration could well be related to global warming

(Trenberth and Hoar 1996). This last suggestion indicates

that changes in the frequency and intensity of ENSO-type

events that strongly influence interannual variability of

climate are likely in a future greenhouse-gas-warmed climate. While the immediate attraction of seasonal forecasting of climate is obvious from, for example, a famine

early-warning point of view, it should also be recognized

that the constellation of new research in climate modeling and in impacts assessment provides a fertile area for

new research in longer term climate change, i.e., the consideration of changes in the statistical characteristics of

events that strongly influence interannual climate variability, and how these changes could affect agricultural

production.

Our project is an interdisciplinary investigation that

concerns development of plausible scenarios for regional

climate for application to improved assessments of the

potential impacts of climate variability on U.S. agricultural production and world production.

We propose to conduct a multifaceted study in the

Southeastern U.S. that will combine stochastic modeling

of interannual climate variability, high-resolution regional

climate modeling, application of crop models, and application of remote-sensing techniques, to examine the potential effects of changes in interannual climatic variability on crop production. This work will build on a regional

modeling study that is currently underway at NCAR

whereby high-resolution (50 km) control and doubled runs

will be produced (Giorgi et al. 1993a,b; Giorgi et al. 1994).

In this proposal we plan to use these runs as a baseline

climate scenario and apply them to crop models (i.e., the

CERES and CROPGRO family of models).

Two types of scenarios will be developed from these

model runs: one including only mean changes in the relevant climate variables and another including both mean

and daily variability changes (Mearns et al. 1996, 1997).

Since the regional-climate-model scenario will be developed by nesting it in a general circulation model (GCM)

with only a mixed-layer ocean, the changes in variability

predicted by the climate model will be “incomplete” in

that major changes in interannual variability resulting from

alterations in three-dimensional ocean dynamics and heat

exchange will not be modeled. We will, however, construct guided sensitivity studies of changes in the frequency of ENSO and North Atlantic Oscillation (NAO)

events relevant to the region, through examination of both

indications of past changes in ENSO events and the most

recent results of coupled climate-model transient experiments. These changes will be stochastically simulated and

applied to the crop models.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 261

Science Goals

1) Further knowledge regarding possible effects of

changing climatic variability on regional crop production.

2) Clarify the relative importance of ENSO and NAO

events on crop yields in the southeast by stratifying

various measures of observed yields according to

ENSO- or NAO- related categories (e.g., El Niño,

La Niña, normal).

3) Further the use of remote sensing (particularly

AVHRR) for determination of crop characteristics and

conditions.

4) Improve crop-climate models by incorporating crop

response to excess moisture (flooding, water logging)

so the models can be more successfully used for studies of changes in interannual climatic variability.

5) In a pilot-study mode, investigate methods of deriving land-surface parameters for the Regional Climate

Model (RegCM2) from remotely sensed data using

NDVI values. The spatial and temporal dynamics of

land-surface parameters (e.g., surface roughness, albedo, and canopy conductance) would be obtained

directly from remotely sensed data rather than inferred indirectly from survey-based classification.

6) Apply crop models to a relatively high-resolutiongrid system of climate changes (in contrast to studies using a few isolated points to represent a region).

7) Compare the effects of different spatial resolutions

of climate change (nested regional climate compared

to driving GCM resolution) on determination of

changes in crop yield.

Current Activities

The regional climate-modeling runs have been completed,

and a climate-change scenario, for use in the crop models, has been formed. The scenario exhibits fairly large

decreases in precipitation in the late spring and summer,

which likely leads to negative effects on crops. We have

produced some preliminary runs with the CERES-wheat

model over the entire southeastern domain, using the climate-change scenario. Our first results indicate substantial (about 30%) decreases in simulated crop yields

throughout the region with the climate change from the

Regional Model. Next steps include producing simulated

yields from the scenario for all crops, and then repeating

the runs with adaptation and direct CO2 fertilization effects.

Six SPOT images for the 1998 soybean-cropping season

at Florence, South Carolina have been acquired, and NDVI

calculated from the images. We performed field sampling

of LAI for the soybean crop coincident with the SPOT

images. Relationships between NDVI and LAI are being

developed and will be used to validate crop-model runs

at this and other sites.

Biweekly maximum-value NDVI composite data

(from AVHRR) from 1989 through 1998 have been assembled and analyzed for the Southeast. These data were

analyzed according to vegetation-cover type within climate divisions. Six cover types were defined in the Southeast U.S. Average NDVI and associated statistics were

determined for the entire Southeast region, for the region

by cover type, for selected climate divisions and for each

division by cover type. Twenty-four climate divisions

within an expected climate signal (ENSO) as well as sites

outside the signal area were selected for detailed analysis. Analyses of the interannual variability of the NDVI

values for the selected climate divisions are being performed, and relations between NDVI and fluctuations in

both observed and simulated crop yields are being developed.

Some of these NDVI data will be used to validate

crop models (assuming relationships between NDVI and

LAI are successfully developed) and may be used to update the crop models during simulation runs.

Participation in Field Experiments

No participation in field experiments is currently planned.

Use of Satellite Data

We are incorporating the use of remote sensing in this

study in four ways: 1) verification of cropping regions

via SPOT and AVHRR data; 2) validation of the climate

model via SSM/I data, and 3) validation of certain elements of the crop models (such as LAI) to determine their

ability to correctly reproduce interannual variability; and

4) use of AVHRR data to further confirm the effect of El

Niño events on crops in the region, by comparing yearto-year values of NDVI that have been processed to represent specific crop characteristics such as LAI or, perhaps, economic yield.

Particularly extreme El Niño events (e.g., 1982-83)

will be examined in greater detail with AVHRR data to

determine if extreme crop responses can be determined

via remotely sensed data.
262 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Principal Investigator

Linda O. Mearns

Linda O. Mearns is a Scientist III in the Environmental

and Societal Impacts Group (ESIG) at the National Center for Atmospheric Research, Boulder, Colorado, and

leads an interdisciplinary research group within ESIG

focusing on applications of regional climate modeling

results to impact assessments. She holds a Ph.D. in Geography/Climatology from UCLA. She has performed

research and published in the areas of crop-climate interactions, climate-change-scenario formation, climatechange impacts on the agro-ecosystems, and analysis of

climate variability and extreme climate events in both

observations and climate models. She has most recently

published a series of articles on the effects of changes in

climate variability (in contrast to changes in mean climate) on simulated crop yields.

She has contributed to the IPCC Climate Change 1992

and 1995 Reports on the subject of climate variability in

general circulation models, the climatology of mountainous regions, and impacts of climate change on agriculture. She is a member of the IPCC Task Group on Scenarios for Climate Impact Assessment. She currently leads

a project funded by the EPA, NASA, and USDA, on the

effects of changes in climate variability on crop production in the Southeastern U. S.

Co-Investigators

Richard W. Katz - National Center for Atmospheric

Research

William Easterling - Pennsylvania State University

Gregory Carbone - University of South Carolina

D. Rundquist - University of Nebraska

E. Walter-Shea - University of Nebraska

References

Cane, M.A., G. Eshel, and R.W. Buckland, 1994: Forecasting Zimbabwean maize yield using eastern equatorial Pacific sea surface temperature. Nature, 370, 204-205.

Chen, D., S.E. Zebiak, A.J. Busalacchi, and M.A. Cane,

1995: An improved procedure for El Niño forecasting:

Implications for predictability. Science, 269, 1699-1702.

Giorgi, F., M.R. Marinucci, and G.T. Bates, 1993a: Development of a second generation regional climate model

(REGCM2). Part I: Boundary layer and radiative transfer

processes. Mon. Wea. Rev., 121, 2794-2813.

Giorgi, F., M.R. Marinucci, G. DeCanio, and G.T. Bates,

1993b: Development of a second generation regional climate model (REGCM2). Part II: Cumulus cloud and assimilation of lateral boundary conditions. Mon. Wea. Rev.,

121, 2814-2832.

Giorgi, F., C.S. Brodeur, and G.T. Bates, 1994: Regional

climate change scenarios over the United States produced

with a nested regional climate model. J. Climate, 7, 375-

399.

Mearns, L.O., C. Rosenzweig, and R. Goldberg, 1996:

The effect of changes in daily and interannual climatic

variability on CERES-Wheat: A sensitivity study. Climatic

Change, 32, 257-292.

Mearns, L.O., C. Rosenzweig, and R. Goldberg, 1997:

Mean and Variance Change in Climate Scenarios: Methods, Agricultural Applications, and Measures of Uncertainty. Climatic Change, 35, 367-396.

Trenberth, K., and T.J. Hoar, 1996: The 1990-1995 El

Niño-Southern Oscillation Event: Longest on record.

Geophys. Res. Letters, 23, 57-60.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 263

Observation and Modeling of Heat and Water

Fluxes Over Heterogeneous Land Surfaces at

Mesoscale

Principal Investigator – Massimo Menenti

Science Background

The performance of a Numerical Weather Prediction

(NWP) model is critically dependent on the initialization

and updating of the model state, of which both the model

forecast in the preceding period and the observations of

the atmosphere and of the land surfaces are most important. Hence the quality of the initial data and the dataassimilation procedure determine the prediction skill of

an NWP model. Because the data assimilation is nearly

continuous in time in an NWP model, the availability of

reliable global data becomes critical to update weather

forecasts.

Science Goals

Since it has been shown that initial soil-water content has

an important impact on the NWP model forecast, two strategies for assimilation of soil-moisture fields in an NWP

model can be considered: 1) to derive from the energy

balance at the land-atmosphere interface a measure of

water availability in the plant root zone; and 2) to estimate soil-water content in the surface layer using microwave observations. Earth Science Enterprise (ESE) data

provide excellent opportunities to carry out the above two

strategies. The aims of this investigation are to:

• evaluate the use of advanced imaging radiometers, to

obtain more-accurate estimates of surface albedo, spectral indices, and surface temperature;

• improve the accuracy of the energy partition at the land

surface;

• develop a procedure to obtain large-area soil-water content using microwave observations; and

• develop a procedure to assimilate time series of energy

balance and surface soil moisture into NWP models.

Current Activities

Within the Dutch national remote-sensing program, the

group has developed a new remote-sensing algorithm

Surface Energy Balance (SEBAL) to map heat fluxes for

heterogeneous land surfaces. It has also been shown that

the evaporative fraction (the ratio of latent heat to the difference between net radiation and soil heat flux) is a reliable indicator of soil-water availability. A set of tools has

been created for processing currently available remotesensing data (Landsat, NOAA/AVHRR, Meteosat) to derive the necessary inputs for SEBAL. Various approaches

have been developed for the estimation of surface moisture using microwave observations. A research version

NWP model Regional Atmospheric Climate MOdel

(RACMO) has been applied to North Africa and Europe.

RACMO includes a fully interactive land-surface-process

sub-model that describes heat and water transfer in the

root-zone soil using multi-layers and allows the assimilation of root-zone soil-water indicators and surface moisture.

Use of Satellite Data

EOS data products will be used to retrieve surface parameters to characterize various land-surface processes.

These parameters include surface albedo, vegetation spectral indices, surface emissivity, surface temperature,

roughness, and moisture. MODIS, ASTER, Landsat 7,

AMSU, MISR, and AMSR-E will be used to complement

currently available satellite sensors. These data will be

used to make atmospheric corrections in the optical, infrared, and thermal infrared in combination with synoptic weather information. Derivation of directional reflectance and temperature will also be investigated using these

data.

Participation in Field Programs

Members of this group have been involved in several past

and ongoing large field programs. These include: MONSOON, HAPEX-MOBILHY held in France in 1986, First

ECHIVAL Field Experiment in Desertification Threatened

Areas (EFEDA) held in central Spain in 1991 and 1994,

HAPEX-SAHEL held in Niger in 1992, Heihe basin Field

Experiment (HEIFE) during 1990 and 1995 in Northwest

China, Jornada Experiment (JORNEX) during 1995 and

1996 in Washita, New Mexico, 1992 and 1994, and
264 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

GEWEX ESE Southern Great Plains Hydrology Experiment (SGP’97). During the period 1997-1999 we plan to

participate in the TIPEX, IMGRASS and JORNEX activities.

Principal Investigator

Massimo Menenti

Massimo Menenti of the Winand Staring Centre in

Wageningen, The Netherlands, has been a member of the

1st Steering Committee of ISLSCP and spends regular

extended visits at the NASA/GSFC Hydrological Sciences

Branch and USDA/ARS Hydrology Laboratory. His research interest focuses on land-surface processes and regional hydrological processes. These range from studies

of heat balance in relation to groundwater evaporation to

integration of satellite observations with hydrological

models. High-spatial-and-vertical-resolution laser measurements were used to estimate aerodynamic roughness

and leaf-area index. The relation of climate variability to

large-area vegetation phenology was studied by using long

time series of satellite observations.

Co-Investigators

A. C. M. Belijaars - Weather Forecast, ECMWF

Henk A. R. De Bruin - Wageningen Agricultural

University

Dirk H. Hoekman - Wageningen Agricultural University

A. Holtslag - Royal Netherlands Meteorological Inst.

References

Menenti, M., J.C. Ritchie, and K.S. Humes, 1996: Estimation of aerodynamic roughness at various spatial scales.

Scaling Up in Hydrology Using Remote Sensing, J.B.

Stewart, et al., Eds., Wiley, Chichester, UK, 39-58.

Wang, J., Y. Ma, M. Menenti, and W.G.M. Bastiaanssen,

1995: The scaling-up of processes in the heterogeneous

landscape of HEIFE with the aid of satellite remote sensing. J. Meteor. Soc. Japan, 73, 1235-1244.

Bastiaanssen, W.G.M., M. Menenti, R.A. Feddes, and

A.A.M. Holtslag, 1997: A remote sensing surface energy

balance algorithm for land (SEBAL). Part 1: Formulation. J. Hydrology (special issue), in press.

Ritchie, J.C., M. Menenti, and M.A. Weltz, 1996: Measurements of land surface features using an airborne laser

altimeter: the HAPEX-Sahel experiment. Int. J. Remote

Sens., 17, 3705-3724.

Hurk, B.V.D., W.G.M. Bastiaanssen, H. Pelgrum, and E.V.

Meijgaard, 1997: A new methodology for assimilation of

initial soil moisture fields in weather prediction models

using Meteosat and NOAA data. J. Appl. Meteor., in press.

Z. Su, P.A. Troch, and F.P. De Troch, 1997: Remote sensing of bare soil moisture using EMAC/ESAR data. Int. J.

Remote Sens., 18, 2105-2124.

Investigation URL

http://www.sc.dlo.nl/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 265

Global Climate Impact on Regional HydroClimate and its Effect on Southeastern Asian

Agro-Ecosystems

Principal Investigator – Norman L. Miller

Science Background

The Regional Climate System Model (RCSM) has been

under development for several years. This system

downscales global climate data to the watershed catchment scale, and consists of data pre- and post-processors,

and four model components. The four model components

are: 1) a mesoscale atmospheric model, 2) a soil-plantsnow model, 3) a watershed-hydrology-riverflow model,

and 4) a crop-response model. The first three model components have been coupled, and the system includes twoway feedbacks between the plant-soil-snow model and

the mesoscale atmospheric model. This three-component

version of the RCSM has been tested, validated, and successfully used for operational quantitative precipitation

forecasts and seasonal water-resource studies over the

southwestern U.S.. Integration of the fourth component

(crop-response model) into the RCSM is part of our current research plan in collaboration with NASA and NCAR.

Science Goal

The goal of this research is to improve our current understanding of the relationships between global climate forcing, regional climate variation, and agro-ecosystem response. This investigation is based on numerical simulations using the RCSM with large-scale forcing from global analyses and the utilization of a variety of observational data including specific EOS data sets. This research

is concentrating on southeastern Asia (China, Japan, and

Korea), a rainfall- and-temperature-sensitive region representing over 20% of the world’s grain production and

population, and also the site of the GEWEX Asian Monsoon Experiments (GAME). The primary contribution is

to provide validated fine-resolution soil moisture and input for crop-yield simulations for this region. Past investigations of climate-change impacts on the world’s major

agro-ecosystems have relied on simulated GCM precipitation. However, it has been shown that large-scale precipitation fields do not reproduce precipitation and soil

moisture sufficiently. This leads to the extension of the

RCSM over specific regions with sub-daily to annual time

scales. Validation using reanalysis will provide for a

downscaling system to study regional impacts based on

large-scale climate projections.

Current Activities

We are systematically investigating the impacts of largescale variability on regional water resources and agriculture over the GAME region using the RCSM forced by

global reanalyses. Validation studies for southeastern Asia

(Kim et al. 1997) are being performed with good results.

A 17-year hindcast at 60-km resolution and monsoon

simulations at 20-km resolution are to be carried out during 1998. This mesoscale-modeling research is part of a

collaboration with the Korean Meteorological Research

Institute (METRI). The hydrological data collection and

modeling research is part of a collaboration with the Chinese Ministry of Water Resources and the Changwon

National University of Korea. Agriculture data and modeling is in collaboration with NASA and NCAR scientists. These efforts will contribute to both the GAME/

HUBEX (Huaihe Basin EXperiment) and KORMEX

(KORean Monsoon EXperiment) field campaigns.

Use of Satellite Data

We are using a variety of satellite-produced data sets including the 1o × 1o TOVS Pathfinder A data set to perform model validation and climatology studies. The main

data fields are precipitation, surface air temperature, skin

temperature, precipitable water, outgoing longwave radiation, and downwelling surface longwave radiation. Additionally, we are using the AVHRR-produced leaf-area

index and green-leaf fraction, as well as the NOAA 9, 11

GPCP data.

Participation in Field Activities

Participation in the HUBEX Intensive Observation Period (IOP): Travel to Korea during 1998 and work with

scientists from the Korean Meteorological Research Institute.

Participation in the KORMEX Intensive Observation Period (IOP): Travel to the Huaihe Basin during Spring 1998

and work with scientists from the Chinese Ministry of

Water Resources.
266 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Principal Investigator

Norman L. Miller

Norman L. Miller received his Ph. D. in Meteorology from

the University of Wisconsin in 1987, He is currently a

Hydrometeorologist at the University of California-LBNL

and is principally involved in Regional Climate System

Model management and development. This entails numerical-code development and sensitivity analyses for hydrological and biophysiological phenomena at a range of

temporal and spatial scales. Special focus is on atmospheric-hydrologic coupling and feedbacks, hydrologic

model calibration and verification, and land-surface characterization.

Co-Investigator

Jinwon Kim - University of California

References

Kim, J., N.L. Miller, J-H.Oh, J. Chung, and D-K. Rha,

1998: Eastern Asian hydrometeorology simulation using

the Regional Climate System Model. Global and Planetary Change, 19, 225-240.

Kim, J., 1997: Precipitation and snow budget over the

southwestern United States during the 1994-1995 winter

season. Water Resour. Res., in press.

Kim, J., Miller, N., K.P. Georgakakos, and A.K. Guetter,

1998: River flow response to precipitation and snow budget in California during the 1994-1995 winter. J. Climate,

11, 2378-2386.

Kim, J., N.L. Miller, J.-H. Oh, and J. Chung, 1997: A

simulation of precipitation and land-surface water budgets over East Asia using the UC Regional Climate System Model. The Third International Study Conference on

GEWEX in Asia and GAME, 26-28 March 1997, Cheju,

Korea.

Kim J., and N.L. Miller, 1996: Application of a coupled

atmosphere river flow model to a regional water resources

study. Second International Science Conference on global energy and water cycle, 17-21 June 1996, Washington, DC.

Kim, J., and S-T Soong, 1996: A simulation of a precipitation event in the western U.S. Regional Impacts of Climate Change, S. Ghan, W. Pennel, K. Peterson, E. Rykiel,

M. Scott, and L. Vail, Eds., Battelle Press.

Kim, J., and M. Ek, 1995: A simulation of the surface

energy budget and soil water content over the Hydrologic

Atmospheric Pilot Experiments-MOBILHY forest site. J.

Geophys. Res., 100, 20,845-20,854.

Miller, N.L., 1997: Coupling global climate models to

regional hydrometeorologic models, In Minutes of the

Twelfth Mission to Planet Earth/Earth Observing System

(MTPE/EOS) Investigators Working Group Meeting. The

Earth Observer, March/April, 9, No. 2, 15.

Miller, N.L., and J. Kim, 1997: The UC-LLNL Regional

Climate System Model (RCSM). Mission Earth: Modeling and Simulation for a sustainable Global System. Ed.

M.G. Clymer and C.R. Mechoso, Eds.

Miller, N. L., J. Kim, and J. Duan, 1997: The UC-LLNL

Regional Climate System Model: Southwestern United

States and Eastern Asia Studies. Research Activities in

Atmospheric and Oceanic Modelling. CAS/JSC Working Group on Numerical Experimentation. WMO/ICSU/

IOC World Climate Research Programme Report 25. A.

Staniforth, Ed.

Miller, N.L., J. Kim, J-S Chung, J-H. Oh, and B-H Bae,

1997: East Asian hydroclimate and agro-ecosystem research using the Regional Climate System Model. The

Third International Study Conference on GEWEX in Asia

and GAME, 26-28 March 1997, Cheju, Korea.

Miller, N.L., and J. Kim, 1996: Numerical prediction of

precipitation and riverflow over the Russian River watershed during the January 1995 California storms. Bull.

Amer. Meteor. Soc., 77, 101-105.

Investigation URL

http://ccs.lbl.gov/RCSM
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 267

Changes in Global Biogeochemical Cycles

Principal Investigator – Berrien Moore

Science Background

This Inderdisciplinary Science investigation addresses the

primary biogeochemical cycles of planet Earth.

Initial efforts focus on the cycles of water, carbon,

nitrogen, and selected trace gases. Process-based models

are developed as modules, in concert with database management techniques which synthesize the in-situ and remote sensing data needed to characterize regional and

global scales. Ecosystem, hydrologic, and biogeochemical modules will ultimately be coupled interactively to

atmospheric chemistry and transport modules. The results

of this investigation have supported the priority research

needs of the Intergovernmental Panel on Climate Change

(IPCC) and other regional and global integrated assessment activities, including the U.S. National Assessment.

Models of the Earth’s biogeochemical cycles are a

central theme. They provide a rigorous means for developing quantitative projections of the interactions of atmospheric composition, climate, terrestrial and aquatic

ecosystems, ocean circulation, and the effects of human

activities. The family of models being developed in this

investigation will provide the predictive link between the

physical and biological Earth system and the human dimensions of global change.

Goal and Objectives

The long-term goal of our IDS research is to understand

the primary biogeochemical cycles of the planet, the nature of the coupling between the Biogeochemical Subsystem and the Physical-Climate Subsystem, and the characteristics of the human forcing of the Biogeochemical

Subsystem, including the hydrological cycle. Our strategy is to study how element cycles function in natural

systems where perturbations in biogeochemical states are

driven primarily by climate variability and in systems

where disturbance gradients induced by human activity

have modified significantly exchanges of water, carbon,

nitrogen, or sulfur.

To execute this strategy, we have been developing

regional and global, geographically-specific, mathematical models and databases. These describe ecosystem distribution and condition, the biological processes that determine the exchange of CO2 and trace gases with the

atmosphere, and the fluxes of carbon and nutrients to

aquatic ecosystems. This suite of models rests within interactive information systems that integrate geographic

information systems, remote-sensing systems, database

management systems, graphics packages, and model interface shells. A macro Information Management System

is being developed to “wrap” the specific subsystem information management systems.

Five science Objectives form the basis for our IDS research.

• To describe the global pattern and distribution of terrestrial ecosystems and to describe the geographical and

temporal forcing agents of anthropogenic disturbance,

particularly deforestation.

• To describe globally, for terrestrial ecosystems, key biological processes such as net primary production, heterotrophic respiration, transpiration, nutrient uptake,

carbon allocation, and leaching, which bear upon global biogeochemical cycles.

• To determine the baseline and changing fluxes of water, carbon, nitrogen, and phosphorus from terrestrial

biomes to the world’s oceans.

• To determine the spatial and temporal patterns of the

fluxes in CO2, CH4, CO, N2O, NH3, reduced sulfur

gases, and the nonmethane hydrocarbons between terrestrial biomes and the atmosphere, and between aquatic

systems and the atmosphere.

• To develop the background trace-gas-release data associated directly with human industrial and urban activities.

Principal Investigator

Berrien Moore

Berrien Moore earned a Ph.D. in Mathematics from the

University of Virginia in 1969. He is best known internationally for his computer modeling of the global carbon

cycle. Professor Moore’s specific research interests include the application of geographic information systems
268 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

and remote sensing in modeling ecosystem dynamics globally, and the use of inverse calculations to develop ocean

models for use in carbon-cycle investigations. He is wellpublished in ecosystems literature and in studies of the

role of the ocean in the carbon cycle. He is involved in

numerous related studies for NASA, the National Science

Foundation, and the Environmental Protection Agency.

Professor Moore is Director of the Institute for the Study

of Earth, Oceans, and Space at the University of New

Hampshire.

Co-Investigators

William Emanual - University of Virginia

Robert Harris - NASA/Langley Research Center

Jerry M. Melillo - Marine Biological Laboratory

Bruce Peterson - Marine Biological Laboratory

The following are from the University of New Hampshire:

John Aber

Steve Froking

Barrett N. Rock

Chang Sheng Li

David Skole

Charles Vorosmarty

References

Aber, J.D., B.L. Bolster, S. Newman, M. Soulia, and M.E.

Martin, 1994: Testing the utility of end-member analysis

in the measurement of carbon fraction and nitrogen content of forest foliage. J. Near Infrared Spectroscopy, 2,

15-24.

Melillo, J.M., A.D. McGuire, D.W. Kicklighter, B. Moore,

C.J. Vorosmarty, and A.L. Schloss, 1993: Global climate

change and terrestrial primary production. Nature, 363,

234-240.

Moore, B., and B.H. Braswell, 1994: The lifetime of excess atmospheric carbon dioxide. Global Biogeochem.

Cycles, 8, 23-28.

Skole, D.L., and C.J. Tucker, 1993: Tropical deforestation, fragmented habitat, and adversly affected habitat in

the Brazilian Amazon: 1978-1988. Science, 260, 1905-

1910.

Vorosmarty, C.J., B. Moore, A.L.Grace, M.P. Gildea, J.M.

Melillo, B.J. Peterson, E.B. Rastetter, and P.A. Steudler,

1989: Continental-scale models of water balance and fluvial transport: An application to South America. Global

Biogeochem. Cycles, 3, 241-265.

Investigation URLs

http://eos-www.sr.unh.edu/eos/

http://pathfinder-www.sr.unh.edu/pathfinder/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 269

A Global Assesment of Active Volcanism,

Volcanic Hazards, and Volcanic Inputs to the

Atmosphere from EOS

Principal Investigator – Peter J. Mouginis-Mark

Science Background

The impact of volcanoes on the Earth system was dramatically demonstrated by the eruption in 1991 of Mt.

Pinatubo (Philippines), and in 1994 by activity at Rabaul

volcano (Papua New Guinea). Mt. Pinatubo had a nearglobal effect via the introduction of 20-to-30 megatons

of sulfur dioxide and aerosols into the atmosphere, and

represented the second largest eruption this century—second only to Mt. Katmai (Alaska) in 1912. The materials

injected into the stratosphere by Mt. Pinatubo circled the

Earth in only 3 weeks, and covered ~42 percent of the

Earth’s surface after 2 months. Atmospheric models suggest that a global cooling of 0.5 degrees Celsius took place

the year after the eruption. In Papua New Guinea, the

hazards associated with volcanoes were clearly demonstrated by the unexpected eruption of Rabaul volcano,

which caused 30,000 people to be hastily evacuated hours

before over a meter of ash was deposited in parts of the

nearby town!

The degassing history of a lava flow or an eruption

plume may have a major effect on the local or hemispheric

climate, depending on the rate of eruption, the magma

chemistry, and pre-eruption storage characteristics of the

magma. Through the analysis of ongoing eruptions, data

from EOS surface imagers and atmospheric instruments

are expected to significantly improve the understanding

of volcanic hazards, how volcanoes work, and the shortterm effects that eruptions have on weather and climate.

Science Goals

This investigation’s objectives are threefold: 1) to understand the physical processes associated with volcanic eruptions; 2) to investigate the manner by which sulfur dioxide, water vapor, carbon dioxide, and other volcanic gases

are injected into the troposphere and stratosphere; and 3)

to place the diverse volcanic eruptions into the context of

the regional tectonic setting of the volcano.

Current Activities

The major activity is the development of robust algorithms

that enable the team to routinely study volcanic phenomena and their impact on the atmosphere. This includes a

wide range of investigations, including the development

of SO2 retrievals using UV and thermal-infrared data, the

mapping of topography and topographic change using

radar interferometry, the analysis of the particle-size distribution and gas content of volcanic eruption clouds using visible and infrared data, and the analysis of the distribution of temperatures within active lava flows and

domes from infrared observations. Automated techniques

are also being developed that will enable MODIS to detect a new eruption in near real-time, and distinguish an

eruption from a forest fire or other hotspot, thereby enabling event detection to be routinely conducted worldwide. Field programs that test the ability of remote-sensing instruments to make quantitative measurements of volcanic phenomena, and the validation of satellite observations made at visible, infrared, and microwave wavelengths also make up much of our on-going research.

Use of Satellite Data

This investigation draws heavily on many of the EOS sensors and complementary ESE instruments, combining

high-spatial-resolution images of near-vent activity and

daily regional low-resolution views of volcanic thermal

anomalies and eruption plume dispersal. ASTER,

Landsat 7, and MODIS will be used for temperature measurements of active lava flows and eruption plumes. EOSP,

MISR, MLS, SAGE III, and TES will be used to study

the dispersal of different volcanic gases and aerosols.

ASTER and orbital radars (Radarsat, ENVISAT’s ASAR)

will be used for high-resolution topographic mapping of

volcanoes and the analysis of ground deformation due to

intrusions and eruptions. Jason-1, MISR, MODIS, and

VCL will be used to determine the heights of eruption

plumes and their three-dimensional shapes, and these measurements will be compared to AIRS atmospheric temperature data in order to investigate eruption-plume dynamics.

Before the EOS satellites are launched, the team is

using analog data sets from existing instruments, including ATSR, AVHRR, ERS-1/2 radar, HIRS, Landsat 5,

MLS/UARS, Radarsat, SIR-C/X-SAR, TIMS, TOMS, and

TOPSAR. The radar data sets from ERS-1/2, SIR-C/XSAR, and TOPSAR provide baseline topography for individual volcanoes which can be compared to future EOS

digital elevation models derived from ASTER and MISR,

as well as the Shuttle Radar Topography Mission (SRTM).
270 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Different orbital radar instruments are being used to gain

experience in studying temporal changes of volcanoes.

ERS-1/2 and SIR-C/X-SAR data are being used to develop experience in handling large volumes of data and

in working with on-going missions. HIRS is used as an

analog for MODIS, and TIMS (an aircraft instrument similar to the thermal-infrared portion of ASTER) is being

used for temperature studies as well as the development

of algorithms for mapping tropospheric SO2. Four versions of the TOMS instrument have been flown on satellites since 1978 and these have been routinely used to

estimate amounts of SO2 released by volcanic eruptions.

The EP-TOMS has proven to be particularly useful (by

virtue of its relatively low-altitude orbit) for studying tropospheric SO2 from volcanoes. The MLS on UARS provided experience in the interpretation of daily global maps

of SO2 that started 3 months after the eruption of Pinatubo.

In order to observe eruptions while they are still in

progress, this EOS investigation has already contributed

significantly to the development of a near-real-time response capability. Automatically generated alarms for hot

lava flows will be produced continuously from the MODIS data stream and will be placed on our Web site. Such

a capability is expected to be of benefit to numerous other

studies of transient phenomena, particularly forest fires,

since they too will be mapped each day. Higher order data

sets that document the characteristics of specific eruptions, the height and dispersal of eruption plumes, and

the geology of individual volcanoes will be the primary

archival products. These thermal alarms and other data

products will be maintained locally on our Web site for

access by the volcanology community at large.

Participation in Field Programs

Our team is heavily involved in several field programs

related to the analysis of the 15 International Decade Volcanoes, as well as on-going studies of other active volcanoes around the world. We helped organize Decade Volcano Workshops at Santa Maria (Guatemala) in 1993 and

a workshop at Taal (Philippines) in 1995. Planning is currently underway to collaborate with the Filipinos in the

study of Mt. Pinatubo and Canlaon volcanoes as part of

NASA’s PacRim studies. We have also experimented with

the use of Fourier Transform and other thermal IR sensors to monitor SO2 and HCl at Mt. Etna (Sicily). In 1996,

we participated in the NASA aircraft deployment to New

Zealand to map some of the volcanoes and perform volcanic gas studies. These programs are multi-disciplinary,

involving the measurement of volcanic gases, surface temperatures, ground deformation, and topography. Mapping,

using satellite and aircraft data, is also conducted in the

Andes of Chile, the Philippines, and the Galapagos Islands, while synoptic radar data are employed to study

volcanoes in Central Africa.

Principal Investigator

Peter J. Mouginis-Mark

Peter Mouginis-Mark received his training in environmental sciences (Ph.D. from Lancaster University, England,

1977). He has concentrated his research experience on

volcanic phenomena, planetary geology, and remote sensing. He has been associated with the University of Hawaii since 1982, and now is a member of the Hawaii Institute of Geophysics and Planetology. Mouginis-Mark

has been actively involved in many NASA and foreign

Earth orbital missions, particularly in the field of radar

remote sensing. He is currently the Chair of the Commission on Remote Sensing of Volcanoes for the International

Association of Volcanology and Chemistry of the Earth’s

Interior (IAVCEI), and is a former member of NASA’s

Earth System Science and Applications Advisory Committee (ESSAAC). He also has a strong commitment to

space science education and is Program Director for Remote Sensing for the NASA Hawaii Space Grant Consortium.

Co-Investigators

John Adams - University of Washington

Joy A. Crisp - Jet Propulsion Laboratory (Deputy Team

Leader)

Luke P. Flynn - University of Hawaii

Peter W. Francis - Open University, England

Lori S. Glaze - Proxemy Research, Inc.

Jonathan Gradie - TerraSystems, Inc.

Kenneth Jones - Jet Propulsion Laboratory

Anne B. Kahle - Jet Propulsion Laboratory

Arlin Krueger - NASA/Goddard Space Flight Center

Fred Prata - CSIRO-DAR, Australia

David C. Pieri - Jet Propulsion Laboratory

Vince Realmuto - Jet Propulsion Laboratory

William I. Rose - Michigan Technological University

Stephen Self - University of Hawaii

Louis S. Walter - George Washington University

Lionel Wilson - Lancaster University, England

Charles A. Wood - University of North Dakota

Howard A. Zebker - Stanford University
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 271

References

Flynn, L.P., and P.J. Mouginis-Mark, 1995: Thermal characteristics of active lava flows and forest fires. Geophys.

Res. Lett., 22, 2577-2580.

Glaze, L.S., L. Wilson, and P.J. Mouginis-Mark, 1999:

Volcanic eruption plume top topography and heights as

determined from photoclinometric analysis of satellite

data. J. Geophys. Res., 104, 2989-3001.

Holasek, R.E., S. Self, and A.W. Woods, 1996: Satellite

observations and interpretation of the 1991 Mount

Pinatubo eruption plumes. J. Geophys. Res., 101, 27,635-

27,655.

Kahle, A., M.J. Abrams, E.A. Abbott, P.J. Mouginis-Mark,

and V.J. Realmuto, 1995: Remote sensing of Mauna Loa.

Mauna Loa Revealed: Structure, Composition, History,

and Hazards. American Geophysical Union Monograph

No. 92, 145-170.

Krueger, A.J., L.S. Walter, and C.C. Schnetzler, 1996: The

December 1981 eruption of Nyamuragira Volcano (Zaire)

and the origin of the “mystery cloud” of early 1982. J.

Geophys. Res., 101, 15,191-15,196.

Prata A.J., and P.J. Turner, 1997: Cloud-top height determination using ATSR data. Remote Sens. Environ., 59, 1-

13.

Realmuto, V.J., A.J. Sutton, and T. Elias, 1997: Multispectral thermal infrared mapping of sulfur dioxide

plumes—a case study from the East Rift Zone of Kilauea

Volcano, Hawaii. J. Geophys. Res., 102, 15,057-15,072.

Rose, W.I., D.J. Delene, D.J. Schneider, G.J.S. Bluth, A.J.

Krueger, I. Sprod, C. McKee, H.L. Davies, and G.G.J.

Ernst, 1995: Ice in Rabaul eruption cloud of 19-21 September 1994. Nature, 375, 477-479.

Self, S., and P.J. Mouginis-Mark, 1995: Volcanic eruptions, prediction, hazard assessment, and remote sensing.

U.S. National Report to the IUGG, 1991-1994, Revs.

Geophys. Suppl., July 1995, 257-262.

Zebker, H.A., P.A. Rosen, S. Hensley, and P.J. MouginisMark, 1996: Analysis of active lava flows on Kilauea Volcano, Hawaii, using SIR-C radar correlation measurements. Geology, 24, 495-498.

Zebker H.A., P.A. Rosen, and S. Hensley, 1997: Atmospheric effects in interferometric synthetic aperture radar

surface deformation and topographic maps. J. Geophys.

Res., 102, 7547-7563.

Investigation URL

http://www.geo.mtu.edu/eos/

Studying the eruptive characteristics and topography of volcanoes will be greatly aided by EOS-Era instruments. ASTER, MODIS, Landsat

7, SRTM and VCL will be used routinely by the Volcanology IDS Team to study on-going activity, as well as the geology and geomorphology

of volcanoes around the world. This image is of Socompa volcano, NE Chile, which is over 6,050 m high. Landsat Thematic Mapper data

were combined with a digital elevation model derived from ERS-2 radar interferometry to study the flow dynamics of a giant landslide deposit.

Arrows show the direction of flow of the landslide. This landslide, which resulted from an eruption similar to the 1980 activity at Mt. St. Helens,

formed when part of the summit collapsed sometime between 500 to 10,000 years ago. The resultant deposits cover about 490 km2, and

have a minimum volume of 15 km3. Image courtesy of Mary MacKay and Harold Garbeil, University of Hawaii.
272 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Synoptic Analysis of Factors Influencing

Carbon Fluxes at a Continental Margin Time

Series: CARIACO

Principal Investigator – Frank E. Muller-Karger

Science Background

Over geological time scales, geochemical imbalances at

the Earth’s surface are closely tied to carbon sequestration by marine organisms. However, whether the ocean

helps mitigate the increase of anthropogenic greenhouse

gases over shorter time scales (years to decades), represents one of the most pressing questions in ocean biogeochemistry. The question is relevant because even

though the global carbon budget could be balanced if the

terrestrial biosphere were a net sink, at present there is a

net flux of ~3.25 × 1015 gC y-1 from the land biosphere to

the atmosphere. Current biosphere models are inadequate

because they use coarse grids to increase efficiency and

because they are constrained by averages of scarce ocean

data, which are primarily derived from the ocean’s interior. Also, we still don’t understand uncertainties associated with processes that control the fluxes of key elements.

While much of the attention in oceanography over

the past 100 years has focused on the deep ocean, now

there is increasing evidence that ocean margins play a

key role in the global carbon budget. Annual new production integrated over the world’s continental shelves

and slopes (a total of 5.8 × 107 km2) is estimated to be

about 3.7 × 1015 g Carbon. This is over 56% of the total

global new oceanic production. The importance of this

flux lies in its efficient sequestration of elements, i.e., particles that take up carbon from the surface of the ocean

take it with them as they sink. This carbon can be stored

for long periods in deep waters or in the sediment. This

“biological pump” is more significant along continental

margins than in the ocean’s interior, since the mean particle flux at 2,300 m is ~7.0 gC m-2 y-1, compared to ~0.8

gC m-2 y-1 at 2,300 m in the deep sea. These issues lie at

the core of the role of oceanic moderation of atmospheric

CO2 and other greenhouse gases.

Recent evidence suggests that the tropical Atlantic,

and particularly the Caribbean Sea, may function as barometers of global change. The Caribbean experiences

the most marked of the El Niño teleconnections in the

Atlantic Ocean. During El Niño, the Trade Winds tend to

blow more to the NNW rather than to the ESE, and warmer

sea-surface temperatures (SSTs) are observed in the Caribbean. Changes in solar irradiance also lead to SST variations which are in phase in tropical regions, but out of

phase in extratropical regions. Global ocean changes are

therefore dominated by changes in the tropics, and changes

in irradiance accentuate the response of tropical regions.

Along margins, natural and anthropogenic perturbations

may have an amplified effect because of vigorous exchange processes between land, atmosphere, and the

ocean.

The Cariaco Basin is a depression on the continental

shelf of the southern Caribbean Sea (10 ̊20’N, 64 ̊10’W,

11 ̊00’N, 66 ̊10’W). It consists of two main sub-basins,

each about 1400 m deep, separated by a saddle at about

900 m depth off the coast of Venezuela. The basin is bound

to the north by a sill that allows free exchange of water

with the open ocean above about 100 m, but which isolates waters below this depth. Therefore, the Cariaco Basin forms a natural sediment trap embedded within a continental shelf. This is the only permanently anoxic basin

in the world’s oceans, and serves as an oceanic analog of

the Black Sea. In Cariaco, the effects of external oceanic

variability (i.e., in the Atlantic Ocean and Caribbean Sea)

are preserved for decades in the water column and more

permanently within the sediments. We chose the Cariaco

Basin for this study because of these characteristics.

Science Goal

This study seeks to quantify the influence of large-scale

phenomena on the partitioning of carbon into various pools

at a continental-margin time-series site. Of specific interest is the particulate carbon flux that sinks to deeper waters and that is deposited as sediment, since it may represent long-term removal of carbon from the atmosphere.

The primary goal is to assess whether phenomena in the

Western Atlantic have a significant effect on processes

such as the vertical flux of nutrients, river discharge, or

sea-surface temperature, and their interaction on the partitioning of carbon into various pools, including carbon

uptake and deposition, in the Cariaco Basin. We seek to

understand which oceanographic processes are most relevant to components of the carbon budget at this site.

Current Activities

To address the connection between surface oceanographic

processes and sediment flux to deep waters, the National

Science Foundation, in collaboration with the Consejo

Nacional de Investigaciones Cientificas y Tecnologicas
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 273

(CONICIT, Venezuela), implemented a program of observations in the Cariaco Basin in November 1995. This

cooperative, multidisciplinary program is referred to as

CARIACO (CArbon Retention In A Colored Ocean).

CARIACO is part of the NASA SIMBIOS program (Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies) for satellite ocean-color

product validation. Similar programs only exist at two

deep-water oceanic stations, Bermuda and Hawaii, but

CARIACO addresses continental margins issues.

CARIACO is now incorporated into the “Synthesis

and Modeling Project” (SMP) of the U.S. Global Ocean

Flux Study (U.S. JGOFS) through the NASA EOS Interdisciplinary Science Investigation program. This EOS activity will integrate synoptic observations from satellite

platforms into the ongoing field data collection, synthesis, and modeling efforts conducted at the CARIACO

continental-margin time-series station. It will also incorporate a strong education component with national and

international graduate students, research associates, and

middle-and high-school teachers.

Our measurements to date have captured three cycles

of seasonal upwelling in the Cariaco Basin. We estimate

that Net Primary Production (NPP) would normally be of

the order of 450 g C/m2/yr, which compares with a vertical flux of 22.6 g C/m2/yr at 260 m depth and 8.25 g C/

m2/yr at 1250 m. Our observations suggest, however, that

very brief (~2 weeks) punctuated production events raise

productivity as high as 615 g C/m2/yr. These events would

normally be missed in one-time survey programs, but are

captured in the satellite and field-observation time-series

programs.

Use of Satellite Data

We use regional and basin-scale ocean color, infrared,

scatterometer, and selected altimeter observations to study

spatial and temporal variability of parameters that influence the distribution of phytoplankton, primary productivity, dispersal of dissolved organic matter, and the vertical flux of organic material. The satellite data are a rich

source of information that can be used to pinpoint the

upwelling foci, circulation patterns, and the relationship

between local phenomena and processes acting upstream

in the Atlantic Ocean and Caribbean Sea. Ocean-color

data from the CZCS and SeaWiFS sensors, and future

data from MODIS, help us study phytoplankton biomass

fields and the dispersal pattern of river plumes. AVHRR

and future MODIS data provide us with local and global

estimates of the sea-surface temperature, a parameter that

is critical in defining circulation and areas of nutrient supply. Scatterometer data (NSCAT, QuikSCAT, SeaWinds,

ERS-1, ERS-2) provide at least once per day and frequently twice per day coverage of global/regional winds.

These allow us to better understand the dispersal of cold

waters and pigment. With TOPEX/Poseidon data, we have

started an analysis of variability in the sea-surface elevation of the Caribbean Sea and the adjacent Western Atlantic Ocean. These data will be compared with local tidegauge observations to define whether variation seen in

sea level along the coast is due to transient eddies, wind

set-up during the upwelling process, or steric (densityrelated) height changes.

Participation in Field Activities

Our approach to understanding variability in the sediment

record in the Cariaco Basin is to study the relationship

between the sinking flux of particles (measured with

moored sediment traps) and variability in present-day

oceanographic conditions (measured with electronic

probes or discrete samples from a ship). Our results show

that to interpret sediment-trap samples, each of which represents a 2-week integration of the sinking flux, hydrographic and primary productivity observations are required

at least monthly. The field component focuses on primary

production, phytoplankton biomass, hydrography, nutrient, and dissolved inorganic carbon observations on a

monthly basis, on cruises lasting 1.5 days. These monthly

measurements are needed to support the basic objectives

of the sediment-trapping component, and are required to

interpret changes in bacterial community productivity and

respiration. Two of the 1.5-day cruises are extended to 4

days during upwelling maxima and minima periods, respectively, each year. The objective is to study spatial variability around our single monthly station located at 10.5°

N, 64.66° W and map the three-dimensional structure of

the upwelling plume. Our profiling conductivity-temperature-depth (CTD) probe is equipped with both a fluorometer configured to detect chlorophyll and with a c-beam

transmissometer (660 nm). This combination of instruments helps us detect and map the three-dimensional structure of the phytoplankton bloom and differentiate it from

any possible submerged sediment plume extending from

the continental margin.

Principal Investigator

Frank E. Muller-Karger

Frank E. Muller-Karger received his Ph.D. in Marine and

Estuarine Sciences in 1988 from the University of Maryland. He has an M.S. in Biological Oceanography from

the University of Alaska (1984), and a B.S. in Biological

Oceanography from the Florida Institute of Technology

(1979). Muller-Karger was a NASA Graduate Student

Trainee at the Goddard Space Flight Center between 1985

and 1988 and a post-doctoral fellow at the University of

South Florida in 1988. He joined the faculty at the University of South Florida in 1989 where he serves as Associate Professor tenured in the Department of Marine Science. Muller-Karger acted as Program Scientist for Ocean

Biogeochemistry at NASA Headquarters, in this rotating
274 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

position, between 1992 and 1994. His research focuses

on remote sensing of continental margins, including application of visible- and infrared-satellite data to understanding fluxes of elements between land, the ocean surface, and the ocean bottom. Among awards he has received are NASA’s Jet Propulsion Laboratory Award for

Outstanding Contributions in 1996, the NASA

Administrator’s Award for Exceptional Contribution and

Service in 1995, the American Geophysical Union (AGU)

Sea Scholar award (1987-1988), and the American Geological Institute’s Minority Participation Program Scholarship (1987-1988).

Co-Investigators

Ramon Varela - Fundacion La Salle de Ciencias

Naturales Estacion de Investigaciones Marinas Isla

Margarita, Venezuela

John J. Walsh - University of South Florida

Robert Thunell - University of South Carolina

Mary Scranton - State University of New York

Gustavo Ruiz - Fundacion Instituto Ingenieria

Universidad Simon Bolivar, Venezuela

Linwood Jones - University of Central Florida

References

Ballester, A., and R. Margalef, 1965: Produccion primaria.

Memoria. Sociedad de Ciencias Naturales La Salle,

XXV:(70, 71, 72), 209-221.

Berner, R. A., 1992: Comments on the role of marine sediment burial as a repository for anthropogenic CO2. Global Biogeochem. Cycles, 6, 1-2.

Brewer, P. G., 1986: What controls the variability of carbon dioxide in the surface ocean? A plea for complete

information. Dynamic Processes in the Chemistry of the

Upper Ocean. J. D. Burton, P.G. Brewer, and R. Chesselet,

Eds., Plenum, NY. pp. 215-231.

Deuser, W.G., F.E. Muller-Karger, R.H. Evans, O.B.

Brown, W.E. Esaias, and G.C. Feldman, 1990: Surfaceocean color and deep-ocean carbon flux: how close a connection? Deep-Sea Res., 37, 1331-1343.

Enfield, D.B., and D.A. Mayer, 1997: Tropical Atlantic

sea surface variability and its relation to El Niño-Southern Oscillation. J. Geophys. Res., 102, 929-945.

GOFS. 1987. U.S. Global Ocean Flux Study: Ocean Margins in GOFS. Report of the workshop on The Impact of

Ocean Boundaries on the Interior Ocean, March 10-12,

1987. Chairman: George A. Knauer. U.S. GOFS Planning Report Number 6. Woods Hole Oceanographic Institution. 245 pp.

Hochman, H.T., F.E. Muller-Karger, and J.J. Walsh, 1993:

Interpretation of the Coastal Zone Color Scanner (CZCS)

signature of the Orinoco River. J. Geophys. Res., 99, 7443-

7455.

Jahnke, R.A., 1996: The global ocean flux of particulate

organic carbon: Areal distribution and magnitude. Global Biogeochem. Cycles, 10, 71-88.

Longhurst, A R., 1991: Role of the marine biosphere in

the global carbon cycle. Limn. and Ocea., 36, 1507-1526.

Melillo, J.M., T.V. Callaghan, F.I. Woodward, E. Salati,

and K. Sinha, 1990: Effects on ecosystems, p. 283-310,

in: J. T. Houghton et al. [eds.], Climate Change - the IPCC

scientific assessment. Cambridge.

Muller-Karger, F.E., and R. Aparicio, 1994: Mesoscale

Processes Affecting Phytoplankton Abundance in the

Southern Caribbean Sea. Continental Shelf Res., 14, 199-

221.

Muller-Karger, F.E., C.R. McClain, T.R. Fisher, W.E.

Esaias, and R. Varela, 1989: Pigment distribution in the

Caribbean Sea: observations from space. Progress in

Oceanography, 23, 23-69.

Muller-Karger, F.E., C.R. McClain, and P.L. Richardson,

1988: The dispersal of the Amazon’s water. Nature, 333,

56-59.

Peterson, L.C., J.T. Overpeck, N.G. Kipp, and J. Imbrie,

1991: A high-resolution late quaternary upwelling record

from the anoxic Cariaco Basin, Venezuela.

Paleoceanography, 6, 99-119.

Richards, F.A., and R.F. Vaccaro, 1956: The Cariaco

Trench, an anaerobic basin in the Caribbean Sea. DeepSea Res., 3, 214-228.

Walsh, J.J., 1988: On the nature of continental shelves.

Academic Press, San Diego. pp. 1-520.

Zhang, J.Z., and F.J. Millero, 1993: The chemistry of the

anoxic waters in the Cariaco Trench. Deep Sea Res., 40,

1023-1041.

Investigation URL

http://paria.marine.usf.edu
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 275

Investigation of the Atmosphere-Ocean-Land

System Related to Climate Processes

Principal Investigator – Masato Murakami

International Sponsor – Japan

Science Background

It has been widely recognized that the observed long-term,

climatic variations should be understood in the framework of an integrated atmosphere-ocean-land system. The

atmosphere, ocean, and land interact with each other

through the exchanges of heat energy, momentum, and

water substance, while each subsystem undergoes changes

following its own internally determined physical processes. One example can be seen in the relationship between the tropics and the global climate. The tropics act

as heat source regions which drive the global atmospheric

circulation. Recent observational and theoretical studies

have revealed that the long-term variations of tropical heat

sources play an important role in the climatic variability

of the global atmospheric circulation, e.g., such phenomena as El Niño and the Southern Oscillation (ENSO).

The atmospheric circulation changes affect the oceanic circulation through the changes in wind stress at the

sea surface. On the other hand, it is also known that the

variations of the tropical heat sources are closely associated with the variations of sea surface temperature (SST)

through the process of heat exchange. In addition, the circulation changes also cause changes of the soil moisture

and snow cover over land. Recently, investigations have

shown increasing evidence that changes in land-surface

conditions affect the variation of the large-scale atmospheric circulation features such as monsoons.

The preceding discussion serves to illustrate the importance of our understanding of the integrated behavior

of the Earth system. There are other important components to be taken into account when we try to understand

and predict climatic changes. For instance, the effects of

atmospheric minor constituents on the global climate

should be investigated by both observational and modeling studies.

Science Goal

The goal of this investigation is to perform a comprehensive investigation of the atmosphere-ocean-land system

by pursuing seven different subjects (described in the next

section) including both observational and modeling studies.

Current Activities

This investigation provides a mixture of observational

studies and climate modeling related to the atmosphereocean-land interactions that occur through heat and momentum exchanges. The investigation has three components. First, researchers will develop algorithms for the

objective identification of cloud types and the quantitative measurement of precipitation. Data validation of

newly developed remote-sensing techniques will also be

carried out. Based on these products, observational studies will be conducted to examine the atmospheric systems associated with various rainfall activities. The role

of atmospheric minor constituents in climate changes will

also be examined. Secondly, researchers will monitor climatic changes of the sea-surface temperature, sea level,

and sea-surface wind through the use of satellite observations, eventually generating data sets that can be incorporated in the ocean modeling study of seasonal/interannual variations of the Pacific and the mid-latitudinal eddies of the ocean. Finally, researchers will examine landsurface conditions, such as ground wetness and snow

mass.

An atmospheric general circulation model (GCM)

will be incorporated to evaluate the impact of anomalous

surface conditions on climate change. Project elements

will exchange results and data with other elements under

the direction of the Principal Investigator to ensure overall understanding of the Earth system.

The seven supporting studies being conducted by the

Meteorological Research Institute (MRI) of the Japan Meteorological Agency (JMA) are as follows: 1) measurement of precipitation and analysis of rain-producing systems; 2) study of the climatic and environmental changes

affected by the increase of greenhouse gases; 3) ozone

chemistry; 4) validation of EOS data by use of MRI lidar

and JMA data; 5) monitoring of the ocean from satellites;

6) ocean modeling study; and 7) analysis of the changes

of surface conditions in the vicinity of Japan, and studies

of their impact on atmospheric circulations with the use

of the MRI GCM.

Use of Satellite Data

In the atmospheric part of this study we plan to delineate

the convective activity (heat sources) and moisture fields
276 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

at relatively fine spatial resolution with the combination

of data from AIRS, MODIS, and HSB. We have been using AVHRR to estimate rainfall from cumulus-type clouds.

The technique uses classification by the split-window

technique in conjunction with radar and rain gauge observations. The technique will be tuned to retrieve total

precipitable water from the split window and passive microwave data, comparing results with radiosonde observation data. We will also intercompare the passive microwave retrieval and split-window retrieval methods for

rainfall estimation and also for water-vapor estimation

over cloud-free regions. During the early stage of EOS,

intercomparisons with AIRS, ASTER, MODIS, HSB, and

AMSR-E will be carried out. In the oceanic part of this

study, efforts will be concentrated in developing algorithms for retrieving and validating the following geophysical parameters: SST, sea level, and latent heat flux.

Algorithms for retrieving SST with AMSR-E will be developed.

Principal Investigator

Masato Murakami

Masato Murakami was academically trained in Geophysics and Meteorology at the University of Tokyo, and

earned his S. Sc. from that institution in 1974. Except for

a 2-year position at Florida State University, Murakami

has been affiliated with the Meteorological Research Institute for his entire professional career. Currently, he is

Chief of Laboratory in the Typhoon Research Division.

His research interests include tropical, monsoon, and satellite meteorology. He is acting as a WMO rapporteur on

the Asian/African monsoon program and is engaged in

the project management of JEXAM (Japanese Experiment

of Asian Monsoon).

Co-Investigators

The following co-investigators are from the Meteorological Research Institute

Tadao Aoki

Masahiro Endoh

Toshifumi Fujimoto

Masashi Fukabori

Toshiro Inoue

Masafumi Kamachi

Y. Kitamura

Akio Kitoh

Yukio Makino

Tetsuo Nakazawa

Toru Sasaki

Akira Shibata

Kenzo Shuto

Masato Sugi

Tatsahi Tokioka

Osamu Uchino

Isamu Yagai

Koji Yamazaki

References

Chen, T.C., and M. Murakami, 1988: The 30-50 day variation of convective activity over the western Pacific Ocean

with emphasis on the northwestern Pacific Ocean. Mon.

Wea. Rev., 116, 892-906.

Murakami, M., 1992: The equatorial convective activity

and its variation. Technical Note, J. Meteor. Soc., 176,

63-72 (in Japanese).

Murakami, M., and K. Takahashi, 1993: The large scale

convective activity over the equatorial Pacific and the

SPCZ. Kaiyo Monthly, No.5, 33-39 (in Japanese)

Takayabu, T.N., and M. Murakami, 1991: The structure

of super cloud clusters observed in 1-20 June 1986 and

their relationship to easterly waves. J. Meteor. Soc. Japan, 69, 105-125.

Yamazaki, N., and M. Murakami, 1989: An intraseasonal

amplitude modulation of the short-term tropical disturbances over the western Pacific. J. Meteor. Soc. Japan,

67, 791-807.

Investigation URL

http://www.mri-jma.go.jp
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 277

Evaluation and Comparison of Global Threedimensional Marine Carbon Cycle Models

Principal Investigator – Raymond G. Najjar

Science Background

Understanding the processes that control the amount of

carbon dioxide in the atmosphere is critical to our success in making predictions about future climate. The

oceans play a major role in determining atmospheric CO2

because the oceans exchange rapidly with the atmosphere

and because the oceans contain about 65 times more carbon than the atmosphere. Currently, the oceans are believed to be absorbing about 1-2 billion tons of carbon

per year from the atmosphere, a substantial fraction of

the CO2 added to the atmosphere by fossil fuel burning.

Numerical models of the marine carbon cycle are essential for making predictions of atmospheric CO2. Such

models have not been exhaustively evaluated with observations, which are needed in order to determine the their

credibility. What does seem clear is that existing models

do differ greatly from each other. These differences, in

combination with evaluation of the models, could be exploited in order to improve the models and make them

more suitable for the prediction of atmospheric CO2 in

the future.

In 1995, the Ocean Carbon-cycle Model

Intercomparison Project (OCMIP) was initiated. Its goals

were to improve the ability of marine carbon cycle models to simulate the uptake and storage of carbon dioxide.

Through carefully designed simulations, the causes of

model differences were determined. There is still a need,

however, to evaluate these models thoroughly with observations in order to determine model weaknesses and

accelerate model development. Furthermore, a limited

set of simulations was made which did not include the

natural marine carbon cycle.

Science Goal

We have proposed to carry OCMIP to its next phase, which

will include a more- extensive suite of simulations (including the natural marine carbon cycle), a greater diversity of modeling groups, and exhaustive evaluation of

models with observations. The overall goal is the same as

the original aims of OCMIP—to improve marine carbon

cycle models.

Use of Satellite Data

Satellite ocean color data measured from SeaWiFS will

be critical for evaluating models of the natural marine

carbon cycle. SeaWiFS will provide information on chlorophyll concentrations and primary productivity, two important measures of biological cycling in the upper ocean

that affects the carbon budget.

Participation in Field Activities

Data have already been collected for evaluating the models from programs such as JGOFS and WOCE. There is

also a rich historical data set that will be exploited. Therefore, no field measurements are proposed for this project.

Prinicipal Investigator

Raymond G. Najjar

Raymond Najjar is an assistant professor in the Departments of Meteorology and Geosciences at the Pennsylvania State University. His research interests are mainly

associated with the role of the oceans in the Earth system, particularly in the area of global biogeochemical

cycles.

Co-Investigators

Ken Caldeira - Lawrence Livermore National Laboratory

Scott Doney - National Center for Atmospheric

Research

Mick Fellows - Massachussetts Institute of Technology

Robert Key - Princeton University

John Marshall - Massachussetts Institute of Technology

Christopher Sabine - Princeton University

Jorge Sarmiento - Princeton University

Investigator URL

http://www.meto.umd.edu/MISSIONS/

tropoconv.htm
278 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Tropospheric Convection and StratosphereTroposphere Exchange: Effects on

Photochemistry, Aerosols, and Climate

Principal Investigator – Kenneth E. Pickering

Science Background

Deep convection and stratosphere-troposphere exchange

(STE) processes cause substantial changes in the vertical

profiles of trace gases and aerosols which, in turn, have

effects on the actinic flux and on the radiative forcing of

climate. For example, convective transport of ozone precursors leads to enhanced photochemical ozone production in the upper troposphere. These transport processes

develop on small spatial scales, but are globally important and strongly influence the budgets of many species.

However, these smaller-scale hydrodynamical effects and

nonhydrostatic motions are typically not well represented

in state-of-the-art global climate models (GCMs). For example, considerable uncertainty is associated with parameterization of deep convection in GCMs. A variety of other

models, submodels, and algorithms are available to evaluate convection and STE in a GCM and to further enhance

the GCM. Our investigation covers modeling and data

analysis efforts to improve understanding of coupling processes between atmospheric chemistry and climate. We

address two major elements of the EOS Science Strategy: 1) clouds, radiation, water vapor, and precipitation;

and 2) greenhouse gases and tropospheric chemistry.

Science Goals

The major goals of our work are to: 1) examine the effects of vertical mixing processes such as deep convection and STE on photochemically active trace gases and

aerosols and the resulting effects on radiative forcing of

climate; and 2) determine the ability of global chemical

transport models to accurately represent these vertical

mixing processes at various model resolutions. To address

these objectives we are enhancing the Goddard Chemical

Transport Model (GCTM) to operate with a variable resolution grid and with a tropospheric chemical scheme, with

the ultimate goal of coupling the transport model with

the stretched-grid version of the Goddard Earth Observing System (GEOS) GCM and performing experiments

with the coupled system. In addition, we are adding a

chemical scheme to the Goddard Cumulus Ensemble

(GCE) Model. This cloud-resolving coupled system will

be used to evaluate the parameterized convection in the

global model in simulations of observed case-study vertical-mixing events. The combination of models will allow estimation of the effects of mixing events on global

chemical budgets and radiative heating. The sensitivity

of global chemical budgets and related climate characteristics to uncertainties in model description of convection

and STE will be estimated.

Current Activities

Our work to date has centered on five areas: 1) modification of the advection scheme in the GCTM to allow calculation of transport on a stretched grid; 2) incorporation

of the Sparse-Matrix Vectorized Gear code (SMVGEAR

II) chemical solver and chemical mechanism into the

GCTM; 3) development and use of a single-column CTM

for testing chemical mechanisms and for case-study analysis; 4) development of methods for calculating aerosol

and cloud effects on photolysis rates; and 5) preparation

for case-study simulations.

In our transport experiments the continuity equation

for trace gases will be solved on a nonuniform grid generated automatically within the chemical transport model.

The grid is chosen so that its resolution is uniform and

maximum in the region of interest (e.g., the region of a

field experiment); the grid spacing increases gradually

outside of the region with the coarsest resolution occurring on the opposite side of the globe. The advantages of

this approach include improved accuracy in transport and

photochemical calculations in the region of interest and

avoidance of boundary problems that develop in nestedgrid models. The stretched-grid CTM is designed to be

compatible with the Stretched-grid GEOS GCM, which

is under development with separate funding. The modified advection scheme is currently being tested through a

series of Rn-222 tracer experiments. Model runs are being conducted using a uniform grid (2 × 2.5-degree resolution) and with the modified scheme, with a stretched

grid focused over North America and the North Atlantic.

Results are being compared with observed Rn-222 at Bermuda.

We are coupling the Stretched-grid GCTM with the

high-speed SMVGEAR II chemical solver. Initially, we

are using the Jacobson chemical scheme which includes

three different reaction sets (urban, free troposphere, and

stratosphere). Other reaction schemes will also be tested.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 279

We have developed a single-column CTM, which describes the vertical mixing processes exactly as in the

GCTM. It can be driven by the GEOS-1 assimilated data

for a particular region and can be used for case-study

analysis and interpretation of field observations. We are

using the column CTM for comparing model results with

observations as a test of the chemistry schemes for polluted air and for clean marine-boundary-layer conditions.

We are using the discrete-ordinate radiative transfer

model (DISORT) for calculations of actinic flux, and in

combination with molecular properties, we are computing a full set of photolysis rates for use in the CTM. Use

of DISORT will allow consideration of the effects of aerosol and cloud properties on photolysis rates. We have focused on the July 15, 1995 high-ozone episode along the

east coast of the U.S. In this preliminary study of the effects of observed aerosol on tropospheric ozone production, we have computed enhanced ozone production rates

associated with scattering sulfate aerosol and decreased

production with absorbing aerosols such as soot or dust.

We are preparing for upcoming simulations with the

Stretched-grid GCTM for cases of observed convective

mixing and/or STE. The first convective simulation that

will be conducted with the model will be for a period of

the Kansas-Oklahoma PRE-STORM experiment of 1985.

A wealth of meteorological and chemical data is available from this experiment, and we have already performed

simulations of individual convective events from this experiment with the GCE model. Stretched-grid GCTM

calculations will be performed for the April 1996

AEROCE field-campaign period. In this work we will

examine the relative role of photochemical production,

deep convection over land, and transport from the stratosphere in determining ozone mixing ratios over the North

Atlantic Ocean. Major convective episodes have been

detected in the 1994 MAPS CO data. We will also simulate these periods with the Stretched-grid GCTM.

The Stretched-grid GEOS GCM, while still under development, has been successfully run with the dynamics

computed on the stretched-grid and the physical packages computed with a uniform grid of intermediate resolution. Use of winds, temperatures, convective mass

fluxes, and diffusion coefficients from this version of the

GCM with high regional spatial resolution of the dynamics will allow us to account for the effects of small-scale

vertical mixing on chemical processes. When this GCM

is completed, we will couple the GCM with the Stretchedgrid CTM and conduct experiments with the coupled system for vertical mixing events.

Use of Satellite Data

Because CO is an excellent tracer of convective transport, the MAPS CO data will be very useful for the proposed simulations. Similarly, after Terra launch, MOPITT

CO will also be extremely valuable. TOMS total ozone

data will be used in the calculation of photolysis rates,

and TOMS-derived tropospheric ozone will be used in

tropical case studies. CERES, MODIS, and ASTER cloud

products will be used in model verification.

Participation in Field Programs

Pickering and Stenchikov participated in the STERAOA deep convection experiment in Colorado in 1996.

Pickering also took part in the NASA/GTE/TRACE-A

mission in 1992 and in the 1997 NASA/AEAP/SONEX

mission. Deep convection was an important process affecting the measurements in both of these experiments.

Dickerson is a key participant in the AEROCE and

INDOEX field missions.

Principal Investigator

Kenneth E. Pickering

Kenneth Pickering is an atmospheric scientist who is a

research faculty member in the Department of Meteorology at the University of Maryland. He received his B.S.

degree from Rutgers University and an M.S. from the State

University of New York at Albany. Pickering worked in

private consulting in the air pollution meteorology field,

and subsequently earned his doctoral degree in Meteorology from the University of Maryland in 1987. Following completion of his doctoral work, he was a Visiting

Scientist at the NASA/Goddard Space Flight Center where

he studied the effects of deep convection on free tropospheric ozone production through the use of convective

transport and photochemical models. He joined the Joint

Center for Earth System Science (a joint University of

Maryland and NASA/GSFC research institute) in 1994.

Co-Investigators

Georgiy L. Stenchikov - Rutgers/State University of

New Jersey

Dale J. Allen - University of Maryland

Russell R. Dickerson - University of Maryland

Michael S. Fox-Rabinovitz - University of Maryland

Robert D. Hudson - University of Maryland

Wei-Kuo Tao - NASA/Goddard Space Flight Center
280 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

References

Dickerson, R.R., S. Kondragunta, G. Stenchikov, B.

Doddridge, W.F. Ryan, and B. Holben, 1997: The impact

of aerosols on photochemical smog production. Science,

278, 827-830.

Fox-Rabinovitz, M.S., G.L. Stenchikov, M.J. Suarez, and

L.L. Takacs, 1997: A finite-difference GCM dynamical

core with a variable-resolution stretched grid. Mon.

Weather Rev., 125, 2943-2968.

Investigation URL

http://www.meto.umd.edu/MISSIONS/

tropoconv.htm

Upper tropospheric Rn-222 concentrations at 00 UT April 8, 1993 from the UMD/Goddard Stretched-grid CTM. Stretched-grid (uniform-grid)

results are shown in the top (bottom) plot. The location of every 3rd grid point is shown with dots. The resolution of the stretched grid varies

from 0.5 × 0.625 to 2 × 2.5 degrees. The resolution of the uniform grid is 2 × 2.5 degrees. The contour interval is 3 (6) pCi/SCM for

concentrations less (greater) than 18 pCi/SCM. Rn-222 is a tracer used to evaluate venting of the boundary layer by convection in global

chemical transport models.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 281

Coupling Atmospheric, Ecologic, and

Hydrologic Processes in a Regional Climate

Model

Principal Investigator – Roger Pielke, Sr.

Science Background

For several years, we have explored the influence of landscape on weather and climate. In our work, we have demonstrated that alterations in transpiration patterns, due to

vegetation changes over time, have significantly modified thunderstorm development and intensity, and largescale precipitation and temperature patterns (e.g., Pielke

et al. 1998; Pielke and Zeng 1989). We have shown that

these effects extend across the United States (Copeland

et al. 1996) and globally (Chase et al. 1996). Such landscape-change effects may have already altered climate as

much as is proposed for a doubling of greenhouse gases

(Pielke and Zeng 1994). An extensive review of modeling and observational studies of the importance of landscape processes on weather and climate is presented in

Pielke et al. (1998).

Evaluating the two-way interactions between atmospheric and land-surface processes is crucial to understanding regional and global climate, vegetation dynamics, and watershed hydrology. Terrestrial biospheric processes respond strongly to atmospheric temperature, humidity, precipitation, and radiative exchanges, as well as

to surface hydrologic processes including runoff, percolation, and snowpack accumulation and melt. Atmospheric

processes, including large- and small-scale circulations

and the formation of clouds and precipitating systems,

are highly dependent on surface heat and moisture fluxes,

which, in turn, are largely dependent upon vegetation function and soil-moisture storage. In addition, vegetation

plays a major role in determining the relative contributions of precipitation, interception, runoff, and transpiration. The underlying hypothesis motivating this proposal

is that atmospheric, terrestrial biospheric (biophysical/biogeochemical), and surface hydrologic processes are

strongly interactive, such that accurate modeling of these

processes requires their coupling in numerical models.

Examples of interactions we hope to study as part of this

proposal include: 1) identifying whether a dry spring, and

its associated reduced biomass, leads to a relatively dry

summer because of reduced transpiration and moisture

recycling, 2) determining whether a wet spring, and its

relative increase in biomass, reduces the chance of having a relatively dry summer, through the enhanced transpiration and associated precipitation, and 3) quantifying

the influence of land-use practices, like irrigation and grazing programs, on the character of weather and climate.

Science Goal

Our research involves coupling two state-of-the-art models developed at Colorado State University: RAMS and

CENTURY. The Regional Atmospheric Modeling System (RAMS) is a general-purpose atmospheric-simulation modeling system consisting of equations of motion,

heat, moisture, and continuity in a terrain-following coordinate system (Pielke et al. 1992). The Land Ecosystem Atmospheric Feedback model, version two (LEAF2), is a subset of RAMS that represents the storage and

exchange of heat and moisture associated with the atmosphere-terrestrial interface (Walko et al. 1998). The CENTURY ecosystem model simulates the biospheric response

(changes in above- and below-ground biomass) to atmospheric and hydrologic forcings (Parton et al. 1996).

In its current form, RAMS/LEAF-2 assumes that vegetation phenology is predefined according to existing

climatologies and time of year. This limitation prevents

vegetation-related functions from responding to deviations

from climatology, such as wetter or drier than average

seasons, or to changes in climate. Similarly, CENTURY

assumes that atmospheric forcing is known, and that vegetation dynamics have no influence on meteorology or

climate. In contrast to this idealized configuration, numerous studies have shown that there are significant feedbacks between vegetation and the atmosphere (recent studies on this topic include Pielke and Vidale 1995; Chase et

al. 1996; Copeland et al. 1996; Pielke et al. 1997, 1998;

Avissar 1995; Dickinson 1995; Entekhabi 1995). The

current proposal is designed to remedy this uncoupled

misrepresentation of the climate system by merging

RAMS/LEAF-2 and CENTURY. As further justification

for the need to perform such a coupling, we have found

the two models to be sensitive to each other’s outputs.

Because vegetation responds strongly to atmospheric

temperature, precipitation, and soil moisture, both atmospheric and soil hydrologic processes, including precipitation and runoff, must be adequately accounted for in

order to accurately simulate this type of vegetation change.

In turn, the type and quantity of vegetation strongly influence runoff, evaporation, transpiration, surface heat
282 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

flux, and, consequently, the air temperature and development of precipitating systems.

The atmospheric and ecosystem models are coupled

through an exchange of information operating on a sevenday time step. CENTURY receives, as input, the atmospheric-forcing variables including air temperature, precipitation, and radiation simulated by RAMS. From CENTURY-produced outputs, parameters including leaf-area

index, vegetation fractional coverage, displacement and

roughness height, rooting profile, and vegetation albedo

are computed and returned to RAMS/LEAF-2. In this way,

vegetation responses to short-term (weekly) and long-term

(seasonal-to-interannual) atmospheric changes are simulated and fed back to the atmospheric/land-surface hydrology model. The coupled model forms a sophisticated

representation of the atmosphere-land system including

relevant aspects of the hydrological cycle.

The goals of this modeling effort closely follow many

of the priority research areas outlined within the context

of the NASA/NOAA Global Energy and Water Cycle Experiment (GEWEX). In particular, the scientific goals of

this work include:

 1) To develop and validate a comprehensive hydrologicbiospheric-atmospheric model that integrates known

important land and atmospheric processes into a unified interactive system.

 2) To explore mechanisms by which land-use change

affects the hydrological cycle on short-term, seasonal,

and interannual time scales.

 3) To apply a coupled atmosphere-hydrological-ecosystem model as a tool in assessing the potential atmospheric, biospheric, and hydrologic impacts of climate-change scenarios.

Current Activities

To achieve these goals, we are using a climate version of

RAMS that is capable of efficiently performing full annual integrations (Copeland et al. 1996; Liston and Pielke

1998), and focusing on the Rocky Mountains and Central

Grasslands regions.

Comparisons and evaluations of feedbacks between

the models, and their performance as a coupled system,

are being carried out in seasonal-to-multi-year simulations. The integrations initially focus on the 6-year period from 1988 through 1993, which was chosen to highlight a combination of generally typical as well as anomalously wet (e.g., 1993) and dry (e.g., 1988) years. By the

end of our research effort, we expect to achieve the milestone of developing, testing, and verifying the coupled

modeling system to the extent that we are confident in its

usefulness as a primary research tool and simulation model

for studying the complex interactions between the atmosphere, biosphere, and hydrosphere. Specifically, we are

focusing on coupling and evaluating hydrological/ecosystem and atmospheric models over regional-to-continental spatial scales, and over seasonal-to-interannual temporal scales.

As part of our previous research efforts, we have demonstrated that the two models are indeed sensitive to the

outputs of each other. For example, changes in leaf-area

index (LAI), defined within RAMS/LEAF-2, lead to climatologically-significant changes in atmospheric properties like temperature and precipitation. In addition, CENTURY has been found to produce ecologically-significant variations in properties like root-zone biomass and

LAI, in response to climatologically plausible variations

in atmospheric forcings of temperature and precipitation.

Consequently, we anticipate the coupled models will highlight some interesting and significant interactions and

feedbacks.

The major biological variables that influence the atmosphere include live-leaf biomass, plant residue, and

live-root biomass. Increasing live-leaf biomass contributes to greater transpiration water loss from the soil, increased interception water loss, reduced surface runoff,

and a generally lower albedo resulting in increased surface absorption of solar radiation. Increasing plant residue (dead standing and surface plant material) contributes to higher plant-interception water loss, lower surface runoff, lower bare-soil evaporation rates, and generally higher albedo than live plants. Higher root biomass

causes increased evaporation and transpiration water loss

from the soil.

In the coupled models, CENTURY receives, as input, the daily air temperature, precipitation, radiation, wind

speed, and humidity simulated by RAMS/LEAF-2. CENTURY evaluates heterotrophic respiration and nutrient dynamics. From CENTURY-produced outputs, parameters

including leaf-area index (LAI), vegetation fractional coverage, displacement and roughness height, rooting profile, and vegetation albedo are computed and input to

RAMS/LEAF-2 every seven days. In this way, vegetation responses to both short-term and long-term atmospheric changes are simulated and fed back to the atmospheric and hydrology models.

The major proposal objectives in Year 1 involve making the model modifications required to ensure compatibility of the information passed between RAMS/LEAF2 and CENTURY. In addition, the data sets required to

drive and validate the uncoupled and coupled models will

be accumulated. Specific tasks that are being performed

include:

1) Modify RAMS/LEAF-2 to receive inputs from CENTURY. This includes a) casting RAMS/LEAF-2 in a

form that receives spatially distributed vegetation

parameter data sets which are only indirectly linked

to vegetation type, instead of the direct vegetation-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 283

type linkage that currently exists, and b) implement

the routines required to convert from CENTURY-produced variables to those used by RAMS/LEAF-2.

2) Couple RAMS/LEAF-2 and CENTURY dynamically

through subroutine calls operating at a weekly

timestep. Cast the models on common spatial grids,

and implement the use of common vegetation and

soils parameter data sets within the two models.

3) Obtain the data sets required for driving and validating RAMS/LEAF-2 and CENTURY in both uncoupled and coupled modes. These data sets include

those available from the FIFE and CASES program

in Kansas; the Pawnee Grasslands LTER site in Colorado; United States coverage of bi-weekly NDVI data

from the EROS data center; meteorological-station

observations, such as the first-order summary-of-theday data sets; and hourly, six-hourly, and daily atmospheric surface and upper-air observational and analyses data sets such as those provided by the ETA model

as part of GCIP. In addition, we will acquire the NCEP

global-model 6-hourly reanalysis data sets to provide

the RAMS lateral boundary conditions. All of these

data are readily available to us through our accounts

at NCAR and other data archival sites such as the

NASA GSFC Distributed Active Archive Center

(DAAC). The data obtained will focus initially on

the 6-year period 1988 through 1993, chosen to highlight a combination of generally typical as well as

anonymously wet (e.g., 1993) and dry (e.g., 1988)

years. This effort will also complement the regional

atmospheric model intercomparison (PIRCS) for the

Great Plains area being directed by Iowa State University (Takle 1995).

Use of Satellite Data

Satellite remotely sensed data are being used to validate

the coupled RAMS-CENTURY model simulations. Satellite data have also been crucial in identifying current

land use in our modeled domain.

Participation in Field Programs

We are using data collected as part of the FIFE and CASES

in Kansas, and the Pawnee LTER site in Colorado for

model validation. We also plan to utilize ARM/CART data

and information from the University of Oklahoma

mesonet to test the models.

Principal Investigator

Roger A. Pielke, Sr.

Roger A. Pielke, Sr. received both his M.S. and Ph.D.

degrees in Meteorology from Pennsylvania State University. For the last 25 years, he has concentrated on the study

of terrain-induced mesoscale systems, including the development of a three-dimensional mesoscale model of the

sea breeze, for which he received the NOAA Distinguished

Authorship Award for 1974. Pielke has worked for

NOAA’s Experimental Meteorology Lab (1971-1974),

The University of Virginia (1974-1981), and Colorado

State University (1981-present). He is currently a Professor of Atmospheric Science at CSU. He has served as

Chairman and Member of the AMS Committee on

Weather Forecasting and Analysis, and was Chief Editor

for the Monthly Weather Review for 5 years from 1981

to 1985.

In 1977, he received the AMS Leroy Meisinger Award

for “fundamental contributions to mesoscale meteorology through numerical modeling of the sea breeze and

interaction among the mountains, oceans, boundary layer,

and the free atmosphere.’’ Pielke received the 1984 Abell

New Faculty Research and Graduate Program Award, and

also received the 1987/1988 Abell Research Faculty

Award. He was declared “Researcher of 1993” by the

Colorado State University Research Foundation. He was

elected a Fellow of the AMS in 1982. From 1993-1996,

he served as Editor-in-Chief of the U.S. National Science

Report (1991-1995) for the American Geophysical Union.

Starting in January 1996, he was appointed to a threeyear term as Co-Chief Editor of the Journal of Atmospheric Science.

He has published over 200 papers in peer-reviewed

journals, 25 chapters in books, and co-edited 4 books.

He is currently a professor in the Department of Atmospheric Science at Colorado State University.

Co-Investigator

Glen E. Liston - Department of Atmospheric Science,

Colorado State University

References

Avissar, R., 1995: Recent advances in the representation

of land-atmosphere interactions in general circulation

models. Rev. Geophys., Supplement to Vol. 33, 1005-1010.

Chase, T.N., R.A. Pielke, T.G.F. Kittel, R. Nemani, and

S.W. Running, 1996: The sensitivity of a general circulation model to global changes in leaf area index. J.

Geophys. Res., 101, 7393-7408.
284 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Copeland, J.H., R.A. Pielke, and T.G.F. Kittel, 1996:

Potential climatic impacts of vegetation change: A regional modeling study. J. Geophys. Res., 101, 7409-7418.

Dickinson, R.E., 1995: Land-atmosphere interaction.

Rev. Geophys., Supplement to Vol. 33, 917-922.

Entekhabi, D., 1995: Recent advances in land-atmosphere

interaction research. Rev. Geophys., Supplement to Vol.

33, 995-1003.

Liston, G.E., and R.A. Pielke, 1998: A climate version of

the Regional Atmospheric Modeling System. In preparation.

Parton, W.J., D.S. Ojima, and D.S. Schimel, 1996: Models to evaluate soil organic matter storage and dynamics.

In M.R. Carter, Ed., Structure and Organic Matter Storage in Agricultural Soils, CRC Press, Inc., 421-448.

Pielke, R.A., and P.L. Vidale, 1995: The boreal forest

and the polar front. J. Geophys. Res., 100, 25,755-25,758.

Pielke, R.A., and X. Zeng, 1989: Influence on severe

storm development of irrigated land. Nat. Wea. Dig., 14,

16-17.

Pielke, R.A., and X. Zeng, 1994: Compounding of uncertainty in climate change scenarios. Proceedings, Global Climate Change: Science, Policy, and Mitigation Strategies, Air and Waste Management Association, Phoenix,

Arizona, 5-8 April 1994, 393-401.

Pielke, R.A., W.R. Cotton, R.L. Walko, C.J. Tremback,

M.E. Nicholls, M.D. Moran, D.A. Wesley, T.J. Lee, and

J.H. Copeland, 1992: A comprehensive meteorological

modeling system - RAMS. Meteor. Atmos. Phys., 49, 69-

91.

Pielke, R.A., T.J. Lee, J.H. Copeland, J.L. Eastman, C.L.

Ziegler, and C.A. Finley, 1997: Use of USGS-provided

data to improve weather and climate simulations. Ecological Applications, 7, 3-21.

Pielke, R.A., R. Avissar, M. Raupach, H. Dolman, X.

Zeng, and S. Denning, 1998: Interactions between the

atmosphere and terrestrial ecosystems: influence on

weather and climate. Global Change Biology, 4, 101-115.

Takle, E.S., 1995: Project to intercompare regional climate simulations (PIRCS), Preliminary Workshop, 17-

18 November 1994. Bull. Amer. Meteor. Soc., 75, 1625-

1626.

Walko, R.L., L.E. Band, J. Baron, T.G.F. Kittel, R.

Lammers, T.J. Lee, R.A. Pielke Sr., C. Taylor, C. Tague,

C.J. Tremback, and P.L. Vidale, 1998: Coupled atmosphere-terrestrial ecosystem-hydrology models for environmental modeling. Department of Atmospheric Science

Class Report 9, Colorado State University, Fort Collins,

Colorado, 46 pp + figures.

Investigation URL

http://hercules.atmos.colostate.edu/~project/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 285

Chemical, Dynamical, and Radiative

Interactions Through the Middle Atmosphere

and Thermosphere

Principal Investigator – John A. Pyle

International Sponsor – United Kingdom

Science Background

The middle atmosphere is a highly coupled system in

which dynamical, radiative, and chemical processes are

intimately connected. CO2 and O3 play important radiative roles. Ozone absorbs ultraviolet radiation. This leads

to a heating of the middle atmosphere and also protects

the biosphere from a strong and potentially dangerous UV

dosage. The distribution of ozone depends on the chemical interactions of a large number of other gases. Atmospheric temperature and the general circulation of the

middle atmosphere are also crucial to determining the

structure of ozone. Exchanges with both the troposphere

and higher atmospheric levels are important in determining the longer term changes to the system. It is vital that

all these processes be understood.

Science Goals

This investigation aims to improve our understanding of

atmospheric dynamical, chemical, and radiative interactions—and hence the ability to predict and detect longterm atmospheric trends in the Earth’s climatic and chemical environment. Modeling and data analysis efforts will

focus on the following middle atmosphere and thermosphere components: 1) circulation and internally generated variability of the atmosphere; 2) interactions between

chemical, dynamical, and radiative processes; and 3) horizontal and vertical coupling mechanisms.

The study will involve a two-pronged theoretical assault using EOS data and sophisticated numerical, dynamical, radiative, and photochemical models of the troposphere, stratosphere, and mesosphere now being developed in the United Kingdom.

Current Activities

As part of our study we have developed a hierarchy of

numerical models of the middle atmosphere. These include several 3-D models. One is a free-standing general

circulation model (GCM), based on a model from the

European Centre for Medium Range Weather Forecasts,

to which we have added a full description of chemical

processes. Future studies with this model will aim at

chemistry/climate interactions. We have also developed

a number of chemical transport models, using different

vertical coordinate systems, in which the transport is specified, either from meteorological analyses or from previous GCM integrations. These models are complemented

by a range of trajectory models of varying sophistication.

Our scientific studies have involved detailed investigations combining our models with atmospheric data.

Thus, a variety of UARS data sets have been studied using the full range of models. Particular investigations

have looked at, for example, the descent within the polar

vortex, the exchange between the polar vortex and middle

latitudes, as well as studies of chlorine activation and deactivation.

Use of Satellite Data

Our EOS studies will involve the combination of our numerical models with various EOS data sets. Of particular

interest will be instruments designed to measure chemical constituent concentrations or to provide dynamical or

radiative information, especially for the middle atmosphere. These instruments include HIRDLS, MLS, TES,

SOLSTICE, ACRIM III, SAGE III, MOPITT, and

CERES. The data will be used in a number of ways.

Firstly, case studies of interesting periods will be carried

out using our hierarchy of models. Secondly, seasonal,

and longer, integrations will be performed, initializing the

models with appropriate EOS data, and comparing the

subsequent model and data evolution. Thirdly, in research

mode, 4-dimensional variational assimilation studies will

be carried out, building on studies currently underway.

Participation in Field Programs

We have participated in recent field campaigns such as:

1) EASOE - European Arctic Stratospheric Ozone Experiment; 2) SESAME - Second European Stratospheric

Arctic and Mid-latitude Experiment; 3) ASHOE - Airborne Southern Hemisphere Ozone Experiment; and 4)

THESEO, the Third European Stratospheric Experiment

on Ozone.
286 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Our aim has been to study polar ozone loss (with an emphasis on the Arctic) and the way polar processes influence the middle latitudes. Of special interest have been

very-high-resolution modeling studies to investigate the

filaments of air, torn from the edge of the polar vortex,

which have been observed and now successfully modeled.

These investigations are advancing our ability to combine data and models and so are paving the way to studies

in the EOS era.

Principal Investigator

John Pyle

John Pyle holds a D.Phil. in Atmospheric Physics from

the University of Oxford. He is University Reader in Atmospheric Chemistry at the University of Cambridge and

head of the European Ozone Research Coordinating Unit

since 1991. Currently, he serves as Principal Investigator

in the U.K. Universities Global Atmospheric Modeling

Programme supported by the Natural Environment Research Council. He has chaired the Core Groups organizing both EASOE and SESAME campaigns to study

Arctic stratospheric ozone. He is Chairman of the U.K.

Stratospheric Ozone Review Group and has served as a

consultant to the European Space Agency on the future

of middle atmospheric studies from space. In 1985, he

was the recipient of the Eurotrac Award of the Remote

Sensing Society.

Co-Investogators

Timothy J. Fuller-Rowell - CIRES-Boulder, Colorado

Lesley J. Gray - Daresbury Rutherford Appleton

Laboratory

Joanna D. Haigh - Imperial College of Science and

Technology

Robert S. Harwood - University of Edinburgh

Brian Hoskins - University of Reading

Roderic L. Jones - University of Cambridge

Michael E. McIntyre - University of Cambridge

Roy J. Moffett - University of Sheffield

Shaun Quegan - University of Sheffield

David Rees - University College, London

Alan Rodger - British Antarctic Survey

Keith Shine - University of Reading

Ralf Toumi - Imperial College of Science and Technology

References

Bekki,S., M.P. Chipperfield, J.A. Pyle, J.J. Remedios, S.E.

Smith, R.G. Grainger, A. Lambert, J.B. Kumer, and J.L.

Mergenthaler , 1997: Coupled aerosol-chemical modelling of UARS HNO3 and N2O5 measurements in the

Arctic upper stratosphere. J. Geophys. Res., 102, 8977-

8990.

Chipperfield, M.P., A.M. Lee, and J.A. Pyle, 1996: Model

calculations of ozone depletion in the Arctic polar vortex

for 1991/92 to 1994/95. Geophys. Res. Lett., 23, 559-562.

Hadjinicolaou, P., J.A. Pyle, M.P. Chipperfield, and J.A.

Kettleborough, 1997: Effect of interannual meteorological variability on middle latitude ozone. Geophys. Res.

Lett., 24, 2993-2996.

Lee, AS.M., G.D.Carver, M.P.Chipperfield, and J.A.Pyle,

1997: Three-dimensional chemical forecasting: A methodology. J. Geophys. Res., 102, 3905-3917.

McIntyre, M.E., and J.A. Pyle, 1993: Model studies of

dynamics, chemistry, and transport in the Antarctic and

Arctic stratospheres. University Research in Antarctica,

R.B.Heywood, Ed., British Antarctic Survey, 17-33.

Pyle, J.A., G. Carver, J.L. Grenfell, J.A. Kettleborough,

and D.J.Lary, 1992: Ozone loss in Antarctica: The implications for global change. Proc. Roy. Soc. London B, 338,

219-226.

Pyle, J.A., P. Brown, S. Bekki, G.D. Carver, K.S. Law,

and D.Z. Stockwell, 1995: Modeling the sources and sinks

of radiatively active gases. Proc. Roy. Soc. London A, in

press.

Investigation URL

http://www.atm.ch.cam.ac.uk/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 287

Project ATLANTA (ATlanta Land use ANalysis:

Temperature and Air quality)

Principal Investigator – Dale A. Quattrochi

Science Background

Project ATLANTA seeks to observe, measure, model, and

analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970’s has impacted the

region’s climate and air quality. The primary objectives

for this research effort are: 1) To investigate and model

the relationship between Atlanta urban growth, land-cover

change, and the development of the urban heat island

phenomenon through time at nested spatial scales from

local to regional; 2) to investigate and model the relationship between Atlanta urban growth and land-cover change

on air quality through time at nested spatial scales from

local to regional; and 3) to model the overall effects of

urban development on surface-energy budget characteristics across the Atlanta urban landscape through time at

nested spatial scales from local to regional.

Science Goal

Our key goal is to derive a better scientific understanding

of how land-cover changes associated with urbanization

in the Atlanta area, principally in transforming forest lands

to urban land covers through time, has, and will, affect

local and regional climate, surface-energy flux, and airquality characteristics. Allied with this goal is the prospect that the results from this research can be applied by

urban planners, environmental managers, and other decision makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta

area. It is our intent to make the results from this investigation available to the user community to help facilitate

measures that can be applied to mitigate climatological

or air-quality degradation, or to design alternative measures to sustain or improve the overall urban environment

in the future.

Current Activities

The scientific approach we are using in relating land-cover

changes to modifications in the local and regional climate

and in air quality, is predicated on the analysis of remotesensing data in conjunction with in situ data (e.g., meteorological measurements) that are employed to initialize

local- and regional-level numerical models of land-atmosphere interactions. Remote-sensing data form the basis

for quantifying how land covers have changed within the

Atlanta metropolitan area through time from the early1970’s, when Atlanta’s dramatic growth began in earnest,

to the present. These remotely sensed data will be used to

provide input to numerical models that relate land-cover

change through time with surface-energy flux and meteorological parameters to derive temporal models of how

land-cover changes have impacted both the climatology

and the air quality over the Atlanta region. Current remote-sensing data (i.e., data obtained during 1997) will

be used to calibrate the models and to serve as baseline

data for extending the models to predict how prospective

future land-cover changes will affect the local and regional

climate and air quality over the Atlanta-north-Georgia region. Additionally, remote-sensing data will be used to

characterize and measure urbanization and deforestation

parameters that can be used to assess, as well as predict,

the effects of land-use changes on the local microclimate.

The science tasks associated with Project ATLANTA

are being executed via a number of separate, but highly

interlinked, tasks. These are listed in the following paragraphs.

Land-Use/Land-Cover-Change Detection from

Landsat MSS and Thematic Mapper Images

Science Objectives – 1) To detect land-use/land-cover

changes that are meteorologically or climatologically significant across the Atlanta metropolitan area using retrospective Landsat MSS and TM data, and high-spatial-resolution aircraft-scanner data; 2) to map changes in landsurface temperature using retrospective Landsat MSS and

TM data, and high-spatial-resolution aircraft-scanner data;

and 3) to derive NDVI estimates of changes in greenness

for the Atlanta area through time using Landsat MSS and

TM and AVHRR data, and high-spatial-resolution aircraftscanner data. Land-use/land-cover change has been

mapped from MSS data over the Atlanta region for 1973,

1979, 1983, 1988, and 1992. Current research efforts are

focused on extracting NDVI values from the historical

MSS data, on mapping land use/land cover from Landsat

TM data obtained in 1997 over Atlanta, and on mapping

land use/land cover from high-spatial-resolution multispectral aircraft-scanner data acquired over Atlanta in

1997.
288 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Analysis of Urban Surface Energy Fluxes from

High-Spatial-Resolution Multispectral Thermal IR

Data

Science Objectives – 1) To characterize and quantify surface-energy fluxes using high-spatial-resolution airborne

remote-sensing data across the Atlanta urban landscape;

2) to examine and quantify effects of spatial scale on these

energy fluxes; and 3) to develop a functional classification of the change in thermal surface-energy flux over

time of the Atlanta urban landscape. High-spatial-resolution (10-m pixel resolution) multispectral aircraft-scanner data were acquired over Atlanta using the NASA Advanced Thermal and Land Applications Sensor (ATLAS)

in May 1997. These data are being used to derive thermal

IR measurements of land-surface-energy fluxes for day

and night for the Atlanta metropolitan area for input to

the land-use change, and meteorological and air-quality

modeling tasks in Project ATLANTA. MAS and AVIRIS

data were also collected over Atlanta in August 1997 and

will be used to derive additional land-cover information

for use in the land-use change and meteorological modeling tasks of this project.

Linking Satellite Remote-Sensing Data with Temporal Changes in Urban Land Cover and Observed

Climatic Data

Science Objectives – To derive an historical description

of urbanization (i.e., associated land-use change) for Atlanta using the available archived satellite data (e.g.,

AVHRR) from 1985 to date (1996) on an annual basis,

and to estimate the amount of soil moisture, and vegetative cover that has been modified as a result of the urbanization process. NDVI values have been derived from

AVHRR data acquired for the region. These data will be

analyzed for comparison of how NDVI changes through

time over the study area. AVHRR data will be used to

assess the influence of urbanization and related changes

in land cover on the observed in situ maximum and minimum air temperatures. Additionally, AVHRR-derived surface-temperature and vegetation-index values, and modeled fractional-vegetative-cover and heat-flux values will

be analyzed in relation to land-use/land-cover changes as

defined from Landsat MSS and TM data sets.

Meteorological Modeling

Science Objectives – To simulate the regional meteorology and air quality of the Atlanta region over a time span

of several years (e.g., mid-1970’s to the present) as a

means for understanding the linkages between changes

in local land use/land cover and regional meteorology and

air quality. Another objective is to model prospective (i.e.,

future) changes that may occur, based on simulated

changes in land use/land cover, on meteorological and

air-quality conditions over the Atlanta metropolitan area.

These simulations of future impacts are useful as input to

decision makers for potentially developing air-quality control measures and for mitigating the development of the

urban heat island over the Atlanta-north Georgia region.

Two summer episodes have been used to model daytime

and nighttime heating over the Atlanta region. Work is

currently in-progress in implementing the MM5 model

for comparative testing of simulated meteorological scenarios over Atlanta in the future. Current research is directed towards improving meteorological model input

using land-cover information derived from the high-spatial-resolution aircraft data collected in 1997 along with

recent TM data, and in using the historical land-cover information derived from MSS and AVHRR data.

Air Quality Modeling

Science Objectives – The impacts of urban growth on air

quality in Atlanta both for short- and long-term changes

are being modeled using photochemical simulations. Airquality impacts of changes in albedo and vegetation cover/

tree species over time and as proposed in future urban

development plans for Atlanta are also being modeled.

The most significant meteorological impact of these surface modifications is an elevation in air temperature which

will increase chemical reaction rates. A base-case photochemical model has been run for the Atlanta region using

the Urban Airshed Model (UAM) for two air-quality episodes. Improved base-case and modified base-case UAM

scenarios are currently being performed using state-wide

in situ observational meteorological data. Land-use information derived from ATLAS, Landsat MSS and TM,

and AVHRR data are being used to refine the airshed basecase model via input to the background meteorological

model. Remote-sensing data are also used to define albedo input as a refinement to the UAM model.

Analysis of Cloud Effects on Urban Climate

Science Objectives – Clouds are significant intermediaries in the urban land-cover-climate connection. Changes

in urban land cover will change the cloud cover—particularly of the small clouds—which will change the solar insolation and the outgoing infrared radiation, and thus

the climate and the air quality. GOES 8 data are being

used to construct a cloud climatology over the study area

for input to the meteorological modeling tasks of Project

ATLANTA. GOES 8 data are also being analyzed to understand the diurnal variability of albedo, soil-moisture

availability, thermal inertia, and surface roughness needed

to initialize the mesoscale meteorological models. Additionally, GOES 8 data are being used to determine what

effects changes in land use/land cover have on the modeled cloud field over the Atlanta area.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 289

Applications Strategy Assessment

Objectives – During FY97 an effort was initiated to relate

the science tasks associated with Project ATLANTA to

the needs of the user community in the Atlanta metropolitan area. The application of the results achieved in

Project ATLANTA by decision makers, planners, and other

individuals and agencies to make the Atlanta area a moresustainable and habitable urban environment, is viewed

as the ultimate demonstration that the science tasks described above, produce results that can be effectively used

to make the Atlanta metropolitan area a better place in

which to work and live. Three areas comprise the principal foci for current and future work: 1) Maintain effective contact with the recently organized Project ATLANTA

Applications Working Group to ensure that data products

are developed that are responsive to the group’s needs

and interests. This will be accomplished by keeping the

working-group members informed regarding the types of

remote-sensing data collected, plans to utilize this data,

and how we hope to use the data to advance knowledge

of the urban heat island and its impact on air quality and

the energy budget; 2) evaluate the tools and resources

available for integration with the remote-sensing data and

model output products from Project ATLANTA. This includes a survey of GIS-based tools and software packages that are of interest to the user community in the Atlanta area; and 3) transfer the remote-sensing and data

and model output results from Project ATLANTA to the

user community.

Use of Satellite Data

Pre-EOS satellite data are used extensively throughout

Project ATLANTA for analysis of landscape, biophysical, land-atmosphere surface-energy flux, and cloud characteristics over the Atlanta metropolitan area. Landsat

MSS and TM data are used to detect, observe, and measure land-cover/land-use change across the study area.

AVHRR data are being employed to measure a host of

attributes including NDVI, land-cover/land-use change,

soil-moisture availability, and thermal-energy fluxes.

GOES 8 data are utilized to analyze cloud cover, as well

as diurnal variability of albedo, soil-moisture availability, thermal inertia, and surface roughness. These satellite data are key inputs to initializing and calibrating the

meteorological and air-quality models used in Project ATLANTA, and also for providing temporal data on the dynamics of a range of biophysical and land-process phenomena, to assess how these parameters have impacted

the meteorology and air quality of the Atlanta area.

Data from the Terra platform, particularly from

MODIS and ASTER, and the Landsat 7 ETM+, will be

integral to the continued analysis and modeling of how

landscape dynamics across the Atlanta metropolitan area

affects meteorology and climate. As a precursor to the

launch of MODIS, MAS data acquired to support this

project will be used in conjunction with the high-spatialresolution ATLAS data, to define thermal surface-energy

flux characteristics for selected surfaces typical of the

Atlanta urban landscape. MODIS data will be employed

to provide current data on land-cover/land-use change,

NDVI, and thermal land-surface characteristics over the

Atlanta metropolitan region for input to meteorological

and air-quality modeling. ASTER thermal data in conjunction with Landsat 7 ETM+ TIR data, will be analyzed to derive current measurements of daytime and

nighttime thermal-energy flux characteristics that will be

particularly valuable in assessing and modeling the magnitude, extent, and dynamics of the Atlanta urban heat

island on a seasonal and yearly basis. These collective

data from MODIS, ASTER, and Landsat ETM+ will provide a vehicle for developing a near-real-time analysis of

land-cover/land-use change, NDVI, and urban-heat-island

dynamics, at different spatial and spectral resolutions.

These data will also be critical to understanding how urban landscape attributes, biophysical characteristics, and

surface thermal-energy fluxes are manifested at different

spatial, temporal, and radiometric scales. Additionally,

data from the MODIS, ASTER, and Landsat ETM+ sensors, in conjunction with current and future generation

GOES data, will be invaluable for building a comprehensive model on how soil moisture, albedo, and related biophysical properties affect cloud-cover development,

which, ultimately, will affect the climate and air quality

of the Atlanta metropolitan area.

We believe these data will also be of great value to

the user community by providing a variety of satellite data

products obtained at different spatio-temporal resolutions,

that can be used for the continuous characterization of

land-cover dynamics across the Atlanta region. We envision a host of potential applications for MODIS, ASTER,

and Landsat 7 ETM+ data, especially for decision-making on urban land use or environmental policies at the

regional level across the Atlanta metropolitan area.

Participation in Field Activities

Field activities associated with Project ATLANTA are

related primarily to ground-truth assessments of landscape

characteristics for verification of land-cover characterization information derived from aircraft and satellite data.

Field campaigns to support data collection with the ATLAS and MAS sensors in 1997 focused on obtaining spot

surface-temperature measurements using thermal IR thermometers, and in launching radiosonde balloons and setting up solar measurement instrumentation to acquire atmospheric profile and solar insolation data for remotesensing data calibration.
290 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Principal Investigator

Dale Quattrochi

Dale Quattrochi is a Senior Research Scientist with the

NASA Global Hydrology and Climate Center located at

the George C. Marshall Space Flight Center in Huntsville, Alabama. He received his Ph.D. in geography from

the University of Utah and has over nineteen years of experience in the field of Earth science remote-sensing research and applications. His research interests focus on

the analysis of land-atmosphere energy exchanges in urban areas using thermal remote sensing, on the characterization of urban landscape patterns and processes using

remote sensing, on the integration of remote-sensing data

with geographic information systems, and on the spatial

analysis of remote-sensing data using fractals and other

geostatistical techniques. He has co-edited a book with

Michael Goodchild from the University of California,

Santa Barbara, entitled Scale in Remote Sensing in GIS,

published in January 1997 by CRC/Lewis Publishers,

Boca Raton, Florida.

Quattrochi is an adjunct faculty member in the geography departments at the University of New Orleans and

the Louisiana State University. He is also an adjunct professor in the Department of Plant and Soil Science and

the Center for Hydrology, Soil Climatology and Remote

Sensing at Alabama A&M University, and is an adjunct

associate professor in the Department of Atmospheric

Science at the University of Alabama in Huntsville.

Co-Investigators

Jeffrey C. Luvall - NASA, Global Hydrology and

Climate Center

Stanley Q. Kidder - Colorado State University

C.P. Lo - University of Georgia

Haider Taha - Lawrence Berkeley National Laboratory

Robert D. Bornstein - San Jose State University

Robert R. Gillies - Utah State University

Kevin P. Gallo - NOAA/NESDIS National Climatic

Data Center

References

Bornstein, R., 1987: Urban effects on mesoscale and synoptic systems. Preprints, 3rd AMS Conf. on Mesoscale

Processes, 21-26 August, Vancouver, B. C.

Bornstein, R., et al., 1994: Observation and simulations

of urban effects on boundary layer structure. Air Pollution Modeling and its Applications, X, Plenum Press, New

York, 101-108.

Gallo, K.P., J.D. Tarpley, A.L. McNab, and T.R. Karl,

1995: Assessment of urban heat islands: a satellite perspective. Atmos. Res., 37, 37-43.

Gallo, K.P., and J.D. Tarpley, 1996: The comparison of

vegetation index and surface temperature composites for

urban heat-island analysis. Intl. J. Remote Sens., 17, 3071-

3076.

Gallo, K.P., D.R. Easterling, and T.C. Peterson, 1996. The

influence of land use/land cover on climatological values

of the diurnal temperature range. J. Climate, 9, 2941-2944.

Gillies, R.R., T.N. Carlson, J. Cui, W.P. Kustas, and K.S.

Humes, 1997: A verification of the ‘triangle’ method for

obtaining surface soil water content and energy fluxes

from remote measurements of the Normalized Difference

Vegetation Index (NDVI) and surface radiant temperature. Intl. J. Remote Sens., 18, 3145-3166.

Kidder, S.Q., and O.M. Essenwanger, 1995: The effect of

clouds and wind on the difference in nocturnal cooling

rates between urban and rural areas. J. Appl. Meteor., 34,

2440-2448.

Kidder, S.Q., and J. Hafner, 1995: A satellite study of urban warming for global climate change research. Presented at Reducing Scientific Uncertainty II: The Second

Annual NIGEC Research Symposium, 26-27 April 1995,

Tuscaloosa, Alabama.

Lo., C.P., D.A. Quattrochi, and J.C. Luvall, 1997: Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. Intl. J.

Remote Sens., 18, 287-304.

Lo, C.P., 1997: Land use/cover changes of the Atlanta

Metropolitan Region as revealed by Landsat MSS Images, 1973-1992. Abstracts, Southeastern Division of the

Association of American Geographers annual meeting,

22-25 November 1997, Birmingham, AL, p. 15.

Lo, C.P., and X. Yang, 1998: An operational approach to

land use/cover change mapping using multi-date Landsat

MSS imagery. Paper presented at the 94th annual meeting of the Association of American Geographers, 25-29

March 1998, Boston, MA.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 291

Lo, C.P., and X. Yang, 1998: Some practical considerations of relative radiometric normalization of multidate

Landsat MSS data for land use change detection. Paper

presented at the American Society for Photogrammetry

and Remote Sensing-Resource Technology Institute annual meeting, 30 March-3 April, 1998, Tampa, FL.

Owen, T.W., T.N. Carlson, and R.R. Gillies, 1997: An

assessment of satellite remotely sensed land cover parameters in quantitatively describing the climate effect of urbanization. Intl. J. Remote Sens., in press.

Quattrochi, D.A., and M.K. Ridd, 1994: Measurement and

analysis of thermal energy responses from discrete urban

surfaces using remote sensing data. Intl. J. Remote Sens.,

15, 1991-2022.

Quattrochi, D.A., and N.S. Goel, 1995: Spatial and temporal scaling of thermal infrared remote sensing data.

Remote Sensing Reviews, 12, 255-286.

Quattrochi, D.A., and J.C. Luvall, 1997: High spatial resolution airborne multispectral thermal infrared data to support analysis and modeling tasks in EOS IDS Project

ATLANTA. The Earth Observer, 9, 22-27.

Quattrochi, D., and M.K. Ridd, 1998: Analysis of vegetation within a semi-arid urban environment using high spatial resolution airborne thermal infrared remote sensing

data. Atmos. Environ., 32, 19-33.

Taha, H., 1996: Modeling the impacts of increased urban

vegetation on the ozone air quality in the south coast air

basin. Atmos. Environ., 30, 3423-3430.

Taha, H., 1997. Modeling the impacts of large-scale albedo changes on ozone air quality in the south coast air

basin. Atmos. Environ., 31, 1667-1676.

Taha, H., and A. Meier, 1997: Mitigation of urban heat

islands: Meteorology, energy, and air quality impacts.

Proceedings, International Symposium on Monitoring and

Management of Urban Heat Island, CREST/JST, 19-20

November 1997, Keio University, Fujisawa, Japan, 124-

163.

Investigation URL

http://wwwghcc.msfc.nasa.gov/atlanta/

High-resolution (10 m) daytime thermal ATLAS image of the Atlanta, Georgia central business district (CBD). Grayscale

relative temperature ranges are from “hot” (in white) to “cool” (in dark gray to black). Note the shadows cast by tall

buildings in the Atlanta CBD.
292 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Variability and Predictability of LandAtmosphere Interactions: Observational and

Modeling Studies

Principal Investigator – John O. Roads

Science Background

This investigation is aimed at evaluating and predicting

seasonal-to-interannual variability for selected regions

emphasizing the role of land-atmosphere interactions. Of

particular interest are the relationships between large-scale

and regional and local scales and how they interact to

account for seasonal and interannual variability, including extreme events such as droughts and floods. North

and South America, including the GEWEX GCIP,

MacKenzie, and LBA basins, will be emphasized during

the first two years. We will also generalize and synthesize to other land regions across the globe, especially those

pertinent to other GEWEX projects.

Science Goal

The overall goal of this project is to increase our understanding of seasonal-to-interannual variability and predictability of atmosphere-land interactions. The specific

objectives of are to:

1) Document the low-frequency variability in land-surface features and associated water and energy cycles

from general circulation models (GCMs), observations, and reanalysis products.

2) Determine what relatively wet and dry years have in

common on a region-by-region basis and then examine the physical mechanisms that may account for a

significant portion of the variability.

3) Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long-range predictability.

Current Activities

Roads et al. (1998a) compared characteristics of the National Centers for Environmental Prediction and National

Center for Atmospheric Research (NCEP/NCAR) reanalysis surface-water budget to the surface-water budget characteristics in a long-term simulation with the NCEP global spectral model (GSM) used in the reanalysis. There

are many geographic similarities. There are a few differences, though, mainly because the reanalysis has a source

(artificial) of water from a seasonally varying damping

(forcing) term, which affects the surface-water budget. A

number of climatological simulations and sensitivity experiments with the latest NCAR community climate model

coupled to a sea-ice mixed-layer ocean model (Roads et

al. 1998b,c,d) were compared to the NCEP reanalysis and

each other. In addition to a control run forced by observed

sea-surface temperatures for the period 1950-1994, there

have been a number of 20-year CO2 simulations developed, ranging from concentrations of 100 ppm to 3000

ppm. We are also beginning to compare precipitation measurements from GPCP and ultimately from TRMM with

these simulations and the reanalysis.

We are also investigating the relative impacts of local influences (e.g., soil moisture, land cover) versus farfield effects (e.g., SST anomalies) on warm-season precipitation over the central U.S. GCIP region using NCAR’s

Climate System Model (CSM), NCEP and DAO reanalyses, and available observations (Oglesby et al. 1998,

Robertson et al. 1998). Initial findings suggest that remote atmospheric forcings produce a clear response in

soil-moisture anomalies over the GCIP region (through

changes in the structure of the large-scale quasi-stationary wave structure) and that local effects (particularly precipitation) have a clear diagnostic relationship with soilmoisture anomalies.

Use of Satellite Data

This project will make use of current and emerging observational data sets from NASA’s EOS and pre-EOS missions. Global observations of precipitation from GPCP,

MSU, and SSM/I are to be used in documenting interannual variability of regional precipitation and, along with

radiation, to serve as a means for inferring anomalous

thermal forcing to radiation, heat, and moisture budgets.

ERBS TOA fluxes and SRB radiative flux components

are being used to document the gross radiative behavior

over continents and subregions such as the Mississippi

basin. Over land the ERBS fluxes are used as a means to

check the net horizontal flux divergence of moist static

energy in reanalyses. Although soil moisture is not directly observed from space, we are using proxies such as

skin-temperature anomalies from the TOVS Path-A products and the SRB radiative components to assess diagnosed soil moisture. The Schnur/Lettenmaier data set and
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 293

several GEWEX Soil Wetness Products which used observed precipitation and meteorology to drive hydrologic

models are to be scrutinized in this way.

A preliminary evaluation of these combined data

sources has shown the ability of the remotely sensed data

to capture anomalous hydrologic events over the Mississippi basin during the period 1983 to 1991. Lagged surface response to atmospheric vertical motion and resulting precipitation suggests that quantitative use can be

made of these data sets. Water vapor from the NVAP

project and from individual TOVS and SSM/I algorithms

will be used to critique moisture-budget diagnostics and

to infer vertical motions. Global observations of precipitation provided through GPCP and water vapor provided

through NVAP have already been used to validate watervapor cycling rates, defined as column-integrated water

vapor/precipitation rate. As shown by Roads et al. (1998b),

the smallest cycling rate occurs for the satellite-based observations. The cycling rate is a bit higher for the NCEP

reanalysis and quite a bit higher for each of the CCM3

simulations. However, there are strong seasonal similarities among the observations, reanalysis, and CCM3 simulations; the cycling rate is largest during the boreal winter

and smallest during the boreal summer. This seasonal

variation is similar to what occurs in changed-CO2 experiments in that the cycling rate decreases with increasing CO2. This decrease is due to the large increase in atmospheric moisture relative to smaller increases in precipitation.

Participation in Field Programs

This project is not directly involved in any field campaigns. However, analysis of in situ and remotely sensed

data sets for the purpose of checking GCM model performance and cross-checking of regional and global data sets

will be done.

Principal Investigator

John O. Roads

John Roads received a Ph.D. from M.I.T. in 1977 and is

currently based at the Scripps Institution of Oceanography at the University of California, San Diego, where he

is director of the Experimental Climate Prediction Center. He is a member of the NAS/NRC GEWEX panel and

has been involved with GCIP since its inception.

Co-Investigators

Robert J. Oglesby - Purdue University

Susan Marshall - University of North Carolina, Charlotte

Franklin R. Robertson - NASA/Marshall Space Flight

Center

References

Oglesby, R.J., S. Marshall, J.O. Roads, and F.R.

Robertson, 1998: Diagnosing energy and water budgets

for GCIP from models and observations. GCIP Mississippi River Climate Conference. St. Louis, MO, June 8-

12.

Roads, J.O., S.-C. Chen, M. Kanamitsu, and H. Juang,

1998a: Surface water characteristics in the NCEP Global

Spectral Model and Reanalysis. J. Geophys. Res., in press.

Roads, J., S. Chen, S. Marshall, and R. Oglesby, 1998b:

Atmospheric moisture cycling rates. GEWEX News, in

press.

Roads, J.O., S.-C. Chen, S. Marshall, R.J. Oglesby, and

F.R. Robertson, 1998c: Sensitivity of the water budget

over the Americas to increased CO2. Climate of the Americas, Merida, Venezuela, March 16-22.

Roads, J.O., S.-C. Chen, S. Marshall, R.J. Oglesby, and

F.R. Robertson, 1998d: Sensitivity of the water budget

over the Mississippi to increased CO2. GCIP Mississippi

River Climate Conference. St. Louis, MO, June 8-12.

Robertson, F.R., J.O. Roads, R.J. Oglesby, and S.

Marshall, 1998: Anomalies in coupled energy and water

budgets over the Americas during the Northern Hemisphere warm season. GCIP Mississippi River Climate

Conference. St. Louis, MO, June 8-12.
294 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The Development and Use of a FourDimensional Atmospheric-Ocean-Land Data

Assimilation System for EOS

Principal Investigator – Richard B. Rood

Science Background

This investigation will develop a research-quality, 4-dimensional atmosphere-ocean-land data-assimilation system for EOS. The data assimilation melds observations

with a model prediction to provide a dynamically consistent depiction of the Earth-atmosphere system. It has the

unique ability to produce estimates of unobserved quantities.

Data-assimilation approaches are used throughout

science and engineering. Information from the observations is combined with information from the model using

objective analysis techniques. A classic example of the

assimilation process is the parallel development of the

theory of planetary motions and the discovery of the new

planets. For example, the outer planets were hypothesized

because a high degree of confidence was placed in the

equations of motion (i.e., the model, and new objects were

needed to explain the observed perturbations in the orbits

of the known planets). In traditional NASA culture, dataassimilation techniques are crucial to orbit determination

and were essential to navigation in the Apollo flights.

Because of the large number of observations and the

complexity of Earth-system models, Earth-science data

assimilation provides many difficult challenges. The ability of a data-assimilation technique to integrate the diverse measurements of the observing program motivates

addressing these scientific and computational challenges.

The data-assimilation system: 1) organizes the observations from many diverse instrument sources and measurement times into a single useful data product; 2) complements the observations by propagation of information

from observed into unobserved regions and times; 3) provides estimates of expected values of the observations

with which to assess data and instrument quality; 4) provides special products for environmental-assessment studies; and 5) supplements the observations by providing estimates of quantities that are difficult or impossible to observe.

Science Goals

The goals of this investigation are to produce an assimilation analysis to ensure that the maximum information

is gained from the EOS and other observations, and to set

the foundation for future Earth system models. The development will be a sequence of incremental builds of

the Goddard Earth Observing System (GEOS) Data Assimilation System. Continual research into numerical and

theoretical techniques and associated Earth Science process studies will ensure that the developed system meets

the needs of EOS. Analyzing historical and new data sets

available in the pre-launch phase of EOS will serve to

define the basis for NASA’s assimilation system. Application from these pre-launch products will define the evolution of the data-assimilation system. The assimilated

data produced in the pre-launch period will be made available to the broad science community to assure infusion

of relevant diverse applications into the development process. A commitment is made to continued reanalyses of

these data sets to quantify the impact of the heterogeneity

of the input data stream on interannual signals.

Current Activities

The investigation performs research into all aspects of 4-

dimensional data assimilation, including satellite retrievals, data quality control, error propagation, objective

analysis, and all component models of the Earth system.

Data from satellites such as UARS, TRMM, and ADEOS

are being used to assess the utility of new data types, such

as marine-surface wind and precipitation data. Initial studies concentrate on meteorology, with an emphasis on the

hydrological cycle and seasonal and interannual variability. A strong emphasis is also placed on global transport

processes and atmospheric chemistry. Near-term development will emphasize land-surface and ocean-surface

processes.

Significant Events

• Production of 1980-1994 global gridded data set of tropospheric meteorological and hydrological quantities

with version one of the GEOS Data Assimilation System. This product is distributed by the Goddard DAAC.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 295

• Production of 1987-1995 gridded data set of marine

surface winds using SSM/I wind-speed observations.

This product is distributed by the JPL DAAC.

• Production of a 1991-current global gridded data set of

tropospheric and stratospheric meteorological and hydrological quantities. These data sets have been extensively used in international ozone assessment studies.

• Production of near-real-time forecasts to help target

NASA ER-2 and DC-8 aircraft in SPADE, ASHOE/

MAESA, STRAT, POLARIS, and SONEX missions.

Also produced data sets to support the ATLAS mission

on the space shuttle.

• Data-impact studies on ADEOS that show potential of

NSCAT to improve weather forecasting and marine

storm forecasting.

• Data-impact studies of SSM/I and TMI show the ability of precipitation observations to reduce biases in key

radiative climate quantities.

• Provision of numerical algorithms to Code R Global

Modeling Initiative for NASA and IPCC assessments

of the potential impact of aircraft emissions on atmospheric pollution.

• Provisions of the Physical-space Statistical Analysis

System to the U.S. Navy, CPTEC (Brazil) with plans

for more national and international collaborations.

Development and Products

Incremental versions of the GEOS Data Assimilation

System will be built to support NASA missions. The current version supports the CERES instrument on TRMM.

For Terra the GEOS system will be developed specifically to improve tropospheric water and near-surface meteorological conditions. The Terra system will be used to

perform a consistent updated reanalysis from 1979 to current time. Two research efforts, focused on use of MOPITT observations, are being pursued in collaboration with

Duke University and NCAR. For PM-1 much of the focus will be to perform quick evaluation of the impact of

AIRS observations on the assimilated data products. The

data-assimilation system is undergoing continuous improvement to provide increasingly more-accurate representations of transport processes for both tropospheric and

stratospheric chemistry applications. Finally, products are

being provided to improve the quality of retrievals from

a broad range of remote-sensing instruments.

Assimilation products to be made available include the

following 4-dimensional gridded fields:

• Atmosphere: wind, temperature, moisture, geo-potential, turbulence, radiative heating/flux, clouds (amount,

type, mass flux, and detrainment), precipitation, sensible and latent heat flux, and planetary boundary layer

depth.

• Surface (land and ocean): albedo, temperature, pressure, evaporation, roughness (drag and wind stress),

snow depth, soil moisture, and vegetative moisture.

• Surface (ocean only): salinity, currents, sea state, and

sea-level height.

Principal Investigator

Richard B. Rood

Richard Rood obtained a Ph.D. in Meteorology from

Florida State University in 1982. Since then, he has been

at NASA’s Goddard Space Flight Center (GSFC). He has

been involved in the development of atmospheric general circulation models, and three-dimensional chemistry

and transport models. He has pioneered the use of winds

and temperatures derived by data assimilation to study

atmospheric transport processes. In 1992, he was appointed Head of the Data Assimilation Office at GSFC–

the only center of data-assimilation research that is not

maintained within an operational weather-forecasting center. The Data Assimilation Office produces research-quality data sets to study Earth system processes and global

change.

Co-Investigators

Donald R. Johnson - University of Wisconsin

The following are from NASA/Goddard Space Flight

Center:

Robert M. Atlas

J. Ray Bates

Stephen Cohn

Michael Fox-Rabinovitz

H. Mark Helfand

Arthur Hou

David J. Lamich

Siegfried Schubert

Joel Susskind

Lawrence Takacs
296 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The following are from NOAA/National Meteorological

Center:

Wayman E. Baker

John Derber

Eugenia Kalnay

Masao Kanamitsu

Ants Leetmaa

James Miller

James Pfaendtner

Chester F. Ropelewski

References

Daley, R., 1991: Atmospheric Data Analysis. Cambridge

University Press, 457 pp.

DAO, 1996: Algorithm Theoretical Basis Document, Data

Assimilation Office, Goddard Space Flight Center.

Schubert, S., R. Rood, and J. Pfaendtner, 1993: An assimilated data set for earth science applications. Bull.

Amer. Meteor. Soc., 74, 2331-2342.

Cohn, S.E., 1997: An introduction to estimation theory.

J. Meteor. Soc. Japan, 75, 257-288.

National Research Council, 1991: Four-Dimensional

model assimilation of data. National Academy Press.

Investigation URL

http://dao.gsfc.nasa.gov

Assimilated atmospheric winds at 10 meters from the Goddard Earth Observing System Data Assimilation System with

1-degree horizontal resolution showing an intense low-pressure system off Nova Scotia and Newfoundland at 18 Z

November 18, 1991.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 297

Impacts of Interannual Climate Variability on

Agricultural and Marine Ecosystems and

Fisheries

Principal Investigator – Cynthia Rosenzweig

Science Background

In 1997, Pacific sea-surface temperatures were the highest on record, indicating an El Niño event of very large

proportions. What are the agricultural consequences of

El Niño events and how can scientists help in coping with

them? Our EOS Interdisciplinary Science Team brings

together six groups in order to create an ‘end-to-end’

analysis of El Niño predictions and their use in food production: Oceanographers who develop El Niño forecast

models; atmospheric scientists who use global climate

models (GCMs); remote-sensing specialists; agronomists

whose tools include dynamic crop-growth models; marine ecologists; and economists.

The basis of the study is a set of linked regional analyses in places where El Niño events have strong or potentially important impacts on crops and fisheries. The study

regions are the U.S. Corn Belt, Zimbabwe, the Brazilian

Nordeste and Cerrados, and Southeastern South America

(including parts of Brazil, Argentina, and Uruguay). The

fishery study regions are the tropical Atlantic and the tropical Pacific regions. In each study region, we seek to understand the nature and geography of the agricultural systems and then to quantify the relationships among seasurface temperatures, the phases of the El Niño cycle, climate variables (especially precipitation and temperature),

and crop or fishery yields, production, and economic

value.

Science Goals

The objectives of the project are to develop a coordinated

methodological framework for assessment and prediction

of the impacts of large-scale seasonal-to-interannual climate fluctuations, especially El Niño Southern Oscillation (ENSO) events, on important food-producing systems around the world. An additional objective is to improve the timing, geographic specificity, and accuracy of

forecasts of regional climate anomalies and their impacts

on agricultural and marine ecosystems. Furthermore, this

project strives to investigate the potential for mitigation

of negative climate-variability impacts on food production.

Current Activities

The challenge for this project is to make the connections

among the research components to create an integrated

whole, contributing to the practical application of research

relating to the provision of world food supply. To that

end, we are focusing on establishing methodological linkages among the modeling tools of each group. For example, we are testing the use of global GCM output in

the dynamic process crop-growth models, and evaluating

the agronomic feasibility of adaptations suggested by the

economic analysis. A set of ensemble GCM runs was carried out using global observed sea-surface temperatures

for the 1979-present time period and other climate

forcings. SSTs for 1979-1988 were taken from the AMIP

data sets, and those for subsequent years from the blended

analysis approach of Reynolds (1988), already in-house

at GISS. Results show that, in general, the GISS GCM

simulates regional ENSO climate teleconnections adequately. Furthermore, the GCM is particularly helpful

in understanding the climate dynamics contributing to

regional variability. This is a key element in improving

the use of regional climate predictions.

Use of Satellite Data

Each research area has a satellite data component.

ENSO Prediction: This work examines the ability of

TOPEX data, with its complete spatial but coarse time

resolution, to capture propagating features, especially the

equatorial Kelvin waves critical to the ENSO mechanism.

The results show the TOPEX view to be comparable in

quality to an in situ array of echo sounders, and adequate

for prediction studies.

GCM: A microwave postprocessor to the 9-vertical-layer

Goddard Institute for Space Studies (GISS) GCM has

analyzed simulated climates from the ensemble SST runs.

This microwave radiative transfer model calculates the

brightness temperature that would be observed by the

MSU radiometer if it were orbiting the simulated GCM

atmosphere. The MSU mean climatology of 1982-1991

has been used to examine the GCM’s mean annual cycle;
298 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

the MSU regional, interannual variability; the GCM’s internal variability; and the MSU time series of the GCM’s

thermodynamic response to observed SST.

Remote Sensing: The GIMMS component of the IDS team

has produced a new global NDVI data set for the period

of mid-1981 through 1997 from NOAA-7, NOAA-9,

NOAA-11, and NOAA-14 data. Analysis of NDVI IDS

data set is continuing to quantify ENSO influences on

agricultural responses.

Agriculture: The El Niño signal is less pronounced in the

U.S. Cornbelt than in regions such as Australia or Indonesia. Nonetheless, the ENSO signal is present, and distinguishable using coarse-scale Advanced Very High

Resolution Radiometer (AVHRR) imagery.

Maximum monthly (AVHRR) Normalized Difference

Vegetation Index (NDVI) values in the agricultural areas

of the U.S. Cornbelt were summed over the growing season (June, July and August). The growing-season NDVI

values were averaged at the Agricultural Statistics Districts (ASD) level and grouped by ENSO event. The seasonal profile of agriculture in the U.S. Cornbelt is preserved at the 8-km scale. On average, La Niña-year NDVI

values are lower throughout the growing season than during either an El Niño or a neutral year.

To determine the spatial extent of ENSO impacts on

agricultural areas in the U.S. Cornbelt, two methods of

analysis were employed. In the first case, each year’s

NDVI values were related to the maximum NDVI value

in the time series. In the second case, NDVI values during ENSO events values were compared with the 17-year

mean. In both cases, the spatial extent of ASD regions

sensitive to ENSO events is evident.

In general, corn yields during El Niño years are higher

than average while yields during La Niña years are lower

than average. Negative impacts during La Niña years on

corn yields in the U.S. Cornbelt are more severe than the

positive impacts of El Niño years (Phillips et al., 1996).

Growing-season NDVI anomalies and yield anomalies for

the time period in question are significantly correlated.

Marine Ecosystems: Ocean-color data from CZCS is being used to infer the effects of the Indonesian throughflow

and ENSO on ecosystems in the Indo-Pacific basin.

Field Programs

We are working with a small group of experts and stakeholders from each study area to collaborate with us and

advise on the project. These include climatologists,

agronomists, economists, regional agricultural planners,

and commodity group representatives.

Principal Investigator

Cynthia Rosenzweig

Cynthia Rosenzweig is a Research Scientist at NASA/

Goddard Institute for Space Studies and Adjunct Senior

Research Scientist at Columbia University’s Earth Institute. She earned advanced degrees from Rutgers University and the University of Massachusetts. Her research

focuses on the potential impacts of environmental change,

including global warming and El Niño events, on agricultural production at regional, national, and global scales.

She is the co-author with Daniel Hillel of the new book,

Climate Change and the Globe Harvest, published in 1998

by Oxford University Press.

Co-Investigators

Tony Busalacchi - NASA/Goddard Space Flight Center

Mark Cane - Lamont Doherty Earth Observatory

David Rind - NASA/Goddard Institute for Space Studies

Jim Tucker - NASA/Goddard Space Flight Center

References

Druyan, L.M., K.P. Shah, M.A. Chandler, and D. Rind,

1998: GCM hindcasts of SST forced climate variability

over agriculturally intensive regions. Climatic Change,

in press.

Myneni, R.B., C.D. Keeling, C.J. Tucker, G. Asrar, and

R. Nemani, 1997: Evidence from satellite data for northern high-latitude increased photosynthetic capacity from

1982-1990. Nature, 386, 698-705.

Myneni, R.B., S.O. Los, and C.J. Tucker, 1996: Satellitebased identification of linked vegetation index and seasurface temperature anomaly areas from 1982-1990 for

Africa, Australia, and South America. Geophys. Res. Lett.,

23, 729-732.

Phillips, J.G., M.A. Cane, and C. Rosenzweig, 1997:

ENSO, seasonal rainfall patterns and maize yield variability in Zimbabwe. Agric. and Forest Meteor., 90, 39-

50.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 299

Phillips, J.G., B. Rajagopalan, M.A. Cane, and C.

Rosenzweig, 1999: The role of ENSO in determining climate and maize yield variability in the U.S. Cornbelt. Intl.

J. Climatology, in press.

Shah, K.P., and D. Rind, 1999: Comparison of upper tropospheric and lower stratospheric temperatures: MSU,

radiosonde, CIRA, and NCEP/NCAR reanalysis

climatologies. Mon. Wea. Rev., in press.

Investigator URL

http://www.giss.nasa.gov
300 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

POLar Exchange at the Sea Surface (POLES)

Principal Investigator – D. Andrew Rothrock

Science Background

POLES is a broad investigation into the role of polar regions in the global energy and water cycles, and the atmospheric, oceanic, and sea-ice processes that determine

that role. The primary importance of our investigation is

to show how these polar processes relate to global climate.

Science Objectives

The objectives of our current research are:

• Determine the heat and moisture balance of the polar

atmosphere, including the surface heat balance, radiation to space, and the transport of heat and moisture

into the polar atmosphere from mid-latitudes.

• Determine more accurately the amounts of polar clouds

and their effect on the surface and top-of-atmosphere

radiative balance.

• Determine the turbulent surface fluxes of heat, momentum, and moisture and how they and radiative fluxes

interact together with the atmospheric boundary layer

and determine boundary-layer stability.

• Determine a “plumbing diagram” for heat and freshwater in the Arctic Ocean, their seasonal/interannual

variabilities, and their impact on water-mass formation

and the global thermohaline circulation.

• Determine the processes controlling sea-ice mass and

momentum balance and extent, and their role in polar

air-sea exchange.

Current Activities

The Atmosphere and Surface Fluxes—The atmospheric

advection of energy into the Arctic from lower latitudes,

and the deposition of that energy within the Arctic provides a primary link between the Arctic and the global

climate system. We are analyzing an 18-year record of

TOVS Polar Pathfinder temperature and moisture profiles, adding NCEP winds, and producing a climatology

of heat and moisture advection into the Arctic. We are

exploring the variability of these transports and their connection with hemispheric atmospheric oscillations.

Radiative fluxes dominate the surface-energy budget over snow and ice throughout much of the year and in

most high-latitude regions. We are producing critical data

sets on cloud properties and their effect on radiative forcing of the sea-ice cover and are intercomparing these radiative-flux data sets with those commonly used in ice

models and those computed in the NCEP and ECMWF

reanalyses. We have created and analyzed a 2-m air-temperature data set from buoy and station data and have reported a warming trend for May and June: an earlier onset of the summer season.

The Ocean and Sea Ice – Significant changes in Arctic

climate have been observed in the late 1980s and 1990s.

Our models show that Atlantic Water inflow to the Arctic

Ocean has increased in the early 1990s during the positive phase of the North Atlantic Oscillation, and that this

increase enters mainly via the Barents Sea. We have discovered a remarkable and related reduction in the extent

of the Cold Halocline Layer of the Arctic Ocean, as observed by both icebreaker and submarine cruise data.

Ice-Ocean Model Development and Testing – Ice-ocean

models are an important component of global climate

models. We are improving ice-ocean models, testing them,

and making them more computationally efficient. We have

undertaken a comparison of thickness as modeled and as

observed by submarines. Such tests provide a new and

crucial measure of performance for sea-ice models. We

have constructed a global ice-ocean model that couples

the latest GFDL Modular Ocean Model (MOM2) with

our sea-ice model and our latest numerical scheme for

ice dynamics, which is an order of magnitude faster than

previous schemes. Together with our existing regional iceocean model for the north polar ocean, the global iceocean model allows us to examine the effects of globalscale ocean circulation and poleward oceanic heat transport on the behavior of the ice-ocean systems in both polar regions.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 301

Algorithm Development, Data Set Production, and Validation – We have put considerable energy into improving

algorithms for polar cloud and surface variables, and producing data sets based on these algorithms in collaboration with the AVHRR and TOVS Polar Pathfinders. Our

strategy is to intercompare cloud and radiation products

from AVHRR, and from TOVS, with each other and with

available in situ and buoy data sets. By the end of this

year we will have a full 18 years of TOVS Polar Pathfinder data and 14 years of AVHRR Polar Pathfinder data.

As early products have been produced, we have worked

to improve the performance of our algorithms and the efficiency of radiation codes by replacing the radiative transfer code Streamer with a neural network FluxNet.

Principal Investigator

D. Andrew Rothrock

Drew Rothrock earned his Ph.D. from the University of

Cambridge in 1968, studying fluid mechanics. Since 1970,

he has been affiliated with the University of Washington,

where he is a Principal Research Scientist in the Applied

Physics Laboratory and an Associate Research Professor

in the School of Oceanography. His research interests include sea-ice dynamics and kinematics, and the remote

sensing of polar geophysical processes with active and

passive microwave, and thermal and visible satellite sensors.

Co-Investigators

Roger Barry - University of Colorado

Robert Brown - University of Washington

Frank Carsey - Jet Propulsion Laboratory

Jeffrey Key - Boston University

Seelye Martin - University of Washington

Michael Steele - University of Washington

Dale Winebrenner - University of Washington

References

Francis, J.A., 1997: A method to derive downwelling longwave fluxes at the Arctic surface from TIROS operational

vertical sounder data. J. Geophys. Res., 102, 1795-1806.

Key, J.R., J. Collins, C. Fowler, and R. Stone, 1996: Highlatitude surface temperature estimates from thermal satellite data. Rem. Sens. Environ., 61, 302-309.

Martin, S., E. Munoz, and R. Drucker, 1997: Recent observations of a spring-summer surface warming over the

Arctic Ocean. Geophys. Res. Lett., 24, 1259-1261.

Rothrock, D.A., and J. Zhang: Surface downwelling radiative fluxes: Ice model sensitivities and data accuracies. Bull. Amer. Meteor. Soc., in press.

Schweiger, A.J., and J. Key, 1997: Estimating surface radiation fluxes in the Arctic from TOVS HIRS and MSU

brightness temperatures. Intl. J. Rem. Sens., 18, 955-970.

Steele, M., and T. Boyd: Retreat of the cold halocline layer

in the Arctic Ocean. J. Geophys. Res., in press.

Steele, M., J. Zhang, D. Rothrock, and H. Stern, 1997:

The force balance of sea ice in a numerical model of the

Arctic Ocean. J. Geophys. Res., 102, 21,061-21,079.

Thomas, D., The quality of sea ice velocity estimates. J.

Geophys. Res., in press.

Zhang, J., D.A. Rothrock, and M. Steele: Warming of the

Arctic Ocean by a strengthened Atlantic inflow: model

results. Geophys. Res. Lett., submitted.

Investigation URL

http://psc.apl.washington.edu/poles/
302 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Using Multi-Sensor Data to Model Factors

Limiting Carbon Balance in Global Arid and

Semiarid Land

Principal Investigator – David S. Schimel

Science Background

This Interdisciplinary Science investigation (IDS) is investigating the ecology of global ecosystems, focusing

on arid land systems where climate and land use can produce very rapid changes in both ecosystem structure (the

abundance and spatial distribution of woody, grass, and

desert vegetation) and function (plant and animal productivity, trace gas and carbon exchange with the atmosphere,

hydrology). We are also investigating the response of ecosystems regionally and globally to interannual climate

variability using field studies, modeling and remote sensing to determine, observationally, ecosystem responses

to climate as a basis for projecting effects of longer term

climate changes. The IDS is based on the use of

multisensor remote-sensing techniques, and has developed

algorithms that use MODIS, MISR, Landsat, and ASTER

data synergistically.

Science Goal

Quantification of the impacts of land use and climate on

ecosystems of the Earth’s arid and semiarid zones

Current Activities

Key principal activities are: 1) the analysis of Pathfinder

AVHRR data sets for interannual variability in ecosystems and linking that variability to changes in atmospheric

CO2, and 2) development of techniques utilizing radiative-transfer modeling to retrieve land-surface characteristics.

Use of Satellite Data

The investigation is using satellite data in three main ways.

First, in Northern China and Mongolia, we are mapping

land cover and land-cover change to identify trends in

management as part of a study of grassland ecosystem

function. This subproject emphasizes Landsat. Second,

we are using Landsat and AVHRR data in a pilot study

prototyping our radiative-transfer inversion algorithms for

retrieving light interception by foliage and litter, phenology, and albedo. This work focuses on regional studies in

West Africa, the southwestern U.S., and Brazil. Third, we

are using Pathfinder AVHRR to analyze interannual variability in NDVI in relation to temperature. This work suggests that northern ecosystems have high NDVI in warm

years, while arid ecosystems have low NDVIs in warm

years; cold years produce the opposite responses. There

are also lagged correlations of NDVI with temperature

that are suggestive of nutrient-cycling feedbacks.

Participation in Field Activities

The investigation is carrying out field studies in the southwestern U.S. and northeastern Brazil aimed at collecting

the ground optical measurements needed to operate and

validate radiative-transfer models for interpreting satellite data.

Principal Investigator

David S. Schimel

David Schimel is a senior scientist at the National Center

for Atmospheric Research and a member of the College

of Natural Resources, Colorado State University.

Schimel’s research focuses on the ecological control of

terrestrial biogeochemistry. He has reported extensively

on the role of nutrient cycling in regulating terrestrial ecosystem processes, on the global carbon cycle, and on the

development of ecosystem models. He served as Convening Lead Author for the IPCC assessment of the carbon cycle. Schimel is also active in the development of

techniques for studying large-scale processes in ecosystems, including the use of remote sensing.

Co-Investigators

Steve Archer - Texas A&M University

Brian Curtiss - University of Colorado

Alex Goetz - University of Colorado
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 303

Timothy Kittel - NCAR

William Parton - Colorado State University

Carol Wessman - University of Colorado

References

Braswell, B.H., D.S. Schimel, E. Linder, and B. Moore

III, 1997: The response of global terrestrial ecosystems

to interannual temperature variability. Science, 278, 870-

872.

Braswell, B.H., D.S. Schimel, J.L. Privette, B. Moore III,

W.J. Emery, E.W. Sulzman, and A.T. Hudak, 1996: Extracting ecological and biophysical information from

AVHRR optical data: an integrated algorithm based on

inverse modeling. J. Geophys. Res., 101, 23,335-23,348.

Schimel, D.S., B.H. Braswell, and VEMAP Participants,

1997: Continental scale variability in ecosystem processes:

models, data and the role of disturbance. Ecological Monographs, 67, 251-271.

Investigation URL

http://kiwi.atmos.colostate.edu/ids/
304 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Investigation of the Chemical and Dynamical

Changes in The Stratosphere

Principal Investigator – Mark R. Schoeberl

Science Background

This interdisciplinary science investigation focuses on

analyzing stratospheric and tropospheric chemical and dynamical changes using EOS instruments and current satellite and aircraft data sets.

Complex and subtle chemical changes are occurring

within the Earth’s atmosphere, mostly as a result of

changes in the surface emission of important trace gases.

This investigation is primarily interested in the response

of ozone to these trace-gas changes, changes in stratospheric ozone as a result of increasing human-made chlorine, potential changes due to aircraft emissions, and tropospheric ozone changes due to biogenic activity such as

land-use changes, industrial pollutants, and biomass burning. To separate natural changes in trace gases from those

generated by human activity, high-quality data sets are

needed for analysis. Interpretation of the changes requires

complex chemical models. In addition to analysis of the

data, this investigation is responsible for the production

and quality of chemical data products produced by the

EOS Data Assimilation effort.

Science Goal

The scientific goal of the investigation is to isolate natural from anthropogenic chemical changes in the Earth’s

atmosphere to determine their effects on ozone and to

assess radiative and dynamical feedbacks.

Current Activities

The data-analysis effort supports the development and

validation of models being created as part of this investigation, while the modeling effort supports interpretation

of the data. There are three major activities within this

group: model development, satellite and aircraft data

analysis, and chemical assimilation/data-set generation.

Model development – This investigation has developed two models. The first is a fully interactive 2-dimensional chemical/dynamical model. This model is being

used to examine the dynamical feedbacks associated with

ozone loss and the impact of natural and man-made pollution. Because of the computational cost of fully 3D interactive chemical models, the 2D interactive model is

the only way we can currently examine the interaction

between radiative feedbacks and chemical depletions. The

2D model is being used to investigate the impact of CO2

increase on stratospheric ozone, the effect of volcanic

eruptions, and the radiative feedbacks of sub-visible cirrus at the tropopause.

We have also developed a Lagrangian Chemical

Model which, along with the off-line 3D Chemical Model

(partially supported under this investigation), is being used

to investigate the evolution of the annual polar-ozone

depletions and to analyze aircraft observations. Using the

Lagrangian model we have been able to simulate the development of the Antarctic ozone hole, and have predicted

its evolution under different anthropogenic chlorine-loading scenarios.

Analysis of satellite and aircraft data – Our second

major activity involves the analysis of satellite and aircraft data with regard to model validation and increasing

our understanding of the chemical processes within the

stratosphere. We are currently focusing most of our efforts on analysis of Upper Atmosphere Research Satellite

(UARS) data and data from the latest series of aircraft

expeditions. Using the trajectory-mapping technique, and

reverse domain filling (RDF) developed under this Interdisciplinary Science investigation (IDS), we have been

able to utilize meteorological constraints on trace-gas

measurements in an optimal way. This IDS also maintains a ‘user run’ trajectory-model service for the community. In 1997, there were over 100 users with over 7000

accesses for this service.

Analysis of the UARS data is especially important

for this investigation since the UARS instruments,

CLAES, ISAMS, and MLS are progenitors of the EOS

CHEM instruments (HIRDLS, MLS). We also continue

with our analysis of the TOMS data with respect to the

size and variability of the polar-ozone depletions. We are

also analyzing the European GOME data set. CHEM will

fly the Dutch-provided OMI, which is similar to TOMS

and GOME in measurement capability. We have also done

extensive analysis of the CRISTA data set. CRISTA, which

was flown on the Shuttle, is a high-horizontal-resolution

limb sounder. CRISTA data provide a good test of our

analysis methods for HIRDLS data.

Members of our team have been the project scientists for four aircraft expeditions: STRAT, TOTE/VOTE,

POLARIS, SONEX. We will also be involved in the 1999/

00 Sage III validation mission (SOLVE).
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 305

Chemical assimilation/data-set generation – The

third major activity of this investigation is the development of meteorological and chemical data sets for EOSDIS. Sixteen years of NMC global stratospheric data have

been analyzed, and balanced winds and potential vorticity have been produced and transferred to the Goddard

DAAC. Under development is a chemical assimilation

model which will directly assimilate satellite chemical

measurements. Here we work in close collaboration with

the EOS Data Assimilation Office. We are responsible

for stratospheric meteorological data quality and the quality control of the chemical assimilation system. We are

currently using UARS data as a test of that system and

have generated prototype data sets using UARS CLAES

nitrous oxide measurements and HALOE methane data.

Principal Investigator

Mark Schoeberl

Mark Schoeberl received his Ph.D. from the University

of Illinois in 1976. He has 23 years of research experience in atmospheric dynamics, stratospheric physics, and

numerical modeling. He is the author or co-author of more

than 130 scientific papers and has been affiliated with

NASA/Goddard Space Flight Center since 1983. He is

the Upper Atmosphere Research Satellite Project Scientist, and he was co-project scientist for the TOTE/VOTE

aircraft mission. Within his field of research, he has

chaired multiple conferences and committees, and has

served in an editorial capacity for several journals. He is

a recipient of the NASA Exceptional Scientific Achievement and Outstanding Leadership Medals . He is a fellow

of the American Geophysical Union, fellow of the American Meteorological Society, and fellow of the American

Association for the Advancement of Science. He was

elected president of the American Geophysical Union’s

Atmospheric Sciences Section for the term 1998-00.

Co-Investigators

Steve E. Cohn - NASA/Goddard Space Flight Center

Anne R. Douglass - NASA/Goddard Space Flight Center

Marvin A. Geller - State University of New York-Stony

Brook

James Gleason - NASA/Goddard Space Flight Center

Robert D. Hudson - University of Maryland-College Park

Charles H. Jackman - NASA/Goddard Space Flight Center

Leslie R. Lait - Raytheon ITSS Corporation

Paul A. Newman - NASA/Goddard Space Flight Center

Richard B. Rood - NASA/Goddard Space Flight Center

Joan E. Rosenfield - General Sciences Corporation

Richard S. Stolarski - NASA/Goddard Space Flight Center

Anne M. Thompson - NASA/Goddard Space Flight Center

References

Douglass, A.R., M.R. Schoeberl, R.S. Stolarski, J.W. Waters, J.M. Russell III, and A.E. Roche, 1995: Interhemispheric differences in springtime deactivation of vortex

ClO. J. Geophys. Res.

Morris, G.M., M.R. Schoeberl, L. Sparling, P.A. Newman,

L.R. Lait, L. Elson, J. Waters, R. Suttie, A. Roche, J.

Kumer, and J.M. Russell III, 1995: Trajectory mapping

and applications to data from the Upper Atmosphere Research Satellite. J. Geophys. Res., 100, 16,491-16,505.

Newman, P., and M.R. Schoeberl, 1995: A reinterpretation of the data from the NASA stratosphere-troposphere

exchange project. Geophys. Res. Lett., 2501-2504.

Rosenfield, J.E., D. Considine, M.R. Schoeberl, and E.

Browell, 1998: The impact of subvisible cirrus clouds near

the tropical tropopause on stratospheric water vapor.

Geophys. Res. Lett., 25, 1883-1886.

Schoeberl, M.R., et al., 1996: The development of the

Antarctic ozone hole. J. Geophys. Res., 101, 20,909-

20,924.

Schoeberl, M.R., C.H. Jackman, and J.E. Rosenfield,

1998: A Lagrangian estimate of aircraft effluent lifetime.

J. Geophys. Res., 103, 10,817-10,825.

Schoeberl, M.R., and P.A. Newman, 1998: A multiple level

trajectory analysis of vortex filaments. J. Geophys. Res.,

100, 25,801-25,815.

Sparling, L.C., A.R. Douglass, and M.R. Schoeberl, 1998:

An estimate of the effect of unresolved structure on modeled ozone loss from aircraft observations of ClO.

Geophys. Res. Lett., 305-308.

Thompson, A.M., et al., 1996:Where did tropospheric

ozone over southern Africa in the tropical Atlantic come

from in October 1992: Insights from TOMS, GTE TRACE

A, and SAFARI 1992. J. Geophys. Res., 101, 24,251-

24,278.

Investigation URL

http://hyperion.gsfc.nasa.gov/EOS/EOS.html
306 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Interdisciplinary Determination of Snow

Accumulation Patterns on the Greenland Ice

Sheet: Combined Atmospheric Modeling and

Field and Remote Sensing Studies

Principal Investigator – Christopher A. Shuman

Science Background

Ice sheets play a critical role in the global climate system. Not only do they currently store enough water to

raise global sea level 10s of meters, but they affect the

climate system directly and even act as a recorder of climate system temperature and atmospheric composition.

This Interdisciplinary Science investigation focuses on

improving the determination of the incoming mass flux

to the Greenland Ice Sheet as a means of more-accurately

assessing polar mass balance as suggested by the U.S.

Global Change Research Program (USGCRP).

Both direct glaciological and indirect meteorological assessments provide the necessary means of assessing polar mass balance, albeit with their relative costs and

limitations. This proposal will contemporaneously integrate improved meteorological and glaciological observations to produce an enhanced characterization of accumulation patterns over the Greenland ice sheet at multiple sites. Because this approach makes extensive use of

remote-sensing data, it is well-suited to the development

of EOS instruments and should facilitate long-term monitoring of polar ice. If this integrated approach is successful, it will, by extension, increase confidence in the indirect atmospheric-modeling approach that can be used to

predict precipitation/accumulation across the climatically

and politically sensitive Arctic region.

Science Goal

In this research, we propose to: 1) use a high-resolution

diagnostic-dynamic atmospheric model to obtain sub-seasonal and annual estimates of precipitation for specific

locations distributed over the Greenland ice sheet (NASA

project with PI David H. Bromwich); and 2) use a combination of high-resolution stable-isotope (d18O and dD)

profiling in numerous snow pits with comparisons to satellite brightness-temperature trends to document the

amount, rate, and timing of accumulation at the same locations. The resulting comparisons will assess the reliability of the atmospheric modeling approach to accumulation monitoring for ice-sheet mass-balance studies. This

will provide a critical data set for comparison to, and validation of, the hydrologic elements of global climate model

results. Additionally, through the collection and compilation of numerous high-resolution (> 20 samples per year)

stable-isotope profiles distributed across Greenland, a

database will be compiled which can be used to assess

issues critical to some paleoclimate variables.

Current Activities and Field Programs

Current activities are focused on the extensive database

of isotope profiles being provided by collaborators at the

Alfred Wegner Institut Für Polar Und Meeresforschung

from their North Greenland Traverse over the past several years as well as additional data from field expeditions to Greenland in the spring of 1997, 1998 and again

in 1999 (see figure on the following page). Once these

isotope and associated density profiles are obtained, they

will be compared to Special Sensor Microwave/Imager

(SSM/I) trends from equivalent time periods and accumulation amount, rate, and timing information will be

derived. These field- and remote-sensing-based accumulation assessments will be compared to the meteorological analysis results, currently being developed by David

H. Bromwich (BPRC-OSU), and an assessment of the

accuracy of their accumulation amount and timing information will be made.

Use of Satellite Data

The relationship of satellite passive-microwave brightness temperature (TB) to physical temperature is described

by the Rayleigh-Jeans approximation. In this approximation, satellite brightness temperature is the product of the

physical temperature of the near-surface snow multiplied

by its emissivity. In central Greenland, the daily average

37 GHz V brightness temperature trend is similar to the

isotope record from the approximate corresponding depth

interval of a sample snow pit. The similar trends of these

temperature indicators supports the assertion that stable

oxygen and hydrogen isotope ratios record temperature

variations in accumulating snow in central Greenland
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 307

Summit with relatively high frequency. Brightness-temperature data from an SSM/I 37-GHz V (0.81-cm wavelength) channel are available starting in July 1987. The

passive-microwave data used in this study will be obtained

from the National Snow and Ice Data Center. Temperature calibration of the 37-GHz V data will be based on

available AWS records. The EOS-era instrument, AMSRE, will improve the precision of this technique through

its improved spatial and spectral resolution.

Principal Investigator

Christopher A. Shuman

Christopher A. Shuman received M.S. and Ph.D. degrees

in Geology and Geosciences from the Pennsylvania State

University and was a postdoctoral researcher there and

with the National Research Council at NASA’s Goddard

Space Flight Center (GSFC). Shuman is currently a Universities Space Research Association Visiting Research

Fellow at GSFC. His research interests include monitoring the state of the current climate system over the great

polar ice sheets with field and remote-sensing data and

how paleoclimate variations are preserved in polar snow

and ice. He is a member of the science team currently

working at the Siple Dome deep-ice-core site in West

Antarctica.

Co-Investigators

Robert A. Bindschadler - NASA/Goddard Space Flight

Center

David H. Bromwich - Byrd Polar Research Center, Ohio

State University

References

Shuman, C.A., R.B. Alley, M.A. Fahnestock, R.A.

Bindschadler, J.W.C. White, and J. Winterle, 1998: Temperature history and accumulation timing for the snow

pack at GISP2, central Greenland. J. Glaciol., 44, 21-30.

Shuman, C.A., R.B. Alley, M.A. Fahnestock, P.J. Fawcett,

R.A. Bindschadler, S. Anandakrishnan, and C.R. Stearns,

1997: Detection and monitoring of annual indicators and

temperature trends at GISP2 using passive microwave remote sensing data, GISP2-GRIP Compendium Volume.

J. Geophys. Res., 102, 26,877-26,886.

Shuman, C.A., M.A. Fahnestock, R.A. Bindschadler, R.B.

Alley, and C.R. Stearns, 1996: Composite temperature

record from the Greenland summit, 1987-1994: Synthesis of multiple automatic weather station records and SSM/

I brightness temperatures. J. Climate, 9,1421-1428.

Shuman, C.A., R.B. Alley, S. Anandakrishnan, J.W.C.

White, P.M. Grootes, and C.R. Stearns, 1995: Temperature and accumulation at the Greenland Summit: Comparison of high-resolution isotope profiles and passive

microwave brightness temperature trends. J. Geophys.

Res., 100, 9165-9177.

Shuman, C.A., R.B. Alley, S. Anandakrishnan, and C.R.

Stearns, 1995: An empirical technique for estimating nearsurface air temperatures in central Greenland from SSM/

I brightness temperatures. Rem. Sens. Environ., 51, 245-

252.

Shuman, C.A., and R.B. Alley, 1993: Spatial and temporal characterization of hoar formation in central Greenland

using SSM/I brightness temperatures. Geophys. Res. Lett.,

20, 2643-2646.

Shuman, C.A., R.B. Alley, and S. Anandakrishnan, 1993:

Characterization of a hoar-development episode using

SSM/I brightness temperatures in the vicinity of the GISP2

site, Greenland. Annals of Glaciology, 17, 183-188.

Investigation URL

http://igloo.gsfc.nasa.gov/~shuman/home.html

Location of high-resolution isotope profiles used in this

study.
308 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Influence of Subgrid-Scale Heterogeneity on

Remotely-Sensed Surface Temperature

Principal Investigator – W. James Shuttleworth

Science Background

Over the last decade there has been substantial progress

in understanding how best to represent subgrid-scale heterogeneous land cover in meteorological models. Meanwhile there has been rapid (but still ongoing) progress in

providing the remotely sensed land-cover data to apply

that understanding. Research has established the value,

usefulness, and feasibility of applying remotely sensed

land-cover classes when describing heterogeneous land

cover in meteorological models used for free-running seasonal, interannual, and longer-term climate prediction.

However, no attempt has yet been made to apply presentday theory and methods for representing heterogeneous

cover in the Numerical Weather Prediction (NWP) models such as those used with four-dimensional data assimilation (4DDA) to provide gridded data in the Global Energy Water-cycle Experiment (GEWEX) continental-scale

projects. Nor has their use been investigated in the context of the EOS data-assimilation models.

Science Goal

The overall goal of this investigation is to elucidate issues and explore assimilation methods relevant to using

remotely sensed data on land cover, surface temperature,

and surface radiation to aid the diagnosis of the surfaceenergy budget in the mesoscale models used for 4DDA in

the GEWEX large-scale field experiments.

We intend to:

1) develop methods which will allow use of remotely

sensed land-cover data to improve representation of

heterogeneous land cover in regional-scale meteorological models used for 4DDA, specifically the Eta

model at the National Centers for Environmental Prediction (NCEP) and the Eta model at the Brazilian

Center for Weather and Climate Prediction (CPTEC);

2) carry out model experiments to investigate whether

subgrid-scale variations in land cover, topography,

and surface-induced atmospheric circulation can detract from the value of area-average, remotely sensed

surface temperature as a diagnostic of surface-energy

partition;

3) develop and apply current aggregation theory to provide an aggregation algorithm which calculates gridaverage surface-energy fluxes from data on landcover class, surface temperature, and surface radiation available at subgrid scale; and

4) test whether the grid-average surface-energy fluxes

given by the aggregation algorithm, when assimilated

into a model with grid-scale representation of surface-atmosphere interactions, provide a diagnosis of

area-average surface-energy partition which follows

that given by the subgrid-scale data fields.

Current Activities

Much of the research will be carried out using the Regional Atmospheric Modeling System (RAMS) running

nested within the atmospheric fields calculated by (the

relevant versions of) the Eta model used for 4DDA at

NCEP and CPTEC. We will carry out model experiments

at appropriately heterogeneous sites, two in the U.S. and

two in Brazil. The nested-modeling experiments are ongoing for the San Pedro valley in Southern Arizona (a

semi-arid site).

A second U.S. site in the Tennessee valley (a moist

site) has been selected so that we can compare and contrast with the Arizona site the possible importance of topography-generated wind-speed differences on grid-average surface-energy balance. The two Brazilian sites,

around Ji-Parana in Rondonia (where there is managed

forest clearance) and around Santerem in Para (where there

is haphazard clearance and a large river) have been chosen to allow us to investigate the possible importance of

land-cover-induced mesoscale atmospheric circulation.

This investigation will continue and expand a long-standing working relationships between the PI and scientists at

NCEP and CPTEC that has proven effective in past joint

research studies.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 309

Use of Satellite Data

We have implemented the Pinker and Laszlo (1992) algorithm for modeling surface solar irradiance using geostationary satellite data, and we are assimilating the solar

data into the nested RAMS runs. Currently, remotely

sensed land-cover data are available in the form of pathfinder data sets with global coverage for model-relevant

cover classes at a 1 × 1-km pixel size. It is to be anticipated that provision of such land-cover data will soon

become routine using data provided by the Earth Observing System. We will develop and test novel theoretical

ideas for assimilating remotely sensed thermal data from

a variety of platforms and over a wide range of spatial

resolutions. The ultimate goal of assimilating a variety of

satellite data is to allow coupled hydrologic-atmospheric

models to routinely document surface energy and water

exchanges.

Participation in Field Activities

Our research will contribute scientific input to and draw

data, from the GEWEX Continental-scale International

Project (GCIP), the Large-scale Biosphere-Atmosphere

(LBA) Experiment, and the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. We are proposing to actively participate in the LBA experiment as part of the

LBA Science Team.

Principal Investigator

W. James Shuttleworth

Prior to joining the Department of Hydrology and Water

Resources at the University of Arizona in January 1993,

Dr. Shuttleworth was Head of the Hydrology Processes

Division of the prestigious Institute of Hydrology, United

Kingdom. His major research interests are in physical

processes in hydrology, with emphasis on evaporation and

hydrometeorology, as applied to environment change at

local, regional, and global scales. Present research includes: the representation of heterogeneous land surfaces

in Global Climate Models, the application of remote-sensing methods within hydrology, and the micrometeorology of natural semi-arid vegetation and riparian systems

in the desert Southwest. He serves on committees for the

International Council of Scientific Unions, the International Hydrology Programme, the International Geosphere-Biosphere Project and the World Climate Research

Programme, and on the NRC Committee for Global

Change Research and on the Panel on the Global Ocean

Atmosphere Land System

Co-Investigators

James J. Toth - University of Arizona

References

Arain, A. M., W. J. Shuttleworth, Z.-L Yang, J. D.

Michaud, and A. J. Dolman, 1997: Mapping surface cover

parameters using aggregation rules and remotely sensed

cover classes. Quart. J. Roy. Meteor. Soc., 123(B), 2325-

2348.

McNider, R. T., A. J. Song, D. M. Casey, P. J. Wetzel, W.

L. Crosson, and R. M. Rabin, 1994: Toward a dynamicthermodynamic assimilation of satellite surface temperature in numerical atmospheric models. Mon. Wea. Rev.,

122, 2784-2803.

Pinker, R. T., and I. Laszlo, 1992: Modeling surface solar

irradiance for satellite applications on a global scale. J.

Appl. Meteor., 31, 194-211.

Sellers, P. J., D. A. Randall, G. J. Collatz, J. A. Berry, C.

B. Field, D. A. Dazlich, C. Zhang, and L. Bounoua, 1996:

A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. J. Climate, 9,

676-705.

Shuttleworth, W. J., 1998: Combining remotely sensed

data using aggregation algorithms. Hydrology and Earth

System Sciences, 2, 149-158.

Shuttleworth, W. J., Z.-L Yang, and A. M. Arain, 1997:

Aggregation rules for surface parameters in global models. Hydrology and Earth System Sciences, 2, 217-226.

Investigation URL

http://www.hwr.arizona.edu/heterogeneity
310 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Development and Application of the Next

Generation of Ocean Color Models for the

Understanding of Marine Processes on

Regional and Global Scales

Principal Investigator – David A. Siegel

Science Background

Satellite ocean color imagery provides more information

than just the chlorophyll a concentration, a measure of

phytoplankton pigmented biomass. Frankly, the next set

of scientific questions for the ocean biosphere will require considerably more extensive and diverse set of ocean

color data products than we have today. Questions related

to partitioning of the upper ocean carbon budget, estimation of air-sea CO2 exchange, tropospheric aerosol production due to dimethyl sulfide emissions, photochemical production of greenhouse related important trace gases

(such as CO, COS, etc.) and probably the remote estimation of water column integrated primary production rates

require more information about the marine biosphere than

is supplied by just the chlorophyll pigment concentration.

Ocean optics research has shown that an ocean color

spectrum contains some of the missing information and

several recent ocean color models have been developed

to determine the concentration of phytoplankton pigments,

the recycled, colored organic materials and the intensity

of particulate backscatter. It is our opinion, substantial

progress in the application of satellite technology to ocean

biology and biogeochemical processes requires the development and application of a new generation of ocean

color tools. In this way, we will begin to achieve the maximum scientific return from NASA’s (and other international space agency) infrastructure investments.

Science Goal

One of the major objectives of our work is to assess inherent optical properties of the upper ocean on global and

regional scales using data from the on-going SeaWiFS

ocean color mission. Our algorithms have provided the

means for determining simultaneously the concentration

of phytoplankton pigments, the abundance of colored organic materials and the intensity of particulate backscatter . Our first goal is to simply address the time-space

distributions of these optically important, in-water constituents and to assess their relationship with physical forcing mechanisms.

However, these “global solutions” must work on regional scales as well as global scales. Hence, we validate

our state-of-the-art ocean color models using data collected by our group from the NASA SIMBIOS supported

Bermuda BioOptics Project (BBOP) time series in the

Sargasso Sea and the NOAA-COP/ONR supported

Plumes and Blooms field study of the Case II waters of

the Santa Barbara Channel. This allows us to develop new

ocean color “tools” and to assess their utility in addressing biogeochemical and biological processes. By comparing the results derived from global and regional data

sets, we can assess the global validity of common ocean

color modeling assumptions and may be able to make

improvements in retrieval results by parameterizing regional differences in the retrieved model parameters. In

this way, we will develop “optimal” ocean color products

from SeaWiFS, MODIS, etc.

Use of Satellite Data

Satellite ocean color data measured from SeaWiFS are

critical for this work. We will also use data from MODIS,

MISR and a host of international ocean color imagers

(GLI, POLDER-2, MERIS, etc.) as they become available. In addition, we have and will continue to use other

satellite data sets, including altimetry (TOPEX/Poseidon,

ERS, Jason, etc.), ISCCP cloud fields, sea surface temperature (AVHRR pathfinder, MODIS), and TOMS ozone.

Participation in Field Activities

Our group has extensive, on-going field work programs

in both the open sea of the Sargasso Sea (BBOP) and the

coastal waters of the Santa Barbara Channel (Plumes and

Blooms). These programs provide field data that are used

to develop and validate our next generation of ocean color

algorithms. We also participate extensively with the

SIMBIOS program.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 311

Principal Investigator

David A. Siegel

David Siegel is a professor of oceanography at the Institute for Computational Earth System Science. He has academic appointments in the Department of Geography and

the Donald Bren School of Environmental Science and

Management and is an adjunct faculty member of the

Bermuda Biological Station for Research. His research

interests are mainly associated with the role of the oceans

in the earth system, particularly in the area of ocean color

remote sensing and its application to understanding global biogeochemical cycles.

Co-Investigators

Stephane Maritorena - Institute for Computational Earth

System Science

Norman B. Nelson - Bermuda Biological Station for Research

Anthony F. Michaels - USC Wrigley Institute for Environmental Studies
312 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Climate Change and Human Response in the

Semi-arid Near East

Principal Investigator – Ronald B. Smith

Science Background

The Southwest Asian region lies at the junction of three

continents: Europe, Asia, and Africa. It includes Turkey,

Syria, Lebanon, Israel, Iraq, Iran, Jordan, Armenia,

Azerbaijan, Kuwait, Turkmenistan, and Saudi Arabia.

Most of this region is characterized by a semi-arid Mediterranean climate with a strong N-S gradient and interannual variations in precipitation, a rapidly rising population (3-5% per year), inaccessible environmental data sets,

and a long 6000-year history of human influence on the

landscape. Over the last quarter century, due to climate,

population, economic pressure, and governmental policy,

the landscape has been changing rapidly.

Science Goal

The goal of the Southwest Asia Project (SWAP) is to summarize and understand the last 25 years of landscape

changes in the region, including the influence of climate

and human factors. In addition, this research will identify

those special physical attributes and resource issues in

the region which affect the choice and use of remote-sensing technologies for environmental monitoring.

Current Activities

In collaboration with the International Center for Agricultural Research in Dry Areas (ICARDA), we are pursuing five parallel research subprojects:

• large-scale agro-ecological characterization

• impact of interannual climate fluctuation

• crop growth and yield

• rangeland degradation and restoration

• evaluation of new remote-sensing technology

Each of these projects requires remote sensing, the analysis

of archival data, field work, and the development of international partnerships.

Use of Satellite Data

Three types of satellite data are used most heavily in the

Southwest Asia Project: Composite AVHRR, Landsat, and

SIR-C radar. Other data types, including Seasat, ERS-1-

2, Radarsat, MODIS, and ASTER are under evaluation.

The subproject on agro-ecological characterization

uses multi-temporal NDVI to estimate the spatial distribution of natural vegetation and agriculture. A systematic

process of verification and iterative correction of these

estimates is underway using field visits and Landsat images. Composite AVHRR time series are also used in conjunction with conventional climate data and gridded hydrologic models to study interannual variation of vegetation over a 15-year period.

The subproject on crop growth and yield is refining

the use of conventional broadband and hyperspectral image data to estimate biophysical descriptors of dry-land

and irrigated agriculture in the Near East including wet

biomass, leaf-area index and yield, along with crop type

and stage. This study requires extensive ground-levelreflectivity measurements as well as real-time Landsat

acquisitions.

The subproject on rangelands requires the application and refinement of new remote-sensing techniques to

measure sparse vegetation in disturbed steppe regions. The

statistical analysis of SIR-C and Landsat data is underway along with ground verification. Plans are being developed for the application of ERS-1-2, Seasat, ASTER,

and MODIS to the rangeland/steppe problem.

Participation in Field Programs

The various field components of SWAP are carried out in

collaboration with ICARDA, FAO, and other established

regional partners. These field activities consist of ground

surveys and sample analyses, point measurements of climate and soil moisture variables, and hyperspectral measurements of soil-vegetation reflectivity and atmospheric

absorption and scattering.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 313

Co-Investigators

Frank Hole - Yale University

Xuhui Lee - Yale University

Mark Wilson - Yale University

References

Smith, R.B., et al., 1997: A climate and vegetation atlas

of the fertile crescent. CEO, Yale University, Department

of Geology and Geophysics, New Haven, Connecticut,

Internal Publication, 1-34.

Thenkabail, P., R.B. Smith, and E. DePauw, 1999:

Hyperspectral Vegetation Indices for Determining Agricultural Crop Characteristics. Remote Sens. Environ., in

press.

Kouchoukos, N., et al., 1998: Monitoring the Distribution, Use and Regeneration of Natural Resources in Semiarid Southwest Asia. Yale F&ES Bulletin, 103, 1-24

Smith, R.B. et al, 1999: Spatial analysis of climate, landscape, and hydrology in the Middle East: Modeling and

Remote Sensing. In prep.

Investigation URL

http://spectra.ceo.yale.edu/swap.html

Using composite AVHRR imagery and simple models, several aspects of Middle East hydrology can be monitored including

upland snow cover, river discharge, irrigated agriculture, and rain-fed farming.This image shows, with a spatial resolution of

one kilometer, the active irrigated agriculture during the summer of 1995. The largest of these regions are on the lower Ceyhan

near Adana in Turkey, the GAP project in Turkey near the Syrian border, new projects near Raqqa and Aleppo in Syria, historic

farms along the Syrian Euphrates and in Mesopotamia near Baghdad, Iraq. These patterns of irrigation have changed dramatically over the last 15 years.
314 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Long-Term Monitoring of the Amazon

Ecosystems Through EOS: From Patterns to

Processes

Principal Investigator – Joao V. Soares

Lead U.S. Investigator – Thomas Dunne

International Co-Sponsor – Brazil

Science Background

Amazonia is unique among terrestrial ecosystems because

of its extent, the intimate interaction with the largest river

on the planet, and the rate of change caused by human

activity. Environmental conditions in the Basin range from

high mountains to equatorial lowlands, and are subject to

natural and anthropogenic changes. Both natural and anthropogenic changes in the Amazon are expected to disrupt regional vegetation distributions, alter the physical

and chemical characteristics of the continental-scale river

system, and modify regional hydroclimatology with significant potential to influence global climate patterns. Understanding the process dynamics of the Amazon Basin

under natural and disturbed conditions is of high scientific priority and is an essential prerequisite for modeling

global change and for understanding the resulting public

policy issues.

Science Goal

The goals of this investigation are:

• To understand the impacts of land-use cover change to

carbon fluxes and ecosystem’s sustainability; and

• To understand the routing of the mobile terrestrial materials (water, sediment and nutrients) from precipitation, through the landscape and drainage system, to the

atmosphere and ocean under changing climate and land

use.

Current Activities

The EOS Amazon group uses remote sensing, field sampling, and hydromet databases to study carbon dynamics;

ecosystem sustainability; sources, transport and processing of water, sediments and solutes within the basin as

they are governed by the large-scale features of the terrain; atmospheric processes and vegetation characteristics.

Use of Satellite Data

In addition to using currently available data, the group is

preparing, through development of remote-sensing tools,

computer models, and data management systems, to maximize the utility of data from EOS sensors. They are exploring the usefulness of MODIS-type sensors for monitoring the status of forest canopies and using the information in their computations of hydrologic response, primary production, and nutrient cycling. The group has

made comparisons of AVHRR records and TM images of

the forested parts of the Basin in order to learn what aspects of the land cover can be reliably measured from

coarse-resolution images. They have been developing algorithms, for application to new imaging systems, which

take into account the full range of background variation

in spectral variability due to atmosphere, instrument, and

other non-vegetative scene components, as opposed to optimizations based solely on the spectral contrast of the

target material. MODIS has the capability to provide variable-resolution band passes. The Amazon group’s focus

is to optimize these band passes, based on the contrast

between foreground and background, given the natural

variability that exists within these defined groups.

The fore-and-aft viewing of ASTER allows separation of many atmospheric influences from that of the surface in addition to the goal of making stereo pairs. The

inclusion of the thermal channels in ASTER also allows

for better detection of even simple scene components such

as vegetation.

The group has also been incorporating satellite measurements of solar radiation fluxes and the results of numerical weather simulations into their hydrologic models and comparing the data with sparse ground-level measurements in order to learn about the accuracy and utility

of future large sets of environmental data for monitoring

and interpreting the condition of the Basin surface.

Participation in Field Programs

Field studies by the group concern rivers and flood plains

at all scales throughout the Basin, as well as well-drained

forested parts of the landscape. Measurements of vegeta-
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 315

tion characteristics in forested, cleared, and re-growth

areas allow the interpretation of sequential Landsat TM,

SAR, and AVHRR images of land cover. An important

emphasis is the characterization of the vegetation and

geomorphic characteristics of vast wetlands and mapping

of the timing and extent of their inundation, using passive microwave data from SMMR and SSM/I, and from

AMSR-E. This information is interpreted and linked to

basin hydrology through analysis of empirical hydrologic

data and mathematical modeling. The hydrology of these

wetlands, which cover more than 20 percent of the Basin,

is crucial to understanding the biogeochemistry of the river

as well as the exchange of methane with the atmosphere.

Principal Investigator

João Soares

João Soares holds a B.A. and an M.Sc. in Agricultural

Engineering from the Federal University of Viçosa, Brazil, and a Ph.D. in Physics of Remote Sensing conferred

by the University of Paris in 1986. He has focused his

research in the areas of modeling the biosphere/atmosphere interactions for water/carbon/energy fluxes and on

remote sensing. He has worked on the problem of extracting soil moisture and vegetation structure from radar

data in the context of the Space Radar Laboratory (SIRC/X-SAR) experiment. He has been affiliated with the

Instituto Nacional de Pesquisas Espaciais since 1997.

Lead U.S. Investigator

Thomas Dunne

Thomas Dunne is Professor in the School of Environmental Science and Management at the University of California Santa Barbara. He holds B.A. and Ph.D. degrees in

Geography from the University of Cambridge and The

Johns Hopkins University, respectively, and is a Member

of the National Academy of Sciences and the American

Academy of Arts and Sciences. His research concerns field

and theoretical studies of drainage-basin and hill-slope

evolution, incorporating the relations among climate, vegetation, hydrology, sediment transport, and soil properties. In addition to work in several mountain and subarctic environments of North America, he has experience

measuring hydrologic and sedimentation processes in

tropical environments in Africa and Brazil, which he uses

as the basis for computer-modeling studies to generalize

his findings.

Co-Investigators

John B. Adams - University of Washington

John M. Melack - University of California-Santa Barbara

Leal A.K. Mertes - University of California-Santa Barbara

Jeffrey E. Richey - University of Washington

Dar Roberts - University of California-Santa Barbara

Compton J. Tucker - NASA/Goddard Space Flight Center

Reynaldo Victoria - Universidade de Sao Paulo, Brazil

John M. Wallace - University of Washington

The following are from the Instituto Nacional de Pesquisas

Espaciais, Brazil:

Diogenes S. Alves

Marcio N. Barbosa

Bruce R. Forsberg

Hermann Kux

Carlos Nobre

Evlyn M.L.M. Novo

Yosio E. Shimabukuro

Dalton Valeriano

References

Batista G.T., and C.J. Tucker, 1994: Assessment of

AVHRR data for deforestation estimation in Mato Grosso

(Amazon Basin). Remote Sens. Rev., 10, 35-49.

Dunne. T., L.A.K. Mertes, R.H. Meade, J.E. Richey, and

B.R. Forsberg, 1997: Exchanges of sediment between the

floodplain and channel of the Amazon River in Brazil.

Geological Society of America Bull., in press.

Keil, R.G., L.M. Mayer, P.D. Quay, J.E. Richey, and J.I.

Hedges, 1997:Loss of organic matter from riverine particles in deltas. Geochimica et Cosmochimica Acta, 61,

1507-1511.

McClain, M.E., and J.E. Richey, 1996: Regional-scale

linkages of terrestrial and lotic ecosystems in the Amazon basin: A conceptual model for organic matter. Archiv

für Hydrobiologie (Suppl. 113), 111-125.

McClain, M.E., J.E. Richey, J.A. Brandes, and T.P.

Pimentel, 1997: Dissolved organic matter and terrestriallotic linkages in the central Amazon Basin, Brazil. Global Biogeochem. Cycles, 11, 295-311.

McClain, M.E., J.E. Richey, and R.L. Victoria, 1996:

Andean contributions to the biogeochemistry of the Amazon River system. Bulletin de l’Institut Francais d’Etudes

Andines, 24, 425-437.
316 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Mertes, L.A.K., 1997: Documentation and significance

of the perirheic zone on inundated floodplains. Water

Resour. Res., 33, 1749-1762.

Mertes L.A.K., M. Smith, and J.B. Adams, 1993: Quantifying sediment concentration in surface waters of the

Amazon River wetlands from Landsat images. Remote

Sens. Environ., 43, 281-301.

Mertes, L.A.K., T. Dunne, and L.A. Martinelli, 1996:

Channel-floodplain geomorphology of the SolimoesAmazon River, Brazil. Geological Society of America

Bull., 108, 1089-1107.

Novo, E.M., and Y.E. Shimabukuro, 1994: Spectral mixture analysis of inland tropical waters. Int. J. Remote Sens.,

15, 1351-1356.

Richey, J.E., and R.L. Victoria, 1996: Continental-scale

biogeochemical cycles of the Amazon River system. Verh.

Int. Verein. Limnol., 26, 219-226.

Richey, J.E., and R. Victoria, 1993: C, N, and P dynamics

in the Amazon River. Interactions of C, N, P, and S Biogeochemical Cycles and Global Change, R. Wollast, F.T.

Mackenzie, and L. Chou, Eds., Springer-Verlag, Berlin,

123-140.

Richey, J.E., S.R. Wilhelm, M.E. McClain, R.L. Victoria,

J.M. Melack, and C.A.R.M. Araujo-Lima, 1997: Organic

matter and nutrient dynamics in river corridors of the

Amazon Basin and their response to anthropogenic

change. Ciencia e Cultura, 49, 98-110.

Ustin S.L., M.O. Smith, and J.B. Adams, 1993: Remote

sensing of ecological processes: A strategy for developing and testing ecological models using spectral mixture

analysis. Scaling Physiological Processes: Leaf to Globe,

J.R. Ehleringer and C.B. Field, Eds., Academic Press, 339-

357.

Victoria, R.L., L.A. Martinelli, J.M. Moraes, M.V.

Ballester, G. Pellegrino, R.M.B. Almeida, and J.E. Richey,

1997: Surface air temperature variations in the Amazon

region and its borders during this century. J. Climate, in

press.

Investigation URL

http://boto.ocean.washington.edu/eos/
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 317

Middle And High Latitude Oceanic Variability

Study (MAHLOVS )

Principal Investigator – Meric Srokosz

Science Background

The aim of MAHLOVS is to investigate the variability of

the atmospheric forcing of the oceans, the consequent

effect on the oceanic response, and the resulting effect on

the biological productivity of the oceans. Much effort is

presently being expended on determining the long-term

and large-scale means and trends in the structure of the

oceans (for example, the WOCE and JGOFS programs).

By the time of the launch of Terra a good grasp of that

problem should have been obtained. This study builds on

that understanding by examining the spatial and temporal variability of the ocean (on space scales ranging from

one-to-one-thousand kilometers and time scales of days

to years), about these large-scale and long-term means

and trends. This is likely to contribute to the UK component of CLIVAR (the successor to WOCE and TOGA).

To understand changes in the atmosphere-ocean-biology

system it is clear that knowledge about the variability of

the system is necessary, as well as information about

means and trends. MAHLOVS concentrates on mid-tohigh-latitude regions of the oceans, in particular the eastern North Atlantic and the Southern Ocean. These regions

have been chosen because they are areas of significant

atmosphere-ocean-biology interaction and variability and

because there is a continuing UK oceanographic interest

in them (they feature in the UK components of the WOCE

and JGOFS programs). The latter consideration is important in that in situ data are therefore to be available for

incorporation into this study. It is proposed to make use

of the microwave, visible, and infrared sensors of the EOS

system to calculate the sea-surface forcing and fluxes, the

dynamical variability of the ocean, and the biological activity. The data will be combined in a synergistic manner,

and assimilation of the data into ocean models (biological and physical) will be used to enhance the analysis,

interpretation, and understanding of the phenomena observed.

Science Goals

The science goal of this investigation is to examine the

relationship between the temporal and spatial variability

of the atmospheric forcing of the ocean and the consequent variability of the oceanic response and its effect on

the biological productivity at mid-to-high latitudes (particularly in the eastern North Atlantic and the Southern

Ocean). Specific scientific questions to be addressed are:

• What changes occur over a ten-year period in the surface fluxes of momentum, heat, water, and radiation in

the regions of interest, on space scales of the order of

hundreds of kilometers and time scales of longer than

one week?

• What is the variability of the ocean circulation and biological activity in these areas and how do they relate to

the variability of the surface forcing?

• To what extent does the coupling of the eastern North

Atlantic with the Norwegian Sea, the North Sea, and

the Western Mediterranean affect its dynamical and biological variability?

• In the Southern Ocean, what is the effect of the variability of the Antarctic Circumpolar Current on the biological activity?

• What are the differences and similarities between the

eastern North Atlantic and the Southern Ocean?

Current Activities

Recent progress in MAHLOVS studies includes:

• multi-sensor studies of Rossby wave propagation in the

North Atlantic, using TOPEX altimeter height and ERS

ATSR SST data. These show a strengthening of the

Rossby wave signal in the Azores current region.

• a new global climatology of improved air-sea fluxes,

based on in situ data, covering the period 1980-93, has

been generated. This contributes to the understanding

of the coupled atmosphere-ocean system. (see http://

www.soc.soton.ac.uk/JRD/MET/fluxclimatology.html)
318 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

• development of a novel method for assimilating data

into a biological model to obtain better estimates for

the model parameters, thus improving the model’s ability to represent the ocean biology.

• studies of plankton patchiness in the eastern North Atlantic, including data acquired on a recent cruise (AprilMay 1997) and ocean-color data from OCTS on

ADEOS. The data suggest that both biological and biophysical interactions are of importance in the development of patchiness.

• studies of the relationship between wind speed and

stress, using ship measurements (corrected for air-flow

distortion round the ship), have shown that there is no

dependence of wind stress on the wave conditions in

the open ocean.

• development of a new method for estimating rain rate

over the ocean that makes use of the dual-frequency

capability of the TOPEX altimeter.

Use of Satellite Data

Prior to the launch of the EOS sensors, data from other

satellite missions and sensors (Geosat, AVHRR, ERS-1

& 2, TOPEX/Poseidon, SeaWiFS, ADEOS) are being, or

will be, used to carry out initial studies. Once Terra is

launched, data from the radar altimeter, scatterometer (on

ADEOS-II), MODIS, AMSR-E, AIRS and CERES will

be used in combination to investigate atmosphere-oceanbiology interaction and variability. In addition, data from

sensors on the NOAA polar orbiter series, the ESA Envisat

and Metop missions, and the NASDA ADEOS-II mission will be used to complement those obtained from

NASA’s EOS sensors. Important to the investigation is

the requirement for simultaneity of observations from a

number of sensors (the degree of simultaneity required

depends on the particular process being studied), which

will be available from EOS.

Participation in Field Programs

A major cruise, aboard the UK research vessel RRS Discovery, was undertaken in April-May of 1997 to study

plankton patchiness during the development of the spring

bloom. The ship and satellite (ERS-2, ADEOS—particularly OCTS, AVHRR, TOPEX/Poseidon) measurements

acquired during the cruise period contributed to determining the relative importance of the biological and bio-physical interactions in creating patchiness. In addition, biooptical data from the cruise contributed to the validation

of ocean-color algorithms.

To complement the study of the relationship between

wind speed and stress from ship-based measurements

(where air flow distortion round the ship needs to be accounted for), a meteorological buoy has been developed

that can make measurements without the problem of flow

distortion. The buoy carries sonic anemometers that allow the direct measurement of stress via the dissipation

technique. The buoy has been deployed at sea, and the

results obtained will improve understanding of the windspeed-to-stress relationship.

Finally, an acoustic rain-measuring buoy has been

developed, and is to be deployed, to validate the new algorithms for rain over the ocean that use the dual-frequency capability of the TOPEX altimeter. In addition,

data from a ground-based meteorological rain radar will

be used in the validation.

Principal Investigator

Meric A. Srokosz

Meric Srokosz has 18 years of experience in the fields of

applied mathematics and remote sensing of the oceans.

He holds both undergraduate and doctoral degrees in

Mathematics from Bristol University. Currently, he is a

member of the James Rennell Division of the

Southampton Oceanography Centre (SOC). Dr. Srokosz

is a Principal Investigator for the ERS-1 and ERS-2 missions, and a co-investigator for the TOPEX/Poseidon,

ADEOS, and TRMM missions.

Co-Investigators

Keith Haines - University of Edinburgh

The following are from the Southampton Oceanography

Centre:

Peter G. Challenor (James Rennell Division)

Mike Fasham (George Deacon Division)

Trevor Guymer (James Rennell Division)

Ian Robinson (University of Southampton)

Peter K. Taylor (James Rennell Division)

References

Challenor, P.G., J.F. Read, and R.T. Tokmakian, 1996:

Measuring surface currents in Drake Passage from altimetry and hydrography. J. Phys. Oceanogr., 26, 2748-2759.

Cipollini, P.D. Cromwell, M.S. Jones, G.D. Quartly, and

P.G. Challenor, 1997: Concurrent altimeter and infrared

observations of Rossby wave propagation near 34N in

the Northeast Atlantic. Geophys. Res. Lett., 24, 889-892.

Cooper, M., and K. Haines, 1996: Altimetry assimilation

with water property conservation. J. Geophys. Res., 101,

1059-1077.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 319

Fasham, M.J.R., 1995: Variations in the seasonal cycle of

biological production in subarctic oceans: a model sensitivity analysis. Deep Sea Res., 42, 1111-1149.

Harmon, R., and P.G. Challenor, 1997: A Markov chain

Monte Carlo method for estimation and assimilation into

models. Ecol. Modelling, 101, 41-59.

Josey, S.A., E.C. Kent, D. Oakley, and P.K. Taylor, 1996:

A new global air-sea heat and momentum flux climatology. International WOCE Newsletter, 24, 3-5.

Quartly, G.D., T.H. Guymer, and M.A. Srokosz, 1996:

The effects of rain on TOPEX radar altimeter data. J.

Atmos. Oceanic Tech., 13, 1209-1229.

Srokosz, M.A., 1997: Plankton patchiness studies by ship

and satellite, RRS Discovery Cruise 227, 15 April - 16

May 1997. Southampton Oceanography Centre Cruise

Report No. 12, 76 pp.

Robinson, I.S., A.R. Weeks, and B.A. Booty, 1995: A

towed near-surface optical reflectance meter for measuring ocean color in support of remote sensing. Deep Sea

Res., 42, 2093-2111.

Yelland, M., and P.K. Taylor, 1996: Wind stress measurements from the open ocean. J. Phys. Oceanogr., 26, 541-

558.

Investigator URL

http://www.soc.soton.ac.uk/

These Hovmoller diagrams show the westward propagation of baroclinic Rossby waves at 34N and in the N.E. Atlantic,

as observed in the zonal gradients of ERS-1 ATSR SST and TOPEX/Poseidon SSH data.
320 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Water Vapor in the Climate System

Principal Investigator – Graeme Stephens

Science Background

A characteristic of the Earth’s climate system is its great

complexity. Couplings between vast arrays of processes

are thought to produce a series of complex feedbacks in

response to any given climate forcing. The energy budget

of the planet is one important component of the system as

are the dynamical processes which move the atmosphere

and oceans and the hydrological processes that shape the

energy exchanges. One of the major issues confronting

global-change research is understanding how the energy

is distributed in the system, the extent that the hydrological cycle determines this distribution, and how the dynamical processes, driven by heating gradients, in turn

shape the hydrological cycle.

The hydrological cycle is germane to all of the principal components of the climate system (e.g., Chahine,

1992). As such, research aimed at improving our understanding of how this cycle works receives high priority in

both national and international climate research programs

(such as the Global Energy and Water cycle Experiment

(GEWEX) of the World Climate Research Program

(WCRP) and within the U.S. Global Change Research

Program (USGCRP). The objectives of the research on

the Water Vapor in the Climate System are to study how:

• Water vapor plays a decisive role in the transfer of radiation through the atmosphere and therefore largely

determines the atmospheric response to an increase of

infrared-active gases such as carbon dioxide and freons

through the water-vapor feedback mechanism.

• Water vapor is important to the transport and release of

latent heat. The distribution of latent-heat release is a

topic that has received considerable attention over the

past decade, especially with the burgeoning interest in

the variability of the atmosphere on both inter- and intra-seasonal time scales.

• The amount of water vapor present in the atmosphere

influences the rate of evaporation from the surface, a

process of crucial importance to our understanding of

the surface energy budget

• The transport and divergence of water vapor are essential ingredients in determining the distribution of solid

and liquid water in the atmosphere and therefore crucial to the significant and perplexing problem of cloud

feedback in climate change.

• The atmospheric distribution of water vapor is critical

in determining the energy balance at the ocean surface

and indirectly, in the fresh water flux into the ocean. In

that context, the atmospheric water vapor is of a vital

importance in determining the interaction of the ocean

and the atmosphere on a wide spectrum of space and

time scales.

Research Goals

The research described below seeks to elucidate the role

of water vapor in climate and climate change especially

with regard to (i) water-vapor feedback, (ii) the impact of

vertical redistribution on this feedback and (iii) the broad

aspects of the transport of this vapor. To achieve these

three goals, research is discussed in terms of two broad

and connected areas.

The first is concerned with research in ways of obtaining global water-vapor data using existing and new

satellite observations. The second phase of this research

(and one definitely connected to the first) is concerned

with application of the data to evaluate the hydrological

cycle as it is predicted in climate models and observed in

the real world. This research involves analyses of two

types of climate model simulations, one of the AMIP

(Gates, 1992) type where the SSTs are specified and another involving simulations of coupled ocean atmospheric

GCMs. It is important to emphasize that this research is

not merely about collecting water-vapor data and comparison of these data to their model counterparts. Rather

the research focuses on examining the sensitivity of important processes (such as radiative transfer, cloud processes among others) to water vapor and to examine how

well these are treated in climate models.

Current Activities

Further results describing these activities are located on

the web site listed at the end of this investigation summary.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 321

The main elements of this research include:

1) Satellite retrievals: Analyses and assessment of

present satellite capabilities (Engelen and Stephens,

1998).

2) Validation of satellite data: Use of field-study data,

such as collected during the ARM IOP (http://

www.arm.gov/) and other current activities.

3) Analyses of existing data: Analyze existing data to

study the climate system (e.g., Lietzke and Vonder

Haar, 1998). Under this activity we analyze NVAP

and reanalysis data related to other components of

the climate system. We are currently analyzing NVAP,

ECMWF, DAO, and NCEP reanalysis data sets.

4) Reanalyses Comparison: In related activities, the

work of CLERA (Clear Sky Longwave Radiation

from ECMWF Reanalysis) is an extension of earlier

work by Slingo and Webb (1992). The idea is to incorporate analyses data into a model of clear-sky

OLR, and through comparison with measured OLR,

identify problems in the reanalysis measurements.

5) Water vapor transport and mixing: A new effort under development is to use the satellite data, together

with daily wind data to study the properties of watervapor mixing. This work is being carried out in the

University of Chicago under the direction of Professor R. Pierrehumbert using Lagrangian methods; and

at Colorado State University where Davey et al.

(1999) are studying moisture plumes from the tropics to mid-latitudes.

6) Comparisons and analyses of other satellite data: We

have developed a collaboration with J. Waters of JPL

and are beginning to analyze MLS upper troposphere

water vapor in association with TOVS and SSMT2.

These data will not only be compared to other satellite data but will also be used to study the relationship between upper tropospheric water-vapor variability and the variability of the atmospheric circulation.

7) Comparison with models - AMIP-2 comparisons: We

have implemented a special AMIP-2 project under

this research that allows the modeling groups to simulate TOVS radiance directly. Refer to the following

web address: http://langley.atmos.colostate.edu/

richard/amip_home.html

8) Analysis of Coupled Model Results: Experiments

from four coupled climate models in which CO2 concentrations increases at rates of 0.5-1.1% per year

for periods of 75-200 years are used to study the radiative fluxes at the surface and the water-vapor budget of the atmosphere. Results from a fifth simulation are currently being included in this analysis

(Garratt et al., 1998).

9) Signatures of water vapor feedback: We use existing

data sources, primarily derived from current satellite

radiances to study the feedback between radiation,

clouds, water vapor, and sea surface temperature

(SST) in the tropical atmosphere. The variety of data

sources provides new insight about tropical convection and the association of this convection to SST.

Principal Investigator

Graeme L. Stephens

Prior to becoming an Associate Professor in 1984 and a

Professor in 1991 at Colorado State University, Graeme

L. Stephens was a Senior Research Scientist at the Commonwealth Scientific and Industrial Research Organization, Division of Atmospheric Research. He received his

M.S. and Ph.D. degrees at the University of Melbourne,

Australia. In 1990 he received the Henry G. Houghton

Award of the American Meteorological Society.

Co-Investigators

Edward Browell - NASA/Langley Research Center

Michael Exner - University Corp. for Atmospheric Research

J. Garratt - CSIRO, Australia

Jorge Ramirez - Colorado State University-CE

David Randel - Colorado State University-CIRA

Roger Saunders - ECMWF UK

Anthony Slingo - UK Meteorological Office

Thomas H. Vonder Haar - Colorado State University

References

Davey, C., T. Vonder Harr, and J. Forsythe, 1999: Probing the Depths of Atmospheric Moisture Plumes. Poster

presentation at the EOS-IWG meeting, Vale, Colorado,

June 15-17.

Engelen, R., and G.L. Stephens, 1998: Characterization

of Water Vapor Retrievals from TOVS/HIRS and SSMT/

2 Measurements. Quart. J. Roy. Meteor. Soc., in press.

Garratt, J.R., D.M. O’Brien, G.L. Stephens, M.R. Dix,

M. Wild, and J.M. Murphy, 1998: Response of Radiative

Fluxes in the Atmosphere to CO2

 Forcing. J. Climate,

submitted.
322 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Gates, W.L., 1992: AMIP: The Atmospheric Model

Intercomparison Project. Bull. Amer. Meteor. Soc., 73,

1961-1970.

Lietzke, C.E., and T.H. Vonder Haar, 1998: Regional Water

Vapor in the Presence of Tropical Storms. Ph.D. Dissertation. Colorado State University, Department of Atmospheric Science, Ft. Collins, Colorado 80523-1371.

Randel, D.L., T.H. Vonder Haar, M.A. Ringerud, G.L.

Stephens, T.J. Greenwald and C.L. Combs, 1996: Bull.

Amer. Met. Soc., 77, 1233-1246.

Slingo, A., and M.J. Webb, 1992: Simulation of clear-sky

outgoing longwave radiation over the oceans using operational analyses. Quart. J. Roy. Meteor. Soc., 118, 1117-

1144.

Investigation URL

http://langley.atmos.colostate.edu/nasawv.html

Comparisons of observed January TOVS/HIRS channel 11 brightness tempeatures with brightness temperatures calculated using data

derived from the CSU GCM.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 323

Earth System Dynamics: The Determination

and Interpretation of the Global Angular

Momentum Budget Using EOS

Principal Investigator – Byron D. Tapley

Science Background

Momentum, mass, and energy transport between the atmosphere, oceans, and solid Earth produce changes in

the Earth’s rotation and gravity field which are being

measured by modern space-geodetic techniques. Changes

in rotation are attributable both to motions of winds in

the atmosphere and currents in the oceans as well as to

mass redistribution within the Earth system. Alternatively,

changes in the gravity field, which can be inferred from

satellite-orbit perturbations, arise only from mass redistribution. Thus space-geodetic measurements of Earth rotation, gravity variations, and satellite motions provide

global measures of momentum and mass redistribution

and can be used to study the mechanisms involved in these

changes.

The details of the mass and momentum exchange between the components of the Earth’s dynamic system are

not fully understood, and a primary focus of the research

will be to clarify the mechanisms that dynamically couple

the atmosphere, oceans, and solid Earth. The agents that

transfer angular momentum between the atmosphere and

the other components include torques from tangential surface frictional effects and from normal pressure gradients across mountainous topography. Similarly, oceanic

pressure differences across continental faces can also be

important in transferring momentum from oceans to the

solid Earth.

Earth rotation and gravity variations occur over many

time scales and provide measures of such climate-related

signals as seasonal fluctuations in atmospheric pressure

and winds, the El Niño/Southern Oscillation phenomenon,

and longer-term redistribution of water mass among

ocean/continent/polar-ice-cap reservoirs. Appropriate global integrals of the mass and motion of air and water give

predictions of gravity and rotation changes that can be

compared with observations. These comparisons can be

used to verify and improve models of the interaction of

the oceans, atmosphere, and land-surface hydrology. Energy redistribution across the ocean boundary is another

process for which a quantitative assessment of atmosphere-ocean coupling interaction has not been fully

achieved, but the measurement of gravity and its temporal variations along with current ocean-surface-topography measurements from satellite-altimeter missions provides unique information for using ocean models to study

this coupling.

Science Goal

The objective of this investigation is to develop appropriate Earth-system models for analyzing multi-sensor information from EOS satellites, along with in situ data and

data from other satellites, to investigate the interactions

of the atmosphere, oceans, and solid Earth, as represented

by the exchange of angular momentum, mass, and energy among these components. The study will focus on

understanding the relationship of changes in these quantities to global climate-change processes. An important

issue to be addressed is the impact of global warming on

sea-level change. The EOS measurements will allow us

to directly measure the different contributions to sea-level

change including thermal expansion and the melting/accumulation of ice in the polar regions and continental glaciers.

Current Activities

The investigation is utilizing atmospheric angular momentum and related data sets derived from the wind and mass

fields from the NASA Goddard Earth Observing System

Data Assimilation System, as well as from operational

analyses of the world’s major weather centers such as the

National Centers for Environmental Prediction (NCEP).

Variations in oceanic angular momentum due to mass redistribution and changes in currents are being studied as

are interactions between the ocean and the Earth’s solid

crust. Output from ocean general circulation models using both barotropic and eddy-resolving realizations is

being used to calculate and assess oceanic angular momentum and torque mechanisms. Monthly surface winds

derived from scatterometry will be used to improve assessments of the global momentum budget beyond the

result based on operational models. Torques from the ERS1 scatterometer may be in better balance with the inferred

changes in momentum over the seasonal cycle. In addition, research into ocean data assimilation using satellitealtimeter, scatterometer, and radiometer data is being con-
324 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

ducted to develop methodologies for ingesting these data

into appropriate models for more-accurate computation

of ocean circulations. In alternate studies, the TOPEX/

Poseidon altimeter data are being used to measure the seasonal, interannual, and secular sea-level change. Analysis of six years of TOPEX/Poseidon sea-level data indicates that these measurements have the potential to determine the global variations of the mean sea level with an

accuracy of better than 1 mm/yr if a longer time series

can be accumulated. The investigation has also been focusing on the analysis of atmospheric pressure fields from

meteorological models (NCEP, ECMWF) to determine

the effect of atmospheric mass redistribution on the temporal variations of the Earth’s gravity field. These variations are being compared to gravity-field variations observed using satellite laser ranging, and they are also being used in pre-mission studies for the ESSP mission,

Gravity Recovery and Climate Experiment (GRACE).

Use of Satellite Data

The ocean and polar-ice topography changes observed

by the EOS radar and laser altimeter satellites, along with

the Earth rotation and mass change observed by satellite

laser ranging, very long baseline interferometry, and GPS

space-geodesy techniques will be primary measurements

for this investigation. The mass and momentum balances

will require measurements from a number of EOS instruments. AIRS/AMSU/HSB will provide input for the temperature and moisture in the atmospheric momentum,

mass, and water budgets. AMSR-E will be used to observe water vapor and the information about surface winds

over the ocean. QuikSCAT will be used to provide measurements for sea-surface wind vectors. Jason-1 will provide sea-surface topography, wind speed, and wave-height

measurements and measurements of global sea-level

change. ICESat/GLAS will be used to provide changes

in ice-sheet elevations to provide a constraint on the global water budget. These two measurements will be crucial to measuring the impact of global warming on sealevel change.

A critical data set to this investigation will become

available in 2001 with the launch of GRACE. GRACE

will provide the highest resolution measurements of the

mean and time-varying components of the Earth’s gravity field ever made. These measurements will allow us to

monitor mass movement in the solid Earth, the oceans,

the atmosphere, the polar ice caps, and continental groundwater and glaciers.

In addition, other data sources, including many of

the Pathfinder data sets, satellite radar-altimetry data, and

long-term space-geodetic measurements, such as the 20-

year series of satellite laser ranging to geodetic satellites,

will be utilized. The terrestrial reference frame determined

by satellite laser ranging is an essential requirement for

describing changes in the Earth system over multi-decadal

time intervals.

Participation in Field Activities

Instrument-calibration activities were conducted supporting the ESA ERS-1 Venice Tower calibration and the

NASA/CNES TOPEX/Poseidon Harvest Platform and

Lampedusa calibrations. As part of the activities which

support GLAS and accurate measurement of sea level,

additional calibration of ERS-1 and TOPEX/Poseidon

instruments is being conducted in the Galveston Bay region along the Texas coast. These activities will continue

for future altimeter missions such as Jason-1. Team members provide atmospheric angular-momentum data, as well

as Earth-rotation solutions determined from geodetic satellites, to the International Earth Rotation Service.

Principal Investigator

Byron D. Tapley

Byron Tapley earned a Ph.D. in Engineering Mechanics

at The University of Texas at Austin, and has over 30

years of experience in the use of satellites for Earth observations. He has served on the National Research Council (NRC) Space Studies Board (SSB), the SSB Committee on Earth Studies, and the NRC Earth Studies Board

Geodesy Committees. He began teaching at his alma mater

in 1958. Since 1984, he has held the Clare Cockrell Williams Centennial Chair in the Department of Aerospace

Engineering and Engineering Mechanics, and he serves

as Director of the Center for Space Research. He is also

the Director of the Texas Space Grant Consortium. His

research interests focus on the application of nonlinear

parameter-estimation methods to determine crustal motion, Earth rotation, the Earth’s geopotential, and ocean

circulation. He has served as Chairman of the Geodesy

Section for the American Geophysical Union (AGU). He

is the recipient of the NASA Exceptional Scientific

Achievement Medal in 1983, the American Institute of

Aeronautics and Astronautics (AIAA) Mechanics and

Control of Flight Award in 1989, the NASA Public Service Medal in 1995 and the AAS Dirk Brouwer Award in

1996. He is a member of the National Academy of Engineering and a Fellow of AGU, AIAA, and AAAS.

Co-Investigators

Richard J. Eanes - University of Texas at Austin

John Lundberg - University of Texas at Austin

Rui. M. Ponte - Atmospheric and Environmental Research,

Inc.

Richard D. Rosen - Atmospheric and Environmental Research, Inc.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 325

David A. Salstein - Atmospheric and Environmental Research, Inc.

Bob E. Schutz - University of Texas at Austin

C. K. Shum - Ohio State University

Clark R. Wilson - University of Texas at Austin

References

Chen, J.L., C.R. Wilson, D.P. Chambers, R.S. Nerem, and

B.D. Tapley, 1998: Global water mass balance and mean

sea level variations. Geophys. Res. Lett., 25, 3555-3558.

Kuehne, J., S. Johnson, and C. Wilson, 1993: Atmospheric

excitation of non-seasonal polar motion. J. Geophys. Res.,

98(B11), 19,973-19,979.

Nerem, R.S., B.J. Haines, J. Hendricks, J.F. Minster, G.

T. Mitchum, and W. B. White, 1997: Improved determination of global mean sea level variations using TOPEX/

Poseidon altimeter data. Geophys. Res. Lett., 24(11) 1331-

1334.

Ponte, R., and R. Rosen, 1994: Oceanic angular momentum and torques in a general circulation model. J. Phys.

Ocean., 24, 1966-1977.

Ponte, R.M., D. Stammer, and J. Marshall, 1998: Oceanic signals in observed motions of the Earth’s pole of

rotation. Nature, 391, 476-479.

Salstein, D.A., 1993: Monitoring atmospheric winds and

pressures for Earth orientation studies. Adv. Space Res.,

13(11), 175-184.

Tapley, B.D., B.E. Schutz, R.J. Eanes, J.C. Ries, and M.M.

Watkins, 1993: Lageos laser ranging contributions to

geodynamics, geodesy, and orbital dynamics, in Contributions of Space Geodesy to Geodynamics: Earth Dynamics, Geodyn. Ser., Vol. 24, edited by D. E. Smith and

D. L. Turcotte, 147-174, AGU, Washington, D.C.

Watkins, M.M., and R.J. Eanes, 1997: Observations of

tidally coherent diurnal and semidiurnal variations in the

geocenter. Geophys. Res. Lett., 24 (17), 2231-2234.

Watkins, M.M., and R.J. Eanes, 1993: Long-term changes

in the Earth’s shape, rotation, and geocenter. Adv. in Space

Res., 13(11), 251-255.

Investigation URL

http://www.csr.utexas.edu

The figure on the left shows global mean sea level (GMSL) variations measured by the TOPEX/Poseidon (T/P) altimeter satellite from 1993

to 1998, including the rise associated with the 1997 El Niño. This signal is influenced by warming of the upper layer of the ocean and by

changes in the ocean mass. The figure on the right shows variations in GMSL as measured by T/P after removing thermal sea level

variations and a linear trend. Superimposed on this figure is the annual variability predicted from the global water mass balance using

contemporary atmospheric and hydrological models. The results indicate the annual variations of the atmosphere, oceans, and land as they

exchange water mass over the year.
326 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Modeling of Distribution and Interannual to

Interdecadal Variations of Aerosols

Principal Investigator – Ina Tegen

Science Background

In recent years it has become clear that not only sulfate

aerosols, but also other aerosol types like soil dust and

smoke from biomass burning are likely to be important

climate-forcing factors. The magnitude and even the sign

of the climate forcing caused by these tropospheric aerosols is still unclear. Absorbing aerosols like dust and black

carbon do not necessarily cause significant changes in

top-of-atmosphere radiative fluxes but can change heating rates in aerosol-containing layers which could lead to

regional changes in atmospheric circulation. For an assessment of this effect, distributions of optical properties

of all important aerosol species including absorbing aerosols are needed.

“Radiative forcing” by aerosols is defined as the

change in radiative fluxes caused by an increase in aerosol levels. For climate-change studies, we therefore need

to separately consider aerosol emissions from natural

(background) sources and sources that change with time

due to human impact or climate variations. Aerosol loads

can change considerably on interannual-to-interdecadal

timescales, where changes are not globally uniform. Although distinguishing between “natural” and “anthropogenic” aerosols, currently existing aerosol transport models do not take into account changes at interannual and

interdecadal timescales.

Current satellite instrumentation is not sufficient to

allow for global retrieval of tropospheric aerosol properties with an accuracy needed for climate-change studies.

For now, global transport models must be used to calculate aerosol distributions with the best available knowledge on sources and aerosol processes, validating and constraining model results with ground-based measurements

of aerosol concentrations, deposition rates, and extinction optical thicknesses.

Science Goal

The goal is to model sources, transport, and removal of

key aerosol types (mineral dust, carbonaceous aerosol,

sea salt) in the atmosphere using the GISS global 3-D

tracer transport model. As part of a separate project the

sulfate cycle is being included into the Goddard Institute

for Space Studies (GISS) GCM (Daniel Jacob, Harvard

U., Principal Investigator; at GISS this project is carried

out by D. Koch). Results from that model will be available for sensitivity studies.

Estimates of aerosol emissions for the period 1980-

1990, and, in some cases, 1950-1990 together with observed precipitation fields for those years will be included

in the model to provide interannual variations of anthropogenic aerosols. Variations of dust emissions for the different years will also be included. The result of the proposed effort is a global 4-D distribution of aerosol optical

properties useful for climate models and satellite retrievals.

With information on distribution, aerosol optical

thickness, effective particle size and effective variance,

and chemical composition (i.e., refractive indices) direct

aerosol forcing can be calculated. Since aerosol optical

properties are already parameterized in the GISS GCM,

this parameterization will be applied to the calculated

aerosol distributions. An ultimate goal will be to evaluate

the GCM response to changing aerosol levels for the different aerosol types.

Current Activities

A comparison of distributions of different aerosol types

resulting from different models which have been converted into optical thicknesses revealed that sulfate, carbonaceous aerosols, and soil dust contribute approximately equally to the global average tropospheric aerosol

optical thickness. Soil dust and sea-salt aerosols have been

included as tracers (including size distribution) in the GISS

chemical transport model. Carbonaceous aerosol emission fields (soot and carbonaceous aerosols) have been

compiled at GISS by P. Hollrigl and are available to be

included into the tracer transport code. A 20-year emission trend for anthropogenic sulfate and black carbon has

been compiled for different regions of the world.

A new version of the 3-D GISS offline tracer model

being developed by I. Fung (U. Victoria) is available for

the aerosol transport calculations. It uses wind fields derived from the new version of the GISS GCM and calculates convective mixing on-line using temperature, wind,

and humidity fields. It does not include explicit horizontal diffusion. This model shows much improved results,

e.g., for calculations of the distribution of the tracer SF6

compared to the old version of the tracer model that was
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 327

previously used. Similarly improved results compared to

the previous version are expected for the aerosol calculations with this model.

A case study of a Saharan dust storm that affected

dust loads measured over the Atlantic and Mediterranean

Sea was done to explore the possibility of combining modeling, ground-based measurements and satellite retrievals to obtain a complete picture of an aerosol event as

well as to explore possibilities of dust retrievals over land

using brightness temperatures.

Use of Satellite Data

Aerosol retrievals from AVHRR and TOMS will be used

to validate interannual variations of aerosol distributions.

Even if the retrieved aerosol optical thicknesses are uncertain due to unknown aerosol optical properties, the

year-to-year variations in these data should reveal trends

in aerosol loads. In a case study, brightness temperatures

from the Meteosat IR channel archived in the ISCCP pixellevel data set were used to obtain dust-aerosol information over land.

Planned satellite instruments (MODIS, MISR, EOSP)

will provide improved capabilities to retrieve aerosol properties. Retrieval algorithms for these instruments are under development. The aerosol product from this investigation will provide ranges of refractive indices and particle sizes as well as information on particle nonsphericity

(by assuming dust particles to be nonspherical and hygroscopic particles to be spherical) at model resolution as

‘first guess’ for aerosol retrieval calculations, while in turn

the new satellite aerosol products will provide improved

possibilities of validating aerosol transport models.

Principal Investigator

Ina Tegen

Ina Tegen is an Associate Research Scientist in the Department of Applied Physics at Columbia University and

the NASA Goddard Institute for Space Studies in New

York. She received her Ph.D. in Physics at the University

of Heidelberg in July 1992. Her research interests are interactions of tropospheric aerosols and climate. In the field

of soil-dust aerosol her recent research included an estimate of radiative forcing due to dust from

anthropogenically disturbed soils.

References

Hollrigl, P., 1997: Modeling the distribution of aerosols

and their effect on the atmospheric radiation, Ph.D. thesis, ETH Zurich, Switzerland.

Kubilay, N., E. Oszoy, S. Nickovic, and I. Tegen: A hemispheric dust storm affecting the Atlantic and Mediterranean (April 1994): Analyses, modeling, ground-based

measurements and satellite observations. J. Geophys. Res.,

submitted.

Tegen, I., A. Lacis, and I. Fung, 1996: The influence of

mineral aerosol from disturbed soils on the global radiation budget. Nature, 380, 419-422.

Tegen, I., P. Hollrigl, M. Chin, I. Fung, D. Jacob, and J.

Penner, 1997: Contribution of different aerosol species to

the global aerosol extinction optical thickness: Estimates

from model results. J. Geophys. Res., 102, 23,895-23,915.

Tegen, I., and R. Miller: A GCM study on the interannual

variability of soil dust aerosols. J. Geophys. Res., 102, in

press.
328 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

The Role of Natural and Anthropogenic

Aerosols in Earth’s Radiation Budget and

Climate: Microphysical Simulations with the

NCAR Community Climate Model

Principal Investigator – Owen B. Toon

Science Background

Clouds and aerosols play a significant role in the Earth’s

atmosphere. They significantly affect the radiation budget, they impact atmospheric chemistry, and they interfere with satellite remote-sensing measurements. During

the past two decades we have constructed numerical models of the microphysical, chemical, optical, and radiative

properties of clouds and aerosols in both the stratosphere

and troposphere and applied these models to problems of

importance in the Earth’s radiation budget, climate, and

atmospheric chemistry. We have conducted global-scale

three-dimensional simulations of the stratospheric dispersion of debris from the Mt. Pinatubo and El Chichón eruptions as well as one-dimensional simulations of the microphysical evolution of the Mt. Pinatubo volcanic cloud.

We successfully compared these simulations with data

from several satellites and from aircraft and balloon campaigns, demonstrating the sensitivity of volcanic cloud

transport to meteorology at the time of the eruptions. We

have simulated the evolution of Saharan dust storms, and

the continental-scale expansion of smoke from forest fires

in three dimensions. We compared these calculations with

data from satellites, and showed among other things that

the cooling observed beneath smoke clouds could be numerically simulated. We have investigated the interactions

between aerosols and cirrus clouds as well as the interactions between aerosols and stratus clouds. We employed

satellite and in situ observations of ship tracks as a test of

our modeling skills for stratus clouds, and showed that

the cloud albedo, and even the depth of the marine boundary layer, could be affected by aerosols. We helped design, and participated in, an airborne campaign to investigate similar issues for cirrus clouds.

Science Goal

We plan to use EOS data to improve the accuracy of numerical simulations of clouds and aerosols, and to extend

them to the global scale by collaboration with the NCAR

Community Climate Modeling (CCM) group. We will

compare the results of these simulations with observations from currently available sensors and EOS instruments, as their data become available. Initially we will

conduct our global-scale modeling using a model that

employs the physics package from the CCM driven by

observed winds. We will first consider primary aerosols

which are directly emitted into the atmosphere such as

mineral aerosols, carbonaceous aerosols, and sea salt.

These aerosols are relatively simple to model because they

are not chemically active. Then, we will proceed by including secondary aerosols (sulfates and nitrates), which

are more complex because they are produced by gas-toparticle conversion through a complicated chain of chemical and physical processes. Our goal will be to evaluate

the direct and indirect climate effects caused by multicomponent aerosols with time-dependent properties. Previous GCM studies were focused on a given aerosol component or a mixture of components with prescribed fixed

properties. We will recommend simple prescriptions for

including indirect effects of aerosols on clouds in the CCM

and evolve to more-detailed algorithms. We will also continue process-scale modeling so that we can learn from

detailed comparisons with field data how best to model

aerosols and their interactions with clouds.

Current Activities

We are currently pursuing two issues. Scientists at GISS

have used satellite observations of clouds to develop

parameterizations for use in their climate model. We are

using a three-dimensional cloud model to investigate these

parameterizations to determine the physical process that

may be responsible. Our objective is to determine if the

observations used to make the parameterizations can be

used to extrapolate to conditions other than the ones that

occurred when the observations were made. In short we

are trying to establish the physics behind these empirical

cloud parameterizations. Our other current project is threedimensional simulations of aerosols that have been observed by multiple satellite sensors. In particular we are

modeling dust storms observed by LITE, AVHRR, and

METEOR-TOMS. One goal is to test our ability to reproduce the observations from these space-based sensors,

each of which is sensitive to different aspects of the aerosols. Another goal is to better determine how well the
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 329

aerosol-retrieval algorithms used by these instruments are

able to uniquely determine the properties of the aerosols.

Finally, we are trying to determine what information not

currently available, such as aerosol optical constants, is

needed to improve the ability of EOS instruments to retrieve aerosol characteristics properly.

Use of Satellite Data

At the present time we are interacting with data from the

TOMS instrument, LITE, and AVHRR.

Participation in Field Activities

We have participated in a number of field activities in the

past few years, and anticipate several others in the next

few years. We participated in the Monterey Area Ship

Track (MAST) field program, a joint Navy/NASA program designed to understand the ways in which aerosols

affect clouds. In this case a number of ships emitted aerosols into marine-stratus clouds. The changes in cloud albedo and other properties were observed from aircraft and

satellites. We have analyzed some of these data to test

parameterizations of the indirect effects of clouds on aerosols. We also played a major role in NASA’s SUbsonic

aircraft: Contrail and Cloud Effects Special Study (SUCCESS) field project. This project was aimed at better understanding the impact of aviation on clouds and at better

understanding the ability to remotely sense the properties

of clouds. This multi-aircraft campaign obtained a wealth

of data that indicate the difficulty of detecting contrails

from space, and illustrate the difficulty of correctly obtaining cloud-particle size and other data from remotesensing measurements.

Principal Investigator

Owen Brian Toon

Brian Toon completed an A. B. in physics at U. C. Berkeley in 1969 and a Ph.D. in physics at Cornell University

in 1975 with Professor Carl Sagan. He joined NASA

Ames’ civil service staff in 1978 and retired from the federal government in 1997. He became a Professor in the

Atmospheric and Oceanic Department and a member of

the Laboratory for Atmospheric and Space Physics at the

University of Colorado in 1997.

His research is focused on radiative transfer, aerosol

and cloud physics, as well as atmospheric chemistry. He

has published about 200 papers. He was the Deputy Project

Scientist for the 1987 Airborne Antarctic Ozone Expedition, and the DC-8 Flight Scientist in the 1989 and 1992

Airborne Arctic Stratospheric Expeditions, which sought

to understand the reasons for polar-ozone loss. He was

the co-Project Scientist for the Tropical Ozone Transport

Experiment, a 1995-96 aircraft mission to investigate

stratospheric transport processes in the Arctic and in the

tropics. He was also the Project Scientist for the Subsonic

Aircraft: Contrail and Cloud Effect Special Study, a 1996

multi-aircraft campaign whose goal was to learn about

the formation and radiative properties of cirrus clouds and

the effects that aircraft may have on them. In addition to

being an EOS IDS he is a team member of HIRDLS.

Toon received NASA’s medal for Exceptional Scientific Achievement in 1983 for studies of the climates of

Earth and the planets, and again in 1989 for work on the

ozone hole. He was a co-winner of the American Physical Society’s 1985 Leo Szilard Award for Physics in the

Public Interest for his work on nuclear winter. He received

the Washington D.C. Jaycees’ 37th Annual Arthur

Flemming Award for outstanding individual performance

in the Federal Government. He was elected a Fellow of

the American Meteorological Society in 1990, and a Fellow of the American Geophysical Union in 1992.

Co-Investigators

Irina Sokolik - University of Colorado, Boulder

Andy Ackerman - University of Colorado, Boulder

Eric Jensen - NASA/Ames Research Center

References

Ackerman, A.S., O.B. Toon, and P.V. Hobbs, 1995: Numerical modeling of ship tracks produced by injections

of cloud condensation nuclei into marine stratiform clouds.

J. Geophys. Res., 100, 7121-7134.

Toon, O.B., 1995: Modeling the relationships between

aerosol properties and the direct and indirect effects of

aerosols on climate. Aerosol Forcing of Climate, Dahlem

Workshop Report ES 17, R.J. Charlson and J.

Heintzenberg, Eds., J. Wiley & Sons, 197-213.

Zhao, J., R.P. Turco, and O.B. Toon, 1995: A model simulation of Pinatubo volcanic aerosols in the stratosphere. J

Geophys. Res., 100, 7315-7328.

Sokolik, I., and O.B. Toon, 1996: Direct radiative forcing

by anthropogenic airborne mineral aerosols. Nature, 381,

681-683.

Jensen, E.J., O.B. Toon, H.B. Selkirk, and J. Spinhirne,

1996: On the formation and persistence of subvisible cirrus clouds near the tropical tropopause. J. Geophys. Res.,

101, 21,361-21,376.

Investigation URL

http://lerxst.colorado.edu/groupweb/
330 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

A Numerical Analysis of New Nitrogen

Sources of NO3 and N2 Affecting Carbon

Cycling in the Southern Caribbean Sea: A Key

to CDOC Contamination of Satellite Color

Signals

Principal Investigator – John J. Walsh

Science Background

A simple numerical model (Walsh and Dieterle 1994;

Walsh et al.1997) of carbon/nitrogen cycling within the

Bering/Chukchi Seas and early field observations of total

DOC and chlorophyll biomass in the North Sea first suggested that ~50% of the CZCS color signal, sensed above

the 70-m isobath of these sub-polar shelves, might be

composed of colored dissolved organic carbon (CDOC).

A more-complex, spectral bio-optical model (Hochman

et al.1995) of the western English Channel indeed indicated that 39%of the color signal after the spring bloom

and 46-76% during the fall overturn was CDOC contamination of Case-II shelf waters. A similar third spectral

model (Bissett et al. 1998a), embedded within our morecomplex food-web model (Bissett et al. 1998b) of multiple phytoplankton groups, replicated some recent biooptical observations at the JGOFS time series site in the

Sargasso Sea. Our most recent analysis of the BATS data

suggests that absorption of light by CDOC at both 412

nm and 442 nm is equivalent to that by pigments for two

30-day periods, after the spring bloom and during the fall

overturn, even within Case-I waters around Bermuda!

Finally, in the southern Caribbean Sea, away from the

influence of the Orinoco River, preliminary model simulations (Walsh et al. 1998) and a 1995-1998 in situ time

series in the Cariaco Basin concur in suggesting that past

CZCS imagery may have overestimated seasonal changes

of phytoplankton biomass here as well.

Science Goal

In the otherwise oligotrophic Caribbean Sea, distinct seasonal periods of wind-forced upwelling, deposition of Ferich Saharan aerosols, and river discharge provide a unique

opportunity to examine the persistence of CDOC, provided by: 1) physical injection from the aphotic zone, 2)

biological release from surface blooms of the cyanophyte,

Trichodesmium, which provide DOM at a rate of as much

as 50% of N2 -fixation, and 3) lateral supply from land.

We wish to test the hypothesis that after injection of “new”

nitrogen, by coastal upwelling during the winter/spring,

by nitrogen-fixation in the summer, and by river runoff in

the fall, CDOC of distinct physical and biological origins

will continue to contaminate the color signals of the southern Caribbean Sea, seen now by the SeaWiFS sensor. Similarly, in the eastern Gulf of Mexico, arrival of Saharan

aerosols during June-July may stimulate cyanophyte

blooms on the oligotrophic West Florida shelf, serving as

an ultimate nutrient source for subsequent noxious redtides (Walsh 1996), sensed later in the fall by past CZCS

imagery (Gilbes et al. 1996).

Current Activities

We are now using our coupled biological/physical models of carbon/nitrogen cycling by phytoplankton, zooplankton, and bacteria to assess the impacts of nitrogen

fixation and upwelling during new production within the

shelf environs of the Cariaco Basin. During spring upwelling in response to a mean wind forcing of 8 m sec-1,

the physical model matches AVHRR and hydrographic

estimates of surface temperature. Within the 3-D flow

field, the steady solutions of the biological model of a

simple food web of diatoms, adult copepods, and ammonifying/nitrifying bacteria underestimate by ~9%, however,

the mean spring observations of settling fluxes caught by

a sediment trap at ~240 m, moored at our time-series site

in the Basin.

The models also overestimate by ~12% the average

14C net primary production and by ~29% the chlorophyll

biomass at the site, but they do mimic the observed spatial fields of nitrate and light penetration during the same

time period of February-April. To evaluate the importance

of CDOC impact on both the amount of refractory metabolites and light-regulated primary production, one must

have some understanding of its time-dependent sources

and sinks (Walsh et al. 1992). To explore the above lack

of covariance between CDOC and other optical properties, we considered both a strongly colored and weaker

source of CDOC. We conclude that smaller amounts of

CDOC are a correct description of the site’s light field
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 331

during spring, but not in the summer/fall cases of the

model (Walsh et al. 1998).

Addition of a slow-growing cyanophyte, with another

source of new nitrogen and large releases of DOM, would

remedy the deficiencies of the models, attributed to use

of a single phytoplankton group, i.e., diatoms. Indeed,

our del15N isotope budgets of dissolved and particulate

forms of nitrogen suggest that neglected diazotrophs may

contribute 19-34% of new production during spring, none

in summer, and 57-78% in fall. We were able, based on

the structure of the simulation models, to match del15N

of particulate matter suspended in the water column and

caught by sediment traps in the Cariaco Basin (Walsh et

al. 1998).

Use of Satellite Data

Using concurrent AVHRR imagery of SST and aerosol

optical thickness to distinguish different periods of upwelling and of iron deposition, the time-dependent introduction of CDOC to surface waters, by both physical supply and phytoplankton loss, will be analyzed in relation

to the photolysis there of CDOC and to the changing seasonal contamination of SeaWiFS images above both the

Venezuelan shelf of the southern Caribbean Sea and the

West Florida shelf of the Gulf of Mexico.

Participation in Field Activities

Further assessment of the spring nitrogen/carbon economies of the Venezuelan shelf requires: 1) representation

of Trichodesmium as an explicit state variable of a morecomplex model, 2) an analysis of their role in other seasons of the year, 3) consideration of the time-dependent

delivery of atmospheric nutrients, e.g., iron, and 4) addition of picoplankton and protozoan components of the

microbial food web as co-occurring state variables with

diatoms and cyanophytes. Time series of CDOM, DOM,

and the optical signatures of the excretory products of

diatoms, cyanophytes, flagellates, and their predators are

similarly required.

Validation data of the bio-optical part of these analyses will thus consist of in-water optical measurements

made along the Venezuelan coast, from the mouth of the

Orinoco River to the stenohaline Cariaco Basin, as part

of separately funded NASA SIMBIOS and EOS Interdisciplinary projects at USF, conducted by my colleague

Frank E. Muller-Karger. Additional field data on dissolved

Fe, del15N of particulate matter, and Trichodesmium abundance, will be collected during dust events on the west

Florida shelf as part of a NOAA/EPA/ONR ECOHAB

project. Finally, a NASA pre-doctoral fellowship is supporting the thesis work of Mr. Chris Cattral, under the

supervision of Ken Carder at USF, to estimate the aerosol

content seen by SeaWiFS during Saharan outbursts.

Principal Investigator

John J. Walsh

John J. Walsh recieved M.S and Ph.D. degrees at the University of Miami and was a pre- and postdoctoral fellow

at Oak Ridge National Laboratory and the University of

Washington. He is currently a Distinguished Research

Professor at the University of South Florida and is the

author of two books and over 90 papers on biological

oceanography. His awards include a Pre-doctoral Fellowship, Ford Foundation (1967); Gold Medal of Science,

University of Liege (1980); Fellow of the Amer. Assoc.

Adv. Sci. (1990); and Professorial Excellence Program,

USF (1996). His research covers systems analysis of continental shelves, biological components of global carbon

and nitrogen budgets, and numerical models of marine

food webs, constrained by satellite data sets.

References

Bissett, W.P., K.L. Carder, J.J. Walsh, and D.A. Dieterle:

Carbon cycling in the upper waters of the Sargasso Sea,

II, Numerical simulation of apparent and inherent optical

properties. Deep-Sea Res., in press.

Bissett, W.P., J.J. Walsh, D.A. Dieterle, and K.L. Carder:

Carbon cycling in the upper waters of the Sargasso Sea,

I, Numerical simulation of differential carbon and nitrogen fluxes. Deep-Sea Res., in press.

Gilbes, F., C. Tomas, J.J. Walsh, and F.E. Muller-Karger,

1996: An episodic chlorophyll plume on the west Florida

shelf. Cont. Shelf Res., 16, 1201-1224.

Hochman, H.T., J.J. Walsh, K.L. Carder, A. Sournia, and

F.E. Muller-Karger. 1995: Analysis of ocean color components within stratified and well-mixed waters of the

western English Channel. J. Geophys. Res., 100, 10,777-

10,787.

Walsh, J.J. 1996: Nitrogen-fixation within a tropical upwelling ecosystem: Evidence for a Redfield budget of carbon/nitrogen cycling by the total phytoplankton community. J. Geophys. Res., 101, 20,607-20,616.

Walsh, J.J., K.L. Carder, and F.E. Muller-Karger, 1992:

Meridional fluxes of dissolved organic matter in the North

Atlantic. J. Geophys. Res., 97, 15,625-15,637.

Walsh, J.J., and D.A. Dieterle, 1994: CO2

 cycling in the

coastal ocean. I. A numerical analysis of the southeastern

Bering Sea, with applications to the Chukchi Sea and the

northern Gulf of Mexico. Progr. Oceanogr., 34, 335-392.
332 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Walsh, J.J., D.A. Dieterle, F.E. Muller-Karger, K. Aagaard,

A.T. Roach, T.E. Whitledge, and D. Stockwell, 1997: CO2

cycling in the coastal ocean. II. Seasonal organic loading

to the Canadian Basin from source waters south of Bering

Strait. Cont. Shelf Res., 17, 1-36.

Walsh, J.J., D.A. Dieterle, F.E. Muller-Karger, R. Bohrer,

W.P. Bissett, R. Aparicio, R. J. Varela, H.T. Hochman, C.

Schiller, R. Diaz, R. Thunell, G.T. Taylor, M.I. Scranton,

K.A. Fanning, and E.T. Peltzer: Isotope constraints on

numerical simulation of carbon/nitrogen cycling during

spring upwelling in the Cariaco Basin. J. Geophys. Res.,

submitted.
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 333

An Interdisciplinary Investigation of Clouds

and the Earth’s Radiant Energy System:

Analysis (CERES-A)

Principal Investigator – Bruce A. Wielicki

Science Background

The CERES-A interdisciplinary science (IDS) investigation examines the role of clouds and radiative energy balance in the climate system. Studies include cloud feedback mechanisms, which can greatly modify the response

of the climate system to increased greenhouse gases. Initial CERES-A general circulation modeling (GCM) studies have shown that cloud-radiative heating might enhance

the strength of the Hadley cell by as much as a factor of

two.

A typical research strategy for studies of global systems must encompass scientific problems at a wide range

of time and space scales. We develop and apply a series

of radiative and dynamical cloud models that range from

highly detailed Large Eddy Simulation models which resolve scales between 50 meters and 5 km, to greatly simplified GCM cloud models which resolve scales between

200 km and global. Definitive progress is achieved

through a combination of careful observations and modeling studies made across all of the scales important for

the understanding of cloud and radiation processes.

This IDS investigation is closely tied to the CERES

instrument investigation. Our studies will be used to validate CERES instrument measurements and will use the

CERES instrument data to study the role of clouds in the

climate system. The CERES instrument investigation focuses on production of the cloud and radiation budget data

needed for our investigation and other EOS-sponsored

studies. These data products utilize not only CERES

broadband radiance data, but also depend critically on

cloud data derived using the VIRS (Visible and Infrared

Scanner) on TRMM and using MODIS on Terra and EOS

PM. The cloud properties are matched to each CERES

broadband field of view, allowing derivation of a consistent set of cloud properties and radiative fluxes. The

CERES instrument provides radiative flux estimates at

the top of the atmosphere, at the surface, and at several

levels within the atmosphere. These data are critical to

the CERES-A climate-system studies.

Science Goals

Goals of the investigation include: 1) extend the studies

of cloud-radiative effects beyond the top of the atmosphere

to the radiative balance at the surface of the Earth and to

radiative heating/cooling within the atmosphere; 2) extend the studies of cloud-radiative effects using the moreaccurate CERES top-of-atmosphere radiative fluxes; 3)

examine the use of satellite-derived radiative fluxes to

develop improvements in medium-range forecasting; and

4) validate the cloud properties and radiative fluxes produced by the CERES instrument investigation.

Current Activities

Studies are under way to examine the role of clouds in

the tropical ocean heat balance, to examine the amount of

atmospheric heating produced by the absorption of solar

energy in clouds, and to examine potential cloud feedback systems. Studies have also included determination

of the impact of the Pinatubo eruption on the Earth’s radiative-energy balance.

Prospective validation of CERES instrument observations relies on direct observations of surface radiative

fluxes (shortwave and longwave) as well as cloud properties using surface remote sensing (radiometers, lidar,

and radar). Key surface data are being obtained, working

jointly with the DoE ARM (Atmospheric Radiation Measurement) program, the BSRN (Baseline Surface Radiation Network) of the World Climate Research Program,

the Surface Radiation Budget and the NASA FIRE (First

ISCCP [International Satellite Cloud Climatology Project]

Regional Experiment).

Use of Satellite Data

This interdisciplinary investigation will use the CERES

instrument investigation data products as its prime source

of global data on cloud properties and radiative fluxes.

Other important input data for this investigation will include temperature and humidity profiles (NCEP, ECMWF,

and EOS DAO 4-D assimilation), sea-surface and land

temperatures (MODIS, AIRS), cloud liquid water (TMI,

AMSR-E), and ocean-surface winds (scatterometers).

Other satellite data will also be examined to provide coverage of the global oceans and polar regions. For cloud

properties, satellite-based lidar (GLAS) as well as a potential future cloud radar system (CloudSat) placed into

synergistic orbit with EOS PM will be key to determin-
334 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

ing the effects of optically thin cirrus and overlapping

cloud layers and for validating EOS cloud-property retrieval methods. For validating the effects of non-planeparallel clouds, the EOS MISR multi-angle radiance data

will provide key tests of the accuracy of cloud-radiative

models and remote sensing.

Participation in Field Programs

The CERES-A investigation is working closely with the

FIRE cloud field experiment, which will be examining

polar clouds and tropical cirrus in the next 5 years.

CERES-A is also coordinating closely for a long time

series of surface and in-atmosphere radiative flux measurements being taken as part of the DOE ARM program,

the GEWEX (Global Energy and Water cycle Experiment), and the WCRP BSRN surface-measurement program.

Principal Investigator

Bruce A.Wielicki

Bruce Wielicki was awarded a Ph.D. in Physical Oceanography from the Scripps Institution of Oceanography in

1980. He has focused primarily on atmospheric research

concerning cloud properties, cloud remote sensing, and

the Earth’s radiation budget. Following a 3-year assignment at NCAR, Wielicki joined the NASA/Langley Research Center as a Research Scientist in 1980. At NASA

he served as a Principal Investigator on the Landsat Thematic Mapper and Earth Radiation Budget Experiment

(ERBE) science teams. He currently is a Principal Investigator for the First ISCCP Regional Experiment (FIRE).

Wielicki received the NASA medal for Exceptional Scientific Achievement in 1992 and the American Meteorological Society Houghton Award in 1995.

Co-Investigators

Robert D. Cess - State University of New York at Stony

Brook

James A. Coakley, Jr. - Oregon State University

Dominique Crommelynck - Royal Meteorological Institute, Belgium

Leo J. Donner - NOAA/Geophysical Fluid Dynamics

Laboratory

Robert S. Kandel - CNRS Ecole Polytechnique, France

Michael D. King - NASA/Goddard Space Flight Center

Alvin J. Miller - NOAA/National Centers for Environmental Prediciton

V. Ramanathan - Scripps Institution of Oceanography

David A. Randall - Colorado State University

G. Louis Smith - Virginia Polytechnic Institute and State

University

Larry L. Stowe - NOAA/NESDIS

Ronald M. Welch - University of Alabama/Hunstville

The following are from NASA/Langley Research Center:

Bruce R. Barkstrom

Bryan A. Baum

Thomas P. Charlock

Richard N. Green

David P. Kratz

Robert B. Lee III

Patrick Minnis

David F. Young

References

Cess, R.D., M.H. Zhang, P. Minnis, L. Corsetti, E.G.

Dutton, B.W. Forgan, D.P. Garber, W.L. Gates, J.J. Hack,

E.F. Harrison, X. Jing, J.T. Kiehl, C.N. Long, J.-J.

Morcrette, G.L. Potter, V. Ramanathan, B. Subasilar, C.H.

Whitlock, D.F. Young, and Y. Zhou, 1995: Absorption of

solar radiation by clouds: Observations versus models.

Science, 267, 496-499.

Fowler, L.D., and D.A. Randall, 1994: A global radiative

convective feedback. Geophys. Res. Lett., 21, 2035-2038.

Minnis, P., E.F. Harrison, L.L. Stowe, G.G. Gibson, F.M.

Denn, D.R. Doelling, and W.L. Smith, Jr., 1993: Radiative forcing by the Mount Pinatubo eruption. Science, 259,

1411-1415.

Ramanathan, V., B. Subasilar, G.J. Zhang, W. Conant, R.D.

Cess, J.T. Kiehl, H. Grassl, and L. Shi, 1995: Warm pool

heat budget and shortwave cloud forcing: A missing physics? Science, 267, 499-503.

Wielicki, B. A., R. D. Cess, M. D. King, D. A. Randall,

and E. F. Harrison, 1995: Mission to Planet Earth: Role

of Clouds and Radiation in Climate. Bull. Amer. Meteor.

Soc., 76, 2125-2153.

Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B.

Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and

the Earth’s Radiant Energy System (CERES): An Earth

Observing System Experiment. Bull. Amer. Meteor. Soc.,

77, 853-868.

Investigation URL

http://asd-www.larc.nasa.gov/ASDhomepage.html
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 335

Terrestrial Hydrology and Climate Studies

Using EOS-Era Data

Principal Investigator – Eric F. Wood

Science Background

Understanding the role of the terrestrial hydrosphere-biosphere in Earth’s climate system, especially in the coupling of land-surface hydrologic processes to atmospheric

processes over a range of spatial and temporal scales, the

role of the land surface in climate variability and climatic

extremes, and its role in climate change and terrestrial

productivity are integral components of EOS science objectives for terrestrial hydrology and ecology (Running

et al. 1997). They also are central science objectives of

the World Climate Research Program (WCRP) activities

under GEWEX, and, in particular, the GEWEX continental-scale experiments (GCIP, BALTEX, MAGS, LBA, and

GAME).

There is an extensive body of research over the last

30 years to support the contention that land-surface processes control local climate through the partitioning of

precipitation and incoming radiation into their budget

components. What is not well understood are the mean

values and variability of the water- and energy-budget

terms over a range of temporal and continental-to-global

spatial scales. The inherent research strategy for EOS

and WCRP/GEWEX for investigating these issues is

through process-based, terrestrial water- and energy-balance models. This strategy was developed because the

historical record related to the terms in the water- and

energy-balance equations is too short, and the required

spatial and temporal observations are too extensive, costly,

and logistically impractical to support the analysis.

Large-scale applications of energy- and water-balance models are greatly complicated by the scarcity of

land-surface observations and difficulties in representing

hydrological processes at large scales. This recognition

in the early 1980’s resulted the establishment of climate

experimental programs like HAPEX (Hydrology Atmospheric Parameterization EXperiment) and ISLSCP (International Satellite Land Surface Climatology

Programme) as initiatives of the WMO/ICSU Joint Scientific Committee for WCRP. In the late 1980s, ICSU

established a core project on the Biospheric Aspects of

the Hydrological Cycle (BAHC) with a research focus on

the spatial and temporal integration of biospheric-hydrospheric interactions. In addition, the above strategy supported remote-sensing initiatives which resulted in the

recent availability of consistent, long-term remote sensing records, such as AVHRR (Agbu, 1993), GOES (Young,

1995) and SSM/I (Hollinger et al., 1992) Pathfinder data

sets; the compilation of remote-sensing data as part of

ISLSCP initiatives (Sellers et al., 1994, Meeson et al.,

1995), recent advances in remote-sensing algorithms for

deriving forcing variables such as radiation, humidity, and

surface air temperature; and the development of new remote-sensing instruments such as TRMM (for precipitation) and the future suite of EOS sensors that may be used

directly or indirectly to estimate the required variables.

Scientific Motivation and Goals

Achievement of the WCRP GEWEX science objectives

to understand the seasonal, annual, and interannual variability of water and energy cycles, and the EOS science

objectives for terrestrial hydrology and ecology requires

continental-to-global-scale fields of water and energy

fluxes and storages at high spatial and temporal resolution that need to be well validated.

Implicit within GEWEX and EOS science plans is

the belief that remote sensing will provide products that

are appropriate for hydrological modeling, and that the

current generation of models can ingest these products

and provide the continental-to-global fields to address the

scientific objectives. It is the central premise of this research proposal that this research strategy is feasible, but

it still needs to be demonstrated at continental and global

scales. Furthermore, it needs to be demonstrated that

model-derived water and energy fluxes can provide the

necessary data for in-depth analyses of the seasonal, annual, and interannual variability of the terrestrial water

and energy balances at regional-to-global scales.

Thus, the goals of the proposed research are to demonstrate that continental-to-global-scale water and energy

balance fields can be estimated through a combination of

process-based terrestrial hydrological models and remotesensing inputs, and that diagnostic studies with these

model-derived fields can be carried out to further our understanding of the role of land-surface processes in the

global hydrological cycle.
336 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Science Issues and Questions

Science issues central to the proposed research include:

• What are the characteristics of the terrestrial surface

water and energy balances, including their seasonal,

annual, and interannual variability over a range of temporal and spatial scales, and how do these characteristics vary in different climates and locations on Earth?

• What role does the terrestrial hydrosphere-biosphere

play in Earth’s climate system, including the factors

that control partitioning of precipitation and incoming

radiation and their budget components, and how do

these factors vary with climatic, conditions (including

changes in land-surface conditions) and seasonality?

To answer these issues, requires a consideration of the

following research questions:

• What are the spatial and temporal resolution and accuracy requirements of continental-scale water- and energy-balance fields needed to answer the GEWEX and

EOS science objectives related to water and energy balances?

• Can these requirements be achieved through a combination of hydrological modeling and remote sensing,

including a determination of which remote-sensingderived products are most appropriate for hydrological

modeling at continental-to-regional scales?

• Can model-derived, continental-scale water- and energy-balance fields be validated and if so, how?

Research Strategy

A multi-scale research strategy has been developed that

provides an end-to-end proof-of-concept for the research

strategy for selected periods. This

research strategy can be summarized as follows:

1) The development, calibration, and validation of process-based hydrologic models using data from smallscale land-surface experiments (Liang et al. 1994;

Liang et al. 1996; PetersLidard et al. 1997);

2) The use of the developed

models to scale up to larger

spatial scales on the order of

105 sq km, with foci on

model parameterizations at regional scales and on

testing remote-sensing products in the hydrological

models (Abdulla et al. 1996; Nijssen et al. 1997;

Wood et al. 1997); and

3) The simulation of continental-to-global fields of water and energy fluxes through modeling and remote

sensing, and their validation using large-scale hydrologic data (Dubayah et al. 1997).

Table 1 illustrates the implementation of this strategy.

Current activities are directed towards extending these

results at larger regional-to-global-scale basins, validation of the water- and energy-balance models at these

scales, testing of remote-sensing products, and initial diagnostic analyses using model-based fields of water and

energy flux and storage variables. Initial global water

balance simulations have been carried out using observed

daily precipitation and temperature data. A global validation strategy is being developed around a set of continental-scale river basins distributed globally, including

the major GEWEX basins.

Current Use Of Satellite Data

Solar Radiation: Incoming and net solar radiation are

derived using the GOES-VISSR sensor (e.g., Pinker et

al. 1992; Whitlock et al. 1995; Dubayah and Loechel

1997).

Air Temperature: Spatially-varying air temperature may

be estimated using AVHRR data as shown in Goward et

al. (1994), Prince and Goward (1995), Prihodko and

Goward (1997), Prince et al. (1997), and Dubayah et al.

(1997). Dubayah et al. (1997) also have shown how

TOVS-derived air temperature may be used for hydrological modeling.

Table 1: Implementation of observation-modeling strategy

 Modeling/ Scale (sq. km) Research focus Research Data set/

Observations Objective experiment

Small Scale 102-103 Process Land-atmospheric FIFE,

modeling interactions BOREAS

SIR-C, PILPS

Medium Scale 104-105 Coupled Scaling GCIP-SW

models

Remote Test Red-Arkansas

sensing algorithms basins

Large Scale 105

-106 Budget analysis continental- PILPS-2c,

scale variability ISLSCP,

Schnur and

Lettenmaier (1997)
1999 EOS Reference Handbook Interdisciplinary Science Investigations • 337

Surface Humidity: Total-column precipitable water may

be derived in a variety of ways, including the split-window differential-absorption techniques used in AVHRR

and GOES methods, as well as the sounding and dataassimilation strategy using TOVS data (Dubayah et al.

1997).

Precipitation: Estimation of precipitation by satellite remote sensing remains problematic at time scales required

by hydrologic models (see Adler et al. 1994). While missions such as TRMM have great promise for improving

climatological estimates of precipitation, and perhaps for

estimating areal precipitation at monthly-to-seasonal time

steps, the current (and planned) platforms suffer from an

inability to observe the diurnal cycle directly.

Pre-EOS remote-sensing data products expected to be

available include precipitation (GPCP Version 1a Combined Precipitation Data Set [Huffman 1996]), vegetation/land-use products developed by the MODIS instrument team (Running et al. 1997), snow extent and snowwater-equivalent data sets archived at the National Snow

and Ice Data Center, and global atmospheric water-vapor

products from TOVS.

Participation in Field Activities

The science strategy uses data sets from small-scale landsurface experiments for the development, calibration, and

validation of process-based hydrologic models, and data

from continental-scale GEWEX projects to develop model

parameterizations at regional scales, to test remote-sensing products in the hydrological models, and to validate

the models at regional-to-continental scales.

As part of this strategy, we will utilize and participate in a wide variety of field experiments. To date we

have used data from the following experiments: the First

ISLSCP Fields Experiment, the Boreal Ecosystem-Atmospheric Study (BOREAS) (see http://www.princeton.edu/

~eewr/hydrology); the GEWEX Continental Scale Project

(GCIP) in the Mississippi River basin; Mackenzie

GEWEX Study (MAGS); Southern Great Plains (SGP)

Experiment.

Principal Investigator

Eric F. Wood

Eric F. Wood is a terrestrial hydrologist at Princeton University (in the Program for Environmental Engineering

and Water Resources, Department of Civil and Environmental Engineering). He received his doctorate from the

Massachusetts Institute of Technology in 1974 working

with Ignacio Rodriguez-Iturbe in statistical hydrology.

After a 30-month research appointment at the International Institute for Applied Systems Analysis in

Laxenburg, Austria, he was appointed as an Assistant Professor at Princeton University, being promoted to Associate Professor in 1981 and Full Professor in 1986. He served

as the Director of the Water Resources Program from

1982-1993. He is a Fellow of the American Geophysical

Union and the American Meteorology Society, and has

served or serves on numerous journal editorial boards,

society committees, and NRC’s Water Science and Technology Board and Board on Atmospheric Science and

Climate. His research focuses on hydroclimatology and

remote sensing, with an emphasis on land-surface hydrologic parameterization and their scaling behavior over a

range of spatial and temporal scales with interests ranging from tower scales to continental domains. He has been

an investigator in a number of ISLSCP field experiments

including FIFE and BOREAS, and in SIR-C; using this

field and remote sensing data as an integral part of his

model development and

validation research.

Co-Investigators

Dennis Lettenmaier, - University of Washington

Ralph Dubayah - University of Maryland

References

Abdulla, F.A., D.P. Lettenmaier, E.F. Wood, and J.A.

Smith, 1996: Application of a Macroscale Hydrological

Model to Estimate the Water Balance of the ArkansasRed River Basin. J. Geophys. Res.

Adler, R.F., G.J. Huffman, and P.R. Keehn, 1994: Global

rain estimates from microwave-adjusted geosynchronous

IR data. Remote Sens. Rev., 11, 125-152.

Agbu, P., B. Vollmer, and M. James, 1993: Pathfinder

AVHRR land data set, NASA Goddard Space Flight Center, Greenbelt, MD.

Dubayah, R., E.F. Wood, M. Zion, and K. Czajkowski,

1997: A remote sensing approach to macroscale hydrological modeling, in Schultz, G. and E. Engman (Eds.)

Remote sensing in hydrology and water management,

Springer-Verlag.

Dubayah, R., and S. Loechel, 1997: Modeling topographic

solar radiation using GOES data. J. Appl. Meteor., 36,

141-154.

Goward, S.N., R.H. Waring, D.G. Dye, and J. Yang 1994:

Ecological remote sensing at OTTER: satellite macroscale

observations. Ecological Appl., 4, 332-343.

Hollinger J., J. Pierce, and G. Poe., 1990: SSM/I instrument evaluation. IEEE Trans. Geosci. and Remote Sens.,

28, 781-790.
338 • Interdisciplinary Science Investigations 1999 EOS Reference Handbook

Huffman, G.J., 1996: GPCP Version 1a combined precipitation data set documentation, Laboratory for Atmospheres, NASA Goddard Space Flight Center, September

9, 1996.

Liang, X., E.F. Wood, and D.P. Lettenmaier, 1996: Surface Soil Moisture Parameterization of the VIC-2L Model:

Evaluation and Modifications. Global and Planetary

Change, 13, 195-206.

Liang, X., D.P. Lettenmaier, E.F. Wood, and S.J. Burges,

1994: A Simple Hydrologically Based Model of Land

Surface Water and Energy Fluxes for General Circulation Models. J. Geophys. Res., 99, 14,415-14,428.

Meeson, B.W., F.E. Corprew, J.M.P. McManus, D.M.

Myers, J.W. Closs, K.J. Sun, J. Sunday, and P.J. Sellers,

ISLSCP Initiative I-Global Data Sets for Land Atmosphere Models, 1987-1988, Vols. 1-5, NASA, CD-ROM,

1995.

Nijssen, B., D.P. Lettenmaier, X. Liang, S.W. Wetzel, and

E.F. Wood, 1997: Simulation of Runoff from Continental-Scale River Basin using a Grid-Based Land Surface

Scheme. Water Resour. Res., 33, 711-724.

Peters-Lidard, C., M. Zion, and E.F. Wood, 1997a: A soilvegetation-atmosphere transfer scheme for modeling spatially variable water and energy balance processes. J.

Geophys. Res., 102, 4303-4324.

Pinker, R.T., and I. Laszlo, 1992: Modeling surface solar

irradiance for satellite applications on a global scale. J.

Appl. Meteor., 31, 194-211.

Prihodko, L., and S.N. Goward, Estimation of air temperature from remotely sensed observations. Remote Sens.

Environ., in review.

Prince, S.D., Goetz, S.J., Dubayah, R., Czajkowski, K.,

and M. Thawley, 1997: Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using AVHRR satellite observations: validation of algorithms. J. Hydrol., in press.

Running S., J. Collatz, J. Washburn, and S. Sorooshian,

(editors.) 1997: EOS Science Plan, Chapter 5, Land Ecosystems and Hydrology, NASA HQ, Washington, DC.

Schnur, R., and D.P. Lettenmaier, 1997: Global gridded

data set of daily soil moisture for use in General Circulation Models, presented at the 13th Conference in Hydrology, AMS Meeting, Long Beach, CA.

Sellers, P.J., C.J. Tucker, G.J. Collatz, S.O. Los, C.O. Justice, D.A. Dazlich, and D.A. Randall, 1994: A global 1-

degree by 1-degree NDVI data set for climate studies.

Part2: The generation of global fields of terrestrial biophysical parameters from the NDVI. Int. J. Remote Sensing, 15, 3519-3545.

Whitlock,C.H., T.P. Charlock, W.F. Staylor, R.T. Pinker,

I. Laszlo, A. Ohmura, H. Gilgen, R.C. DiPasquale, S.R.

LeCroy, and N.A. Ritchey, 1995: First Global WCRP Surface Radiation Budget Data Set. Bull. Amer. Met. Soc.,

76, 905-922.

Wood, E.F., D.P. Lettenmaier, X. Liang, B. Nijssen, and

S. W. Wetzel, 1997: Hydrological Modeling of Continental-Scale Basins. Annual Reviews of Earth and Planetary

Sciences, 25, 279-300.

Wu, M.C., and C. Cheng, 1989: Surface downward flux

computed by using geophysical parameters derived

from HIRS 2/MSU soundings. Theor. Appl. Climatol., 40,

37-51.

Young, J., J. Hagens, and D. Wade., 1995: GOES pathfinder product generation system, 9th Conference on Applied Climatology, Dallas, TX, American Meteorological

Society, Boston, MA.
1999 EOS Reference Handbook Points of Contact • 339

Points of Contact

EOS Project Science Office

Michael D. King

Senior Project Scientist

Code 900

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5636

Fax: 301/614-5620

Internet: king@climate.gsfc.nasa.gov

Terra

Yoram J. Kaufman

Project Scientist

Code 913

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6189

Fax: 301/614-6307

Internet: kaufman@climate.gsfc.nasa.gov

EOS PM

Claire L. Parkinson

Project Scientist

Code 971

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5715

Fax: 301/614-5644

Internet: clairep@neptune.gsfc.nasa.gov

EOS Missions and Platforms

Landsat 7

Darrel L. Williams

Project Scientist

Code 923

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6692

Fax: 301/614-6695

Internet: darrel@ltpmail.gsfc.nasa.gov

Jason-1

Lee-Lueng Fu

Project Scientist

Mail Stop 300-323

Jet Propulsion Laboratory

4800 Oak Grove Drive

Pasadena, California 91109

Phone: 818/354-8167

Fax: 818/393-6720

Internet: llf@pacific.jpl.nasa.gov
340 • Points of Contact 1999 EOS Reference Handbook

ICESat

H. Jay Zwally

Project Scientist

Code 971

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5643

Fax: 301/614-5644

Internet: jay@intrepid.gsfc.nasa.gov

EOS CHEM

Mark R. Schoeberl

Project Scientist

Code 910

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6002

Fax: 301/614-5903

Internet: schom@zephyr.gsfc.nasa.gov

ESSP

James J. Garvin

Project Scientist

Code 921

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6504

Fax: 301/614-6522

Internet: garvin@denali.gsfc.nasa.gov

SAGE III

William P. Chu

Project Scientist

Mail Stop 475

NASA/Langley Research Center

Hampton, Virginia 23681

Phone: 757/864-2675

Fax: 757/864-2671

Internet: William.P.Chu@larc.nasa.gov

SORCE

Robert F. Cahalan

Project Scientist

Code 913

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5390

Fax: 301/614-5493

Internet: Robert.Cahalan@gsfc.nasa.gov

EOSDIS

Skip Reber

Project Scientist

Code 900

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5201

Fax: 301/614-5267

Internet: reber@skip.gsfc.nasa.gov

SeaWinds

W. Timothy Liu

Project Scientist

Code 300-323

Jet Propulsion Laboratory

4800 Oak Grove Drive

Pasadena, California 91109

Phone: 818/354-2394

Fax: 818/393-6720

Internet: liu@pacific.jpl.nasa.gov

Validation

David Starr

Validation Scientist

Code 913

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6191

Fax: 301/614-6307

Internet: starr@climate.gsfc.nasa.gov

Calibration

James Butler

Calibration Scientist

Code 925

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5942

Fax: 301/614-5790

Internet: butler@highwire.gsfc.nasa.gov
1999 EOS Reference Handbook Points of Contact • 341

Instruments

ACRIM III

Richard C. Willson

Principal Investigator

Columbia University

1001 B Avenue. Suite 200

Coronado, California 92118

Phone: 619/522-2945 or 619/628-8507

Fax: 619/575-8173 or 619/522-2967

Internet: acrim@znet.com

AIRS/AMSU-A/HSB

Moustafa T. Chahine

Team Leader

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 180-904

Pasadena, California 91109-8099

Phone: 818/354-6057

Fax: 818/393-4218

Internet: moustafa.t.chahine@jpl.nasa.gov

AMSR-E

Roy W. Spencer

Team Leader - U.S.

NASA/Marshall Space Flight Center

Code ES43

977 Explorer Blvd.

Huntsville, Alabama 35806

Phone: 256/922-5960

Fax: 256/922-5788

Internet: roy.spencer@msfc.nasa.gov

Akira Shibata

Team Leader - Japan

National Space Development Agency of Japan/

Earth Observing Research Center

1-9-9, Roppongi

Minato-ku, Tokyo, 106

JAPAN

Phone: 81-33-224-7040

Fax: 81-33-224-7051

Internet: Ashibata@eorc.nasda.go.jp

ASTER

Hiroji Tsu

Science Team Leader - Japan

Earth Remote Sensing Data Analysis Center

(ERSDAC)

Forefront Tower

3-12-1 Kachidoki Chuo-ku

Tokyo, 104

JAPAN

Phone: 81-33-533-9380

Fax: 81-33-533-9383

Internet: tsu@gsj.go.jp

Anne Kahle

Team Leader - U.S.

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 183-501

Pasadena, California 91109

Phone: 818/354-7265

Fax: 818/354-0966

Internet: anne@aster.jpl.nasa.gov

CERES

Bruce R. Barkstrom

Principal Investigator

NASA/Langley Research Center

Mail Stop 420

Hampton, Virginia 23681-2199

Phone: 757/864-5676

Fax: 757/864-7996

Internet: brb@ceres.larc.nasa.gov

EOSP

Larry D. Travis

Principal Investigator

NASA/Goddard Institute for Space Studies

2880 Broadway

New York, New York 10025

Phone: 212/678-5599

Fax: 212/678-5622

Internet: ltravis@giss.nasa.gov
342 • Points of Contact 1999 EOS Reference Handbook

ETM+

Samuel Goward

Team Leader

University of Maryland

1113 LeFrak Hall

College Park, Maryland 20742

Phone: 301/405-4055

Fax: 301/314-9299

Internet: sg21@umail.umd.edu

GLAS

Bob E. Schutz

Team Leader

University of Texas at Austin

Center for Space Research, C0605

Austin, Texas 78712-1085

Phone: 512/471-4267

Fax: 512/471-3570

Internet: schutz@csr.utexas.edu

HIRDLS

John Barnett

Co-Principal Investigator

Atmospheric, Oceanic, and Planetary Sciences

Oxford University

Clarendon Laboratory

Oxford, OX1 3PU

UNITED KINGDOM

Phone: 44-186-527-2909

Fax: 44-186-527-2923

Internet: barnett@isams.atm.ox.ac.uk

John C. Gille

Co-Principal Investigator

National Center for Atmospheric Research

Atmospheric Chemistry Division

P. O. Box 3000

Boulder, Colorado 80307

Phone: 303/497-1402

Fax: 303/497-1492

Internet: gille@ncar.ucar.edu

Jason-1

Lee-Lueng Fu

Principal Investigator - U.S.

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 300-323

Pasadena, California 91109

Phone: 818/354-8167

Fax: 818/393-6720

Internet: llf@pacific.jpl.nasa.gov

Yves Menard

Principal Investigator - France

Centre National d'Etudes Spatiales

DSO/ED/AL

bpi 2002

18 Ave. Edouard Belin

31401 Toulouse, Cedex

FRANCE

Phone: 33-56-127-4872

Fax: 33-56-128-2595

Internet: Yves.Menard@cnes.fr

LIS

Hugh J. Christian

Principal Investigator

NASA/Marshall Space Flight Center

Code ES41

977 Explorer Blvd.

Huntsville, Alabama 35806

Phone: 205/922-5828

Fax: 205/922-5723

Internet: hugh.christian@msfc.nasa.gov

MISR

David J. Diner

Principal Investigator

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 169-237

Pasadena, California 91109-8099

Phone: 818/354-6319

Fax: 818/393-4619

Internet: djd@jord.jpl.nasa.gov
1999 EOS Reference Handbook Points of Contact • 343

MLS

Joe W. Waters

Principal Investigator

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 183-701

Pasadena, California 91109-8099

Phone: 818/354-3025

Fax: 818/393-5065

Internet: joe@mls.jpl.nasa.gov

MODIS

Vincent V. Salomonson

Team Leader

NASA/Goddard Space Flight Center

Code 900

Greenbelt, Maryland 20771

Phone: 301/614-5634

Fax: 301/614-5620

Internet: vsalomon@pop900.gsfc.nasa.gov

MOPITT

James R. Drummond

Principal Investigator

University of Toronto

Department of Physics

60 St. George Street

Toronto, Ontario M5S 1A7

CANADA

Phone: 416/978-4723

Fax: 416/978-8905

Internet: jim@atmosp.physics.utoronto.ca

OMI

Pieternel Levelt

Principal Investigator

Royal Netherlands Meteorological Institute (KNMI)

Climate Research and Seismology Department

Atmospheric Sciences Division

P.O. Box 210

3730 AE De Bilt

The Netherlands

Phone: 31-30-220-6667 or 220-6416

Fax: 31-30-221-0407

Internet: levelt@knmi.nl

SAGE III

M. Patrick McCormick

Principal Investigator

Hampton University

Center for Atmospheric Sciences

23 Tyler Street

Hampton, Virginia 23668

Phone: 757/728-6867

Fax: 757/727-5090

Internet: mcc@hamptonu.edu

SeaWinds

Michael H. Freilich

Principal Investigator

Oregon State University

College of Oceanic and Atmospheric Sciences

Oceanography Administration Bldg. 104

Corvallis, Oregon 97331-5503

Phone: 503/737-2748

Fax: 503/737-2064

Internet: mhf@oce.orst.edu

SORCE

Gary J. Rottman

Principal Investigator

Laboratory for Atmospheric and Space Physics

University of Colorado

Campus Box 590

Boulder, Colorado 80309-0590

Phone: 303/492-8324

Fax: 303/492-6444

Internet: Gary.Rottman@lasp.colorado.edu

TES

Reinhard Beer

Principal Investigator

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 183-301

Pasadena, California

Phone: 818/354-4748

Fax: 818/393-4445

Internet: Reinhard.Beer@jpl.nasa.gov
344 • Points of Contact 1999 EOS Reference Handbook

G. Robert Brakenridge

Principal Investigator

Department of Geography

Dartmouth College

Hanover, New Hampshire 03755

Phone: 603/646-2870

Fax: 603/646-1601

Internet: G.Robert.Brakenridge@dartmouth.edu

Ken Caldeira

Principal Investigator

Climate System Modeling Group

Lawrence Livermore National Laboratory

7000 East Avenue

Livermore, California 94550

Phone: 925/423-4191

Fax: 925/423-6388

Internet: kenc@llnl.gov

Douglas G. Capone

Principal Investigator

Chesapeake Biological Laboratory

University of Maryland Center for Environmental

Science

Solomons, Maryland 20688-0038

Phone: 410/326-7250

Fax: 410/326-7341

Internet: capone@cbl.umces.edu

Mary-Elena Carr

Principal Investigator

Jet Propulsion Laboratory

4800 Oak Grove Drive

Pasadena, California 91109

Phone: 818/354-5097

Fax: 818/393-6720

Internet: mec@pacific.jpl.nasa.gov

William Chameides

Principal Investigator

School of Earth and Atmospheric Scienes

Georgia Institute of Technology

221 Bobby Dodd Way

Atlanta, Georgia 30332-0340

Phone: 404/894-1749

Fax: 404/894-1106

Internet: william.chameides@eas.gatech.edu

Mark R. Abbott

Principal Investigator

Oregon State University

College of Oceanic and Atmospheric Sciences

Oceanography Administration Bldg. 104

Corvallis, Oregon 97331-5503

Phone: 541/737-4045

Fax: 541/737-2064

Internet: mark@oce.orst.edu

Kevin Arrigo

Principal Investigator

Code 971

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/286-9634

Fax: 301/286-0240

Internet: Kevin.R.Arrigo.1@gsfc.nasa.gov

Marcia Baker

Principal Investigator

University of Washington

Geophysics Program

Box 351650

Seattle, Washington 98195-1650

Phone: 206/685-3799

Fax: 206/543-0489

Internet: marcia@geophys.washington.edu

Eric J. Barron

Principal Investigator

Pennsylvania State University

Earth System Science Center

248 Deike Building

University Park, Pennsylvania 16802

Phone: 814/865-1619

Fax: 814/865-3191

Internet: eric@essc.psu.edu

Ian J. Barton

Principal Investigator

CSIRO Marine Research

GPO Box 1538

Hobart, Tasmania 7001

AUSTRALIA

Phone: 61-02325222

Fax: 61-02325000

Internet: Ian.Barton@marine.csiro.au

Interdisclipinary Investigations
1999 EOS Reference Handbook Points of Contact • 345

Josef Cihlar

Principal Investigator

Canada Centre for Remote Sensing

588 Booth Street

4th Floor

Ottawa, Ontario K1A 0Y7

CANADA

Phone: 613/947-1265

Fax: 613/947-1406

Internet: cihlar@ccrs.emr.ca

Jean O. Dickey

Principal Investigator

Jet Propulsion Laboratory/Caltech

M/S 238-332

4800 Oak Grove Drive

Pasadena, California 91109

Phone: 818/354-3235

Fax: 818/393-6890

Internet: jean.o.dickey@jpl.nasa.gov

Robert E. Dickinson

Principal Investigator

University of Arizona

1118 E 4th St

P.O. Box 210081

Tucson, Arizona 85721-0081

Phone: 520/621-2810

Fax: 520/621-6833

Internet: robted@hail.atmo.arizona.edu

Paul A. Dirmeyer

Principal Investigator

Center for Ocean-Land-Atmosphere Studies

Institute of Global Environment & Society Inc

4041 Powder Mill Road

Suite 302

Calverton, Maryland 20705-3106

Phone: 301/902-1254

Fax: 301/595-9793

Internet: dirmeyer@cola.iges.org

Jeff Dozier

Principal Investigator

School of Environmental Science and Management

University of California

Santa Barbara, California 93106

Phone: 805/893-7363

Fax: 805/893-7612

Internet: dozier@icess.ucsb.edu

Ralph Dubayah

Principal Investigator

Department of Geography

1113 Lefrak Hall

University of Maryland

College Park, MD 20742

Phone: 301/405-4069

Fax: 301/314-9299

Internet: rdubayah@geog.umd.edu

Thomas Dunne

Lead U.S. Co-Investigator

School of Environmental Science & Management

University of California Santa Barbara

4670 Physical Sciences North

Santa Barbara, California 93106 USA

Phone: 805/893-7557

Fax: 805/893-7612

Internet: tdunne@esm.ucsb.edu

Dara Entekhabi

Principal Investigator

Department of Civil Environmental Engineering

Massachusetts Institute of Technology

48-331

Cambridge, Massachusetts 01239

Phone: 617/253-9698

Fax: 617/258-8850

Internet: darac@mit.edu

Jonathan A. Foley

Principal Investigator

Climate, People, and Environment Program (CPEP)

Institute for Environmental Studies

University of Wisconsin

1225 West Dayton Street

Madison, Wisconsin 53706

Phone: 608/265-5144

Fax: 608/263-4190

Internet: jfoley@facstaff.wisc.edu

Paul Falkowski

Principal Investigator

Environmental Biophysics & Molecular Ecology

Program

Institute of Marine & Coastal Sciences

Rutgers University

71 Dudley Road

New Brunswick, New Jersey 08903

Phone: 732/932-6555

Fax: 732/932-8578

Internet: falko@imcs.rutgers.edu
346 • Points of Contact 1999 EOS Reference Handbook

Inez Fung

Principal Investigator

Center for Atmospheric Sciences

301 McCone Hall #4767

University of California, Berkeley

Berkeley, California 94720

Phone: 510/643-9367

Fax: 510/643-9377

Internet: ifung@uclink4.berkeley.edu

Steven J. Ghan

Principal Investigator

Climate Dynamics Group

Mail Stop K9-30

Battelle Pacific Northwest Laboratory

3200 Q Avenue

Richland, Washington 99352

Phone: 509/372-6169

Fax: 509/372-6168

Internet: steve.ghan@pnl.gov

Barry E. Goodison

Principal Investigator

Climate Research Branch

Atmospheric Environment Service

4905 Dufferin Street

Downsview, Ontario M3H 5T4

CANADA

Phone: 416/739-4345

Fax: 416/739-5700

Internet: Barry.Goodison@ec.gc.ca

Sirpa Hakkinen

Principal Investigator

NASA Goddard Space Flight Center

Oceans and Ice Branch

Code 971

Greenbelt, Maryland 20771

Phone: 301/614-5712

Fax: 301/614-5644

Internet: hakkinen@gsfc.nasa.gov

James E. Hansen

Principal Investigator

NASA/Goddard Institute for Space Studies

2880 Broadway

New York, New York 10025

Phone: 212/678-5500

Fax: 212/678-5622

Internet: jhansen@giss.nasa.gov

Dennis L. Hartmann

Principal Investigator

University of Washington

Department of Atmospheric Science

Box 351640

Seattle, Washington 98195-1640

Phone: 206/543-7460

Fax: 206/685-9302

Internet: dennis@atmos.washington.edu

Eileen Hofmann

Principal Investigator

Center for Coastal Physical Oceanography

Crittenton Hall

Old Dominion University

Norfolk, Virginia 23529

Phone: 757/683-5334

Fax: 757/683-5550

Internet: hofmann@ccpo.odu.edu

Brent Holben

Principal Investigator

Code 923

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6658

Fax: 301/614-6695

Internet: brent.holben@gsfc.nasa.gov

Marc L. Imhoff

Principal Investigator

Code 923

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-6628

Fax: 301/614-6695

Internet: marc.imhoff@gsfc.nasa.gov

Thomas J. Jackson

Principal Investigator

Hydrology Laboratory

U.S. Department of Agriculture

Building 007, BARC West, Room 104

Beltsville, Maryland 20705

Phone: 301/504-8511

Fax: 301/504-8931

Internet: tjackson@hydrolab.arsusda.gov
1999 EOS Reference Handbook Points of Contact • 347

Daniel J. Jacob

Principal Investigator

Harvard University

Pierce Hall

29 Oxford Street

Cambridge, Massachussetts 02138

Phone: 617/495-1794

Fax: 617/495-4551

Internet: djj@io.harvard.edu

Prasad Kasibhatla

Principal Investigator

Nicholas School of the Environment

Duke University

P.O. Box 90328

Durham, North Carolina 27708

Phone: 919/613-8075

Fax: 919/684-8741

Internet: psk9@duke.edu

Ralph F. Keeling

Principal Investigator

Scripps Institution of Oceanography

University of California, San Diego

9500 Gilman Drive

La Jolla, California 92093

Phone: 619/534-7582

Fax: 619/534-2997

Internet: rkeeling@ucsd.edu

Yann H. Kerr

Principal Investigator

Centre National d’Etudes Spatiales

CESBIO

18 Avenue Edouard Belin

31401 Toulouse, Cedex 4

FRANCE

Phone: 33-56-155-8522

Fax: 33-56-155-8500

Internet: yann.kerr@cesbio.cnes.fr

Jeffrey T. Kiehl

Principal Investigator

National Center for Atmospheric Research

P.O. Box 3000

Boulder, Colorado 80307

Phone: 303/497-1350

Fax: 303/497-1324

Internet: jtkon@ncar.ucar.edu

Charles E. Kolb

Principal Investigator

Center for Atmospheric and Environmental Chemistry

Aerodyne Research, Inc.

45 Manning Road

Billerica, Massachussetts 01821

Phone: 978/663-9500

Fax: 978/663-4918

Internet: kolb@aerodyne.com

Randal D. Koster

Principal Investigator

Hydrological Sciences Branch

Laboratory for Hydrospheric Processes

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/614-5781

Fax: 301/614-5808

Internet: randal.koster@gsfc.nasa.gov

William K. M. Lau

Principal Investigator

NASA/Goddard Space Flight Center

Code 913

Greenbelt, Maryland 20771

Phone: 301/614-6772

Fax: 301/614-6307

Internet: lau@climate.gsfc.nasa.gov

W. Timothy Liu

Principal Investigator

Jet Propulsion Laboratory

4800 Oak Grove Drive

Mail Stop 300-323

Pasadena, California 91109

Phone: 818/354-2394

Fax: 818/393-6720

Internet: liu@pacific.jpl.nasa.gov

Yongqiang Liu

Principal Investigator

School of Earth and Atmospheric Sciences

Georgia Institute of Technology

Atlanta, Georgia 30332

Phone: 404/385-0584

Fax: 404/894-1106

Internet: liuy@eas.gatech.edu
348 • Points of Contact 1999 EOS Reference Handbook

John Marshall

Principal Investigator

Massachussetts Institute of Technology

77 Massachussetts Avenue

Bldg. 54-1256

Cambridge, Massachussetts 02139

Phone: 617/253-9615

Fax: 617/253-4464

Internet: marshall@gulf.mit.edu

Charles R. McClain

Principal Investigator

Code 970.2

NASA/Goddard Space Flight Center

Greenbelt, Maryland 20771

Phone: 301/286-5377

Fax: 301/286-1775

Internet: mcclain@calval.gsfc.nasa.gov

Dennis McGillicuddy

Principal Investigator

Woods Hole Oceanographic Institution

Woods Hole, Massachussetts 02543

Phone: 508/289-2683

Fax: 508/457-2194

Internet: dmcgillicuddy@whoi.edu

Linda O Mearns

Principal Investigator

Environmental and Societal Impacts Group

National Center for Atmospheric Research

P.O. Box 3000

Boulder, Colorado 80307

Phone: 303/497-8124

Fax: 303/497-8125

Internet: lindam@ucar.edu

Massimo Menenti

Principal Investigator

Winand Staring Center

P.O. Box 125

Wageningen, 6700AC

The Netherlands

Phone: 31 317 474324

Fax: 31 317 424812

Internet: m.menenti@sc.dlo.nl

Norman L. Miller

Principal Investigator

Earth Sciences Division

Berkeley National Laboratory

University of California

One Cyclotron Road, M/S 90-1116

Berkeley, California 94720

Phone: 510/495-2374

Fax: 510/486-7070

Internet: nlmiller@lbl.gov

Berrien Moore III

Principal Investigator

University of New Hampshire

Morse Hall Room 305

Durham, New Hampshire 03824

Phone: 603/862-1766

Fax: 603/862-1915

Internet: bmoore@unh.edu

Peter J. Mouginis-Mark

Principal Investigator

Hawaii Institute of Geophysics & Planetology

University of Hawaii

2525 Correa Road

Honolulu, Hawaii 96822

Phone: 808/956-3147

Fax: 808/956-6322

Internet: pmm@pgd.hawaii.edu

Frank Muller-Kruger

Principal Investigator

Department of Marine Science

University of South Florida

140 7th Avenue South

St. Petersburg, Florida 33701

Phone: 727/553-3335

Fax: 727/553-1103

Internet: carib@carbon.marine.usf.edu

Masato Murakami

Principal Investigator

Typhoon Research Department

Meteorological Research Institute

1-1 Nagamine, Tsukuba-shi

Ibaraki 305

JAPAN

Phone: 81-29-855-2683

Fax: 81-29-853-8668

Internet: mmurakam@mri-jma.go.jp
1999 EOS Reference Handbook Points of Contact • 349

Raymond C. Najjar

Principal Investigator

Department of Meteorology

503 Walker Building

Pennsylvania State University

University Park, Pennsylvania 16802

Phone: 814/863-1586

Fax: 814/865-3663

Internet: najjar@essc.psu.edu

Kenneth E. Pickering

Principal Investigator

Department of Meteorology

University of Maryland

College Park, Maryland 20742

Phone: 301/405-7639

Fax: 301/314-9482

Internet: pickerin@metosrv2.umd.edu

Roger A. Pielke, Sr.

Principal Investigator

Department of Atmospheric Science

Colorado State University

Fort Collins, Colorado 80523

Phone: 970/491-8293

Fax: 970/491-8293

Internet: pielke@hercules.atmos.colostate.edu

John Adrian Pyle

Principal Investigator

Cambridge University

Department of Chemistry

Lensfield Road, Cambridge CB2 1EW

UNITED KINGDOM

Phone: 44-12-236-1188

Fax: 44-12-234-6739

Internet: pyle@atm.ch.cam.ac.uk

Dale A. Quattrochi

Principal Investigator

Global Hydrology and Climate Center

NASA/Marshall Space Flight Center

977 Explorer Boulevard

Huntsville, Alabama 35806

Phone: 256/922-5887

Fax: 256/922-5723

Internet: dale.quattrochi@msfc.nasa.gov

John O. Roads

Principal Investigator

Climate Research Division

Scripps Institution of Oceanography

University of California-San Diego

9500 Gilman Drive

La Jolla, California 92093

Phone: 619/534-2099

Fax: 619/534-8561

Internet: jroads@ucsd.edu

Richard B. Rood

Principal Investigator

NASA/Goddard Space Flight Center

Code 910.3

Greenbelt, Maryland 20771

Phone: 301/614-6155

Fax: 301/614-6297

Internet: rood@dao.gsfc.nasa.gov

Cynthia Rosenzweig

Principal Investigator

NASA/Goddard Institute for Space Studies

2880 Broadway

New York, New York 10025

Phone: 212/678-5562

Fax: 212/678-5648

Internet: crosenzweig@giss.nasa.gov

D. Andrew Rothrock

Principal Investigator

University of Washington

Applied Physics Laboratory

Mail Stop HN-10

Seattle, Washington 98195

Phone: 206/685-2262

Fax: 206/543-3521

Internet: rothrock@apl.washington.edu

David S. Schimel

Principal Investigator

National Center for Atmospheric Research

PO Box 3000

Boulder, Colorado 80307-3000

Phone: 303/497-1610

Fax: 303/497-1695

Internet: schimel@ncar.ucar.edu
350 • Points of Contact 1999 EOS Reference Handbook

Mark R. Schoeberl

Principal Investigator

NASA/Goddard Space Flight Center

Code 910

Greenbelt, Maryland 20771

Phone: 301/614-6002

Fax: 301/614-5903

Internet: Mark.Schoeberl@gsfc.nasa.gov

Christopher A. Shuman

Principal Investigator

NASA/Goddard Space Flight Center

Code 971

Greenbelt, MD 20771

Phone: 301/614-5881

Fax: 301/614-5644

Internet: shuman@hardy.gsfc.nasa.gov

David Siegel

Principal Investigator

Institute for Computational Earth System Science

University of California at Santa Barbara

Santa Barbara, California 93106-3060

Phone: 805/893-4547

Fax: 805/893-2578

Internet: davey@icess.uscb.edu

W. James Shuttleworth

Principal Investigator

Department of Hydrology & Water Resources

Bldg. 11

University of Arizona

Tucson, Arizona 85721

Phone: 520/621-8787

Fax: 520/621-1422

Internet: shuttle@hwr.arizona.edu

Ronald B. Smith

Principal Investigator

Department of Geology and Geophysics

Yale University

P.O. Box 208109

New Haven, Connecticut 06520

Phone: 203/432-3129

Fax: 203/432-3134

Internet: ronald.smith@yale.edu

Joao V. Soares

Principal Investigator

Instituto Nacional de Pesquisas Espaciais

Divisao de Sensoriamento Remoto

Avenida dos Astronautas, 1758 - C.P. 515

12227-010 Sao José dos Campos, SP

BRAZIL

Phone: 55-12-345-6439

Fax: 55-12-345-6488

Internet: vianei@ltid.inpe.br

Soroosh Sorooshian

Lead U.S. Investigator

University of Arizona

Department of Hydrology and Water Resources

Harshbarger Building, Room 122

Tucson, Arizona 85721

Phone: 520/621-1661

Fax: 520/626-2488

Internet: soroosh@hwr.arizona.edu

Meric A. Srokosz

Principal Investigator

Southampton Oceanography Centre (SOC)

Empress Dock, Southampton SO14 3ZH

UNITED KINGDOM

Phone: 44-170-359-6414

Fax: 44-170-359-6400

Internet: M.Srokosz@soc.soton.ac.uk

Graeme Stephens

Principal Investigator

Atmospheric Science Department

Colorado State University

Ft. Collins, Colorado 85721

Phone: 970/491-8541

Fax: 970/491-8449

Internet: stephens@atmos.colostate.edu

Byron D. Tapley

Principal Investigator

The University of Texas - Austin

Center for Space Research R1000

3925 West Breaker Lane, Suite 200

Austin, Texas 78712

Phone: 512/471-5573

Fax: 512/232-2443

Internet: tapley@csr.utexas.edu
1999 EOS Reference Handbook Points of Contact • 351

Ina Tegen

Principal Investigator

Department of Applied Physics

Columbia University

2880 Broadway

New York, New York 10027

Phone: 212/678-5573

Fax: 212/678-5552

Internet: itegen@giss.nasa.gov

Owen B. Toon

Principal Investigator

Laboratory for Atmospheric & Space Physics

University of Colorado

Campus Box 392

Boulder, Colorado 80309

Phone: 303/492-1534

Fax: 303/492-6946

Internet: toon@lasp.colorado.edu

John J. Walsh

Principal Investigator

Dept. of Marine Science

University of South Florida

140 7th Avenue South

St. Petersburg, Florida 33701

Phone: 727/553-1164

Fax: 727/553-1189

Internet: jwalsh@seas.marine.usf.edu

Bruce A. Wielicki

Principal Investigator

NASA/Langley Research Center

Mail Stop 420

Hampton, Virginia 23681-2199

Phone: 757/864-5683

Fax: 757/864-7996

Internet: b.a.wielicki@larc.nasa.gov

Eric F. Wood

Principal Investigator

Department of Civil and Environmental Engineering

Princeton University

Princeton, New Jersey 08544

Phone: 609/258-4675

Fax: 609/258-2799

Internet: efwood@pucc.princeton.edu
352

• Points of Contact 1999 EOS Reference Handbook
1999 EOS Reference Handbook Acronyms and Abbreviations • 353

Acronyms and Abbreviations

2D Two Dimensional

3D Three Dimensional

4DDA 4-Dimensional Data Assimilation

A

A/SA arid/semi-arid

AABW Antarctic Bottom Water

AAOE Airborne Antarctic Ozone Experiment

AASE II Airborne Arctic Stratospheric

Expedition II

AATSR Advanced Along Track Scanning

Radiometer

ABS oxygen A-Band Spectrometer

ACRIM Active Cavity Radiometer Irradiance

Monitor

AC Atmospheric Corrector

ACSYS Arctic Climate System Study

ADEOS Advanced Earth Observation Satellite

AEAP Atmospheric Effects of Aviation

Program

AERONET Aerosol Robotic Network

AESOPS Antarctic Environment Southern

Ocean Process Study

AESP Aerospace Education Services Program

AGCM Atmospheric General Circulation Models

AGU American Geophysical Union

AHM (model)

AIAA American Institute of Aeronautics and

Astronautics

AIRSAR Airborne Synthetic Aperture Radar

ALI Advanced Land Imager

ALOS Advanced Land Observation Satellite

ALT Altimeter

AMI Active Microwave Instrument

AMIP Atmospheric Model Intercomparison

Project

AMLS Array MLS

AMS American Meteorological Society

AMSR Advanced Microwave Scanning

Radiometer

AMSR-E Advanced Microwave Scanning

Radiometer (EOS Version)

AMSU Advanced Microwave Sounding Unit

AO Announcement of Opportunity

APAR Absorbed Photosynthetically-Active

Radiation

APFZ Antarctic Polar Frontal Zone

API Application Programming Interface

APT Automatic Picture Transmission

ARM Atmospheric Radiation Measurement

ASAR Advanced Synthetic Aperture Radar

ASF Alaska SAR Facility

ASHOE Airborne Southern Hemisphere Ozone

Experiment

ASTER Advanced Spaceborne Thermal

Emission and Reflection Radiometer

ASTEX Atlantic Stratocumulus Transition Experiment

ATBD Algorithm Theoretical Basis Document

ATLAS Atmospheric Laboratory for Applications

and Science

ATMOS Atmospheric Trace Molecule Spectroscopy

ATSR Along Track Scanning Radiometer

AVHRR Advanced Very High-Resolution

Radiometer

AVIRIS Airborne Visible-Infrared Imaging

Spectrometer

AWS Automatic Weather Station

B

BAHC Biospheric Aspects of the Hydrological

Cycle

BASIC Bay Area Shared Information Consortium

BATS Biosphere-Atmosphere Transfer Model

BIOME Biogeochemical Information Ordering

Management Environment

BOREAS Boreal Ecosystems Atmosphere Study

BRDF Bidirectional Reflectance Distribution

Function

BSRN Baseline Surface Radiation Network

BUV Backscatter Ultraviolet
354 • Acronyms and Abbreviations 1999 EOS Reference Handbook

C

CALM Circumpolar Active Layer Monitoring

CAPE Convection and Precipitation Electrification

field project

CARIACO Carbon Retention In A Colored Ocean

CART Cloud and Radiation Testbed

CASES Cooperative Atmosphere-Surface

Exchange Study

CCD Charge-Coupled Device

CCN Cloud Condensation Nuclei

CDIAC Carbon Dioxide Information and Analysis

Center

CDOC colored dissolved organic carbon

CDOM Colored Dissolved Organic Matter

CEES Committee on Earth and Environmental

Sciences

CEM Cumulus Ensemble Model

CENR Committee on the Environment and Natural

Resources

CEOS Committee on Earth Observation Satellites

CERES Clouds and the Earth’s Radiant Energy

System

CESAR Cloud Electrification Studies using Aircraft

and Radar

CESBIO Centre d’Études Spatiales de la Biosphère

CFC Chlorofluorocarbon

CH2Cl2 Dichloromethane

CH3Cl Methyl chloride

CHCl3 Chloroform

CHAMP Challenging Mini-satellite Payload

CHEM-1 Chemistry Mission-1

CLAES Cryogenic Limb Array Etalon

CLASS Canadian Land Surface Scheme

CLIVAR CLImate VARiability and prediction

ClOx oxides of chlorine family

CMDL Climate Monitoring and Diagnostics

Laboratory

CMIS Conical Microwave Imager Sounder

CNES Centre National d’Etudes Spatiales (France)

CPEP Climate, People and Environment Program

CPR Cloud Profiling Radar

CPTEC Center for Weather and and Climate

Prediction (Brazil)

CSMS Communications and System Management

Segment

COARE Coupled Ocean-Atmosphere Response

CODMAC Committee on Data Management, Archiving,

and Computing

COS Carbonyl Sulfide

COSEPUP Committee on Science, Engineering, and

Public Policy

COV Coefficient of Variation

CPR Cloud Profiling Radar

CR Correlation Radiometry

CRIS Cross-track Infrared Sounder

CRYSYS Use of the Cryospheric System to Monitor

Global Change in Canada (EOS IDS)

CSA Canadian Space Agency

CSIRO Commonwealth Scientific and Industrial

Research Organization

CTM Chemistry and Transport Model

CZCS Coastal Zone Color Scanner

D

DAAC Distributed Active Archive Center

DAO Data Assimilation Office

DAS Data Assimilation System

DDL Direct Downlink

DECAFE Dynamique et Chimie de l’Atmosphere en

Foret Equatoriale

DEM Digital Elevation Model

DFA Dual-Frequency radar Altimeter

DGVM Dynamic Global Vegetation Models

DISORT Discrete Ordinate Radiative Transfer Model

DMS Dimethyl Sulfide

DMSP Defense Meteorological Satellite Program

DMWG Data Management Working Group

DoC Department of Commerce

DoD Department of Defense

DoE Department of Energy

DOM Dissolved Organic Matter

DORIS Doppler Orbitography and

Radiopositioning Integrated by Satellite

DSB Direct Sounding Broadcast

DT Delta T (Temperature)

DU Dobson Unit

DWL Dopplar Wind Lidar

E

EASOE European Arctic Stratospheric Ozone

Experiment

EBC Eastern Boundary Currents

EBNet EOS Backbone Network

ECHIVAL European International Project on Climate

and Hydrological Interactions between

Vegetation, Atmosphere, and Land Surfaces

ECLIPS Experimental Cloud Lidar Pilot Study

ECMWF European Centre for Medium-Range

Weather Forecasts
1999 EOS Reference Handbook Acronyms and Abbreviations • 355

ECS EOSDIS Core System

EDC EROS Data Center

EDOS EOS Data and Operations System

EFEDA ECHIVAL Field Experiment in Desertification-Threatened Areas

EGIG Expédition Glaciologique Internationale

au Groenland

ELV Expendable Launch Vehicle

ENSO El Niño-Southern Oscillation

ENVISAT Environmental Satellite, ESA

EO-1 Earth Orbiter-1

EOS Earth Observing System

EOS PM EOS afternoon-crossing satellite

EOSDIS EOS Data and Information System

EOSP Earth Observing Scanning Polarimeter

EOSPSO EOS Project Science Office

EP Earth Probe

EPA Environmental Protection Agency

EPGS EOS Polar Ground Station

EPOP European Polar-Orbiting Platform

ER-2 NASA Research Aircraft

ERB Earth Radiation Budget

ERBE Earth Radiation Budget Experiment

ERBS Earth Radiation Budget Satellite

ERCN Educator Resource Center Network

ERG EOSDIS Review Group

EROS Earth Resources Observation System

ERS European Remote-Sensing Satellite

ERS-1 European Remote-Sensing Satellite-1

ERTS Earth Resources Technology Satellite

ESA European Space Agency

ESSAAC Earth System Science and Applications

Advisory Committee

ESCC Electrically Self-Calibrating Cavity

ESDIS Earth Science Data and Information System

ESE Earth Science Enterprise

ESIP Earth Science Information Partner

ESMR Electrically Scanning Microwave

Radiometer

ESR Electrical Subsitution Radiometer

ESSC Earth System Sciences Committee

ESSP Earth System Sciences Pathfinder

ET Evapotranspiration

ETM Enhanced Thematic Mapper

ETM+ Enhanced Thematic Mapper Plus

EURECA European Retrievable Carrier

F

FAA Federal Aviation Administration

FAO Food and Agriculture Organization

FAPAR Fraction Absorbed Photosynthetically

Active Radiation

FIFE First ISLSCP Field Experiment

FIRE First ISCCP Regional Experiment

FLUXNET Flux Network

FOO Flight Of Opportunity

FOS Flight Operations Segment

FPAR Fraction of Photosynthetically-Active

Radiation

FSSP Forward Scattering Spectrometer Probe

FTS Fourier Transform Spectrometer

FY Fiscal Year

G

GAC Global Area Coverage

GAIM Global Analysis, Interpretation, and

Modeling

GAME GEWEX Asian Monsoon Experiment

GAME-T GEWEX Asian Monsoon ExperimentTropics

GAP Gap Analysis Project

GCIP GEWEX Continental-Scale International

Project

GCM General Circulation Model (also Global

Climate Model)

GCOS Global Climate Observing System

GCTE Global Change in Terrestrial Ecosystems

GDP Gross Domestic Product

GEBA Global Energy Balance Archive

GENESIS Global Environmental and Ecological

Simulation of Interactive Systems

GEOCOMP GEOcoding and COMPositing system

GEOS Goddard Earth Observing System

GERB Geostationary Earth Radiation Budget

GEWEX Global Energy and Water cycle Experiment

GFDL Geophysical Fluid Dynamics Laboratory

GFO Geosat Follow-On

GGD Global Geocryology Database

GHCN Global Historical Climatology Network

GIS Geographic Information System

GISP Greenland Ice Sheet Program

GISS Goddard Institute for Space Studies

GLAS Geoscience Laser Altimeter System

GLCTS Global Landcover Test Site Initiative

GLI Global Imager
356 • Acronyms and Abbreviations 1999 EOS Reference Handbook

GLIMS Global Land Ice Monitoring from Space

GLIS Global Land Information System

GLOBE Global Learning and Observations to Benefit

the Earth

GLOBEC Global Ocean Ecosystem Dynamics

GMS Geostationary Meteorological Satellite

GNP Gross National Product

GOALS Global Ocean-Atmosphere-Land System

GOES Geostationary Operational Environmental

Satellite

GOMOS Global Ozone Monitoring By Occultation of

Stars

GPCP Global Precipitation Climatology Project

GPP Gross Primary Productivity

GPS Global Positioning System

GPSOS Global Positioning Sensor Occultation

System

GRACE Gravity Recovery And Climate Experiment

GRDC Global Runoff Data Center

GSFC Goddard Space Flight Center

GSRP Graduate Student Researchers Program

Gt Gigaton

GTOS Global Terrestrial Observing System

GVaP GEWEX Water Vapor Project

H

HAIRS High Accuracy Inter-satellite Ranging

System

HALOE Halogen Occultation Experiment

HAPEX Hydrological-Atmospheric Pilot Experiment

HCFC Hydrochlorofluorocarbon

HH Horizontal, Horizontal Polarization

HEIFE Heihe basin Field Experiment

HIRDLS High-Resolution Dynamics Limb Sounder

HIRS High-Resolution Infrared Radiation Sounder

HNLC High Nutrient, Low Chlorophyll

HOX odd hydrogen family

HRDI High-Resolution Doppler Imager

HRPT high-resolution picture transmission

HSB Humidity Sounder - Brazil

HSCT High-Speed Civil Transport

HUBEX Huaihe Basin Experiment

I

IABP International Arctic Buoy Program

IAVCEI International Association of Volcanology and

Chemistry of the Earth’s Interior

IBS Integrated Biosphere Simulator

ICESat Ice, Clouds, and Land Elevation Satellite

ICRCCM Intercomparison of Radiative Codes for

Climate Models

ICSU International Council of Scientific Unions

IDS Interdisciplinary Science Investigation (EOS)

IELV Intermediate Expendable Launch Vehicle

IEOS International Earth Observing System

IFC Intensive Field Campaign

IFO Intensive Field Observation

IFOV Instantaneous Field of View

IGAC International Global Atmospheric Chemistry

IGBP International Geosphere-Biosphere

Programme

IGPPDI Global Primary Production Data Initiative

IHP International Hydrological Program

IIP Instrument Incubator Program

ILAS Improved Limb Atmospheric Spectrometer

IMARPE Insituto del Mar de Peru

IMAS Integrated Multispectral Atmospheric

Sounder

IMS Information Management System

INDOEX Indian Ocean Experiment

IOC Intergovernmental Oceanographic Commission

IOP Intensive Observing Period

IPCC Intergovernmental Panel on Climate Change

IPO Integrated Program Office

IR infrared

IRR Imaging Infrared Radiometer

ISAMS Improved Stratospheric and Mesospheric

Sounder

ISCCP International Satellite Cloud Climatology

Project

ISLSCP International Satellite Land Surface Climatology Project

IT Instrument Team

ITCZ Inter-Tropical Convergence Zone

IWG Investigators Working Group

IWP ice water path

J

JERS Japanese Earth Remote-Sensing Satellite

JERS-OPS Japanese Earth Remote-sensing SatelliteOPS

JEXAM Japanese Experiment of Asian Monsoon

JGOFS Joint Global Ocean Flux Study

JMR Jason Microwave Imager

JORNEX Jornada Experiment

JPL Jet Propulsion Laboratory
1999 EOS Reference Handbook Acronyms and Abbreviations • 357

JPLAIRSAR JPL Airborne Synthetic Aperture Radar

JPO Joint Planning Office

JPOP Japanese Polar-Orbiting Platform

K

KINEROS Kinematic wave overland flow, channel

routing and Erosion model

KORMEX Korean Monsoon Experiment

L

LAC Local Area Coverage

LAGEOS Laser Geodynamics Satellite

LAI Leaf-Area Index

Landsat Land Remote-Sensing Satellite

LaTIS Langley TRMM Information System

LBA Large Scale Biosphere-Atmosphere

Experiment in Amazonia

LERTS Laboratoire d’Etudes et de Recherches en

Teledetection Spatiale

LHH L-band HH

LIS Lightning Imaging Sensor

LITE Lidar In-space Technology Experiment

LLNL Lawrence Livermore National Laboratory

LOICZ Land Ocean Interactions in the Coastal Zone

LRC Langley Research Center

LRPT Low-Resolution Picture Transmissions

LS Lower Stratosphere

LSM Land-Surface Model

LSP Land-Surface Parameterization

LTER Long-Term Ecological Research

LW longwave

LWP Liquid Water Path

M

MAAT Mean Annual Air Temperature

MAC Multi-sensor Air Campaign

MAPS Measurement of Air Pollution from Satellites

MBLA Multi-Beam Laser Altimeter

MCS Mesoscale Convective System

MERIS Medium-Resolution Imaging Spectrometer

METEOR-3 Russian Operational Weather Satellite

METOP Meteorological Operational Satellite

METRI Meteorological Research Institute (Korea)

MHS Microwave Humidity Sounder

MIMR Multifrequency Imaging Microwave

Radiometer

MISR Multi-angle Imaging Spectroradiometer

MIT Massachusetts Institute of Technology

MITI Ministry of International Trade and Industry

(Japan)

MLS Microwave Limb Sounder

MM mesoscale model

MMIC Microwave Monolithic Integrated Circuit

MMS Modular Modeling System

MODIS Moderate-Resolution Imaging

Spectroradiometer

MODLAND MODIS Land

MOPITT Measurements of Pollution in the Troposphere

MOU Memorandum of Understanding

MOZART Model for Ozone And Related chemical

Tracers

MSFC Marshall Space Flight Center

MSG Meteosat Second Generation

MSS Multispectral Scanner

MSU Microwave Sounding Unit

MT Megaton

MVI MODIS Vegetation Index

N

NAD Nitric Acid Dihydrate

NADW North Atlantic Deep Water

NAO North Atlantic Oscillation

NARSTO North American Research Strategy for

Tropospheric Ozone

NASA National Aeronautics and Space Administration

NASDA National Space Development Agency (Japan)

NAT Nitric Acid Trihydrate

NBIOME Northern Biosphere Observation and

Modeling Experiment

NCAR National Center for Atmospheric Research

NCDC National Climatic Data Center

NCEP National Centers for Environmental

Prediction

NDVI Normalized Difference Vegetation Index

NESDIS National Environmental Satellite, Data, and

Information Service

NEXRAD Next Generation Weather Radar

NH Northern Hemisphere

NIMA National Imagery and Mapping Agency

NIR Near Infrared

NISN NASA Integrated Services Network
358 • Acronyms and Abbreviations 1999 EOS Reference Handbook

NIST National Institute of Standards and Technology

NMC National Meteorological Center

NMHC Non-Methane Hydrocarbons

NMP New Millennium Program

NOAA National Oceanic and Atmospheric Administration

NOPEX Northern Hemisphere Climate-Processes

Land-Surface Experiment

NOX odd nitrogen family

NPOESS National Polar-orbiting Operational

Environmental Satellite System

NPP Net Primary Production

NRA NASA Research Announcement

NRC National Research Council

NREN NASA Research and Education Network

NSCAT NASA Scatterometer

NSF National Science Foundation

NSIDC National Snow and Ice Data Center

NSTC National Science and Technology Council

NWP Numerical Weather Prediction

O

OCS Carbonyl Sulfide

OCMIP Ocean Carbon-cycle Model Intercomparison

Project

OCTS Ocean Color and Temperature Scanner

ODT Ocean Color and

OES Office of Earth Science

OH Hydroxyl radical

OLR Outgoing Longwave Radiation

OMI Ozone Monitoring Instrument

OMPS Ozone Mapper and Profiler Suite

ONR Office of Naval Research

ORNL Oak Ridge National Laboratory

OSU Oregon State University

OTD Optical Transient Detector

OTTER Oregon Transect Terrestrial Ecosystem

Research

P

PABSI Profiling A-Band Spectrometer/Visible Imager

PACS Pan American Climate Studies

PAR Photosynthetically-Active Radiation

PARC Public Access Resource Center

PARCA Program for Arctic Regional Climate

Assessment

PDF portable document format

PEM Production Efficiency Model

PI Principal Investigator

PICASSO Pathfinder Instruments for Cloud and

Aerosol Spaceborne Observations

PIK Potsdam Institute for Climate Impact

Research

PILPS Project for Intercomparison of Land-Surface

Parameterization (LSP) Schemes

PNNL Pacific Northwest National Laboratory

PNZ Phytoplankton-nutrient-zooplankton

POLDER Polarization and Directionality of the Earth’s

Reflectance

POLES Polar Exchange at the Sea Surface (IDS)

ppm parts per million

PR Precipitation Radar

PSC Polar Stratospheric Cloud

PSU Pennsylvania State University

PW precipitable water

PWV precipitable water vapor

Q

QBO Quasi-Biennial Oscillation

R

RACMO Regional Atmospheric Climate Model

Radarsat Radar Satellite, Canada

RAMS Regional Atmospheric Modeling System

RC radiative-convective

RCSM Regional Climate System Model

REP Relativistic Electron Precipitation

RGPS Radarsat Geophysical Processor System

S

S.D. Standard Deviation

SAA Satellite Active Archive

SADCO South African Data Center for Oceanography

SAFARI South African Fire-Atmospheric Research

Initiative

SAGE Stratospheric Aerosol and Gas Experiment

SALSA Semi-Arid Land-Surface-Atmosphere

SAM Stratospheric Aerosol Measurement

SAR Synthetic Aperture Radar

SAS-C Scientific Applications Satellite-C
1999 EOS Reference Handbook Acronyms and Abbreviations • 359

SAVI Soil-Adjusted Vegetation Index

SBIR Small Business and Innovative Research

SBUV Solar Backscatter Ultraviolet

SCA Snow-Covered Area

SCANSAR Scanning Synthetic Aperture Radar

SCAR-B Smoke, Cloud, and Radiation-Brazil

SCARAB Scanner for Radiation Budget

SCF Scientific Computing Facility

SCICEX Submarine Arctic Science Cruise (Program)

SCISSAP Southern Center for the Integrated Study of

Secondary Air Pollutants

SCIGN Southern California Integrated GPS Network

SCOPE Scientific Committee on Problems of the

Environment

SDPS Science Data Processing Segment

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SEBAL Surface Energy Balance

SEDAC Socioeconomic Data and Applications Center

SESAME Second European Stratospheric Arctic and

Mid-Latitude Experiment

SGP Southern Great Plains

SHEBA Surface Heat Budget of the Arctic Ocean

SI Systeme Internationale

SiB Simple Biosphere Model

SIM Spectral Irradiance Monitor

SIMBIOS Sensor Intercomparison and Merger for

Biological and Interdiscplinary Oceanic

Studies

SIMIP Sea Ice Model Intercomparison Project

SIPS Science Investigator-led Processing System

SIR-C Shuttle Imaging Radar-C

SITUPS Spatial Integrity Thresholding of Urban

Polygons

SLA Shuttle Laser Altimeter

SLR Satellite Laser Ranging

SMM Solar Maximum Mission

SMMR Scanning Multispectral Microwave Radiometer

SMVGEAR Sparse-Matrix Vectorized Gear Code

SOCC Satellite Operations Control Center

SOHO Solar Heliospheric Observatory

SOLAS Surface Ocean Lower Atmosphere Study

SOLSTICE Solar Stellar Irradiance Comparison

Experiment

SOS Southern Oxidants Study

SPCZ South Pacific Convergence Zone

SPE Solar Particle Event

SPOT Systeme pour l’Observation de la Terre

SRB Surface Radiation Budget

SRBEX Susquehanna River Basin Experiment

SRTM Shuttle Radar Topography Mission

SSALT Solid State radar Altimeter

SSBUV Shuttle Solar Backscatter Ultraviolet

SSM/I Special Sensor Microwave/Imager

SST Sea-Surface Temperature

SSU Stratospheric Sounding Unit

STP Standard Temperature and Pressure

STS Space Transport System

SVAT Soil-Vegetation-Atmosphere Transfer Model

SVI Spectral Vegetation Indices

SW shortwave

SWAP SouthWest Asia Project

SWE Snow Water Equivalent

SWG Science Working Group

SWIR Shortwave Infrared

T

T-S temperature-salinity

TAO TOGA Atmosphere-Ocean

TARFOX Tropospheric Aerosol Radiative Forcing

Observational Experiment

TEM Terrestrial Ecosystem Model

TES Tropospheric Emission Spectrometer

THESEO Third European Stratospheric Experiment on

Ozone

THM Terrestrial Hydrology Model

TILDAS tunable infrared laser differential absorption

spectrometer

TIM Total Irradiance Monitor

TIR Thermal Infrared

TIROS Television and Infrared Observation Satellite

TM Thematic Mapper

TMI TRMM Microwave Imager

TMR TOPEX Microwave Radiometer

TOA Top Of the Atmosphere

TOGA Tropical Ocean Global Atmosphere

TOMS Total Ozone Mapping Spectrometer

TOP Terrestrial Observation Panel

TOPEX/ Ocean Topography Experiment

Poseidon

TOPORAD (model)

TOPSAR Topographic Synthetic Aperture Radar

TOVS TIROS Operational Vertical Sounder

TRACE-A Transport and Chemistry near the Equator

over the Atlantic

TRAGNET United States Trace Gas Network

TRCN Teacher Resource Center Network

TRMM Tropical Rainfall Measuring Mission

TSI Total Solar Irradiance
360 • Acronyms and Abbreviations 1999 EOS Reference Handbook

TSS TRMM Support System

TT&C Tracking, Telemetry & Commanding

TZD total zenith delay

U

UAM Urban Airshed Model

UARP Upper Atmosphere Research Program

UARS Upper Atmosphere Research Satellite

UKMO United Kingdom Meteorological Office

UMAC Upper Midwest Aerospace Consortium

UMCP University of Maryland, College Park

UNEP United Nations Environment Program

UNESCO United Nations Educational, Scientific, and

Cultural Organization

USAF United States Air Force

USDA United States Department of Agriculture

USGCRP U.S. Global Change Research Program

USGS United States Geological Survey

USRA University Space Research Association

UT Upper Troposphere

UV Ultraviolet

UV-B Ultraviolet-B

V

VCL Vegetation Canopy Lidar

VEMAP Vegetation/Ecosystem Modeling and

Analysis Project

VHRR Very High Resolution Radiometer

VI Vegetation Index

VIC Variable Infiltration Capacity

VIIRS Visible and Infrared Imaging Radiometer

Suite

VIRGO Variability of solar Irradiance and Gravity

Oscillations

VIRS Visible Infrared Scanner

VIS Visible

VNIR Visible and Near Infrared

VOC Volatile Organic Carbon

W

WCRP World Climate Research Program

WDC-A World Data Center-A

WFC visible Wide-Field Camera

WFPS Water-Filled Pore Space

WMO World Meteorological Organization

WOCE World Ocean Circulation Experiment

WSMC Western Space and Missle Center

WSR Weather Surveillance Radar

WVR Water Vapor Radiometer

X

X-SAR X-Band Synthetic Aperture Radar

XBT Expendable BathyThermograph

XPS XUV Photometer System

Z

ZWD Zenith Wet Delay
1999 EOS Reference Handbook Acronyms and Abbreviations • 361

Appendix

24 EOS Measurements in support of the U.S. Global Change Research Program (USGCRP). The chart above shows the key physical

variables needed to advance understanding of the entire Earth system and the interactions among the components. The EOS instruments

listed in bold font are primary sensors, bold italics represent secondary instruments, and roman fonts are contributing instruments for critical

measurements.

MODIS, GLAS, AMSR-E, MISR, AIRS, ASTER,

EOSP, SAGE III

CERES, ACRIM III, TIM, MODIS, AMSR-E, GLAS, MISR,

AIRS, ASTER, SAGE III

AMSR-E

TES, MOPITT, SAGE III, MLS, HIRDLS, LIS

MLS, HIRDLS, SAGE III, OMI, TES

SAGE III, HIRDLS, MODIS, MISR, EOSP, OMI, GLAS

AIRS/AMSU-A, MLS, HIRDLS, TES, MODIS

AIRS/AMSU-A/HSB, MLS, SAGE III, HIRDLS,

Poseidon 2/JMR, MODIS, TES

LIS

ACRIM III, TIM

SOLSTICE

ETM+, MODIS, ASTER , MISR

MODIS, MISR, ETM+, ASTER

ASTER, MODIS, AIRS, ETM+

MODIS, ASTER, ETM+

MODIS, ASTER, ETM+, MISR

AMSR-E

MODIS, AIRS, AMSR-E

MODIS

SeaWinds, AMSR-E, Poseidon 2/JMR

Poseidon 2/JMR

GLAS, ASTER, ETM+

AMSR-E, Poseidon 2/JMR, MODIS, ETM+, ASTER

MODIS, AMSR-E, ASTER, ETM+

Cloud Properties

(amount, optical properties, height)

Radiative Energy Fluxes

(top of atmosphere, surface)

Precipitation

Tropospheric Chemistry

(ozone, precursor gases)

Stratospheric Chemistry

(ozone, ClO, BrO, OH, trace gases)

Aerosol Properties

(stratospheric, tropospheric)

Atmospheric Temperature

Atmospheric Humidity

Lightning

(events, area, flash structure)

Total Solar Irradiance

Ultraviolet Spectral Irradiance

Land Cover & Land Use Change

Vegetation Dynamics

Surface Temperature

Fire Occurrence

(extent, thermal anomalies)

Volcanic Effects

(frequency of occurrence, thermal anomalies,

impact)

Surface Wetness

Surface Temperature

Phytoplankton & Dissolved Organic

Matter

Surface Wind Fields

Ocean Surface Topography

(height, waves, sea level)

Land Ice

(ice sheet topography, ice sheet volume change,

glacier change)

Sea Ice

(extent, concentration, motion, temperature)

Snow Cover

(extent, water equivalent)

ATMOSPHERE

SOLAR

RADIATION

LAND

OCEAN

CRYOSPHERE

Appendix
NP-1999-08-134-GSFC