NASA Technical Memorandum 104566, Vol. 17

SeaWiFS Technical Report Series

Stanford B. Hooker and

Elaine R. Firestone, Editors

Volume 17, Ocean Color in the 21st Century:

A Strategy for a 20-Year Time Series

Mark R. Abbott, Otis B. Brown, Robert H. Evans, Howard R. Gordon,

Kendall L. Carder, Frank E. M ̈uller-Karger, and Wayne E. Esaias

June 1994
NASA Technical Memorandum 104566, Vol. 17

SeaWiFS Technical Report Series

Stanford B. Hooker, Editor

NASA Goddard Space Flight Center

Greenbelt, Maryland

Elaine R. Firestone, Technical Editor

General Sciences Corporation

Laurel, Maryland

Volume 17, Ocean Color in the 21st Century:

A Strategy for a 20-Year Time Series

Mark R. Abbott

Oregon State University

Corvallis, Oregon

Otis B. Brown, Robert H. Evans, and Howard R. Gordon

University of Miami

Miami, Florida

Kendall L. Carder

University of South Florida

St. Petersburg, Florida

Frank E. M ̈uller-Karger

NASA Headquarters

Washington, DC

Wayne E. Esaias

Goddard Space Flight Center

Greenbelt, Maryland

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

1994
Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

Abstract

Beginning with the upcoming launch of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), there should

be almost continuous measurements of ocean color for nearly 20 years if all of the presently planned national

and international missions are implemented. This data set will present a unique opportunity to understand the

coupling of physical and biological processes in the world ocean. The presence of multiple ocean color sensors will

allow the eventual development of an ocean color observing system that is both cost effective and scientifically

based. This report discusses the issues involved and makes recommendations intended to ensure the maximum

scientific return from this unique set of planned ocean color missions. An Executive Summary is included with

this document which briefly discusses the primary issues and suggested actions to be considered.

1. INTRODUCTION

The development of a 20-year time series of ocean color

measurements from satellites starting with the Sea-viewing

Wide Field-of-view Sensor (SeaWiFS), presents many scientific opportunities to study long-term variability of biological processes in the upper ocean. These studies will

range from the response of the upper ocean ecosystem to

global climate change to the management of coastal zone

resources.

There are several challenges that must be overcome

before these studies can be done. These include: crosscalibration and validation of the different sensors which

will be launched by the National Aeronautics and Space

Administration (NASA), the National Space Development

Agency (NASDA) of Japan, and the European Space Agency (ESA); initiation of a program to ensure comprehensive,

coordinated observation and modeling plans; and consistency of data processing and data access. The presence of

multiple ocean color sensors will allow the eventual development of an ocean color observing system that is both

cost-effective and scientifically based.

This report discusses these subjects and makes recommendations to ensure the maximum scientific return from

this unique set of planned ocean color missions. The Executive Summary (Section 2), encapsulates the primary

points made in this document. The remaining content

is an in-depth discussion of these subjects and concerns.

Some sections of the Executive Summary recur in the main

discussion for emphasis of particular points and narrative

clarity.

2. EXECUTIVE SUMMARY

Over the past decade, the following scientific objectives

have been developed for using ocean color measurements

for ocean research.

1. Improve the quantitative understanding of the ocean’s

role in the global carbon cycle. Specifically, ocean color

imagery, in situ bio-optical measurements, numerical

models, and measurements from other space sensors

(for example, infrared thermometers and scatterometers) will be used to:

a) improve estimates of the production and fate of particulate and dissolved organic carbon (DOC) in the

global ocean;

b) estimate the effects of phytoplankton blooms on the

exchange rates of carbon dioxide (CO2) between the

atmosphere and the upper ocean;

c) describe the evolution of the coupled biological and

physical processes in the upper mixed layer; and

d) provide the first quantitative estimates of interannual to decadal changes in global ocean primary

production.

2. Improve the quantitative understanding of how light

absorption by the upper ocean affects the ocean heat

budget;

3. Improve the quantitative understanding of how phytoplankton blooms affect the production and air-to-sea

exchange of dimethyl sulfide (DMS) and other trace

gases that may affect cloud formation and other atmospheric processes; and

4. Understand the relationship between phytoplankton

and other components of the marine ecosystem as related to fisheries, environmental stress, and resource

management.

The long-term scientific goal is to understand not only

how ocean biological processes affect the global carbon cycle, but how they will change in response to changes in

physical forcing on local, regional, and global scales. An

understanding of the coupled dynamics of ocean biology,

ocean physics, and atmospheric forcing on the oceanic upper mixed layer is the ultimate objective.

In addition to these scientific objectives, ocean color

measurements will provide valuable information for managing ocean resources. For example, Coastal Zone Color

Scanner (CZCS) data were used successfully in several fishery studies for both research and operational applications.

Other applications, such as monitoring coastal water movements and detection of eddies and fronts for shipping, will

also be conducted using ocean color observations.

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Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

To meet these goals, the following observational requirements must be met:

a. Two-day global coverage at 1 km resolution with

a sensor that meets the technical specifications at

least at the level of those of SeaWiFS (continuous

record) and direct read-out of Local Area Coverage

(LAC) data using off-the-shelf equipment;

b. In-water measurements to validate water-leaving radiances and to evaluate regional chlorophyll a algorithms and other bio-optical variables;

c. Develop coupled biological and physical numerical

models which incorporate ocean productivity and

its effects on air and sea CO2 and trace gas exchanges, fates of organic carbon, and ocean heat

budgets using the following inputs: satellite ocean

color imagery, in situ data, and derived products

from other satellite sensors such as wind stress, sea

surface temperature (SST), and solar insolation;

d. Acquire measurements centered near 412 nm for estimates of detrital carbon and improved estimates

of chlorophyll a in oceanic and coastal waters, and

at the sunlight induced fluorescence band (around

685 nm) for improved estimates of coastal chlorophyll a concentrations and for determining the physiological state of phytoplankton (to improve estimates of primary production); and

e. Space based observations with full spectral coverage

from 400 nm through the near infrared (IR), 800 nm,

to resolve accessory pigments and for refined estimates of chlorophyll a, detrital carbon, and other

in-water constituents.

As ocean color observations will be made from a wide

range of sensors with different capabilities and from satellites with different orbits, considerable effort will be required to merge these data sets into a consistent, quantitative view of upper ocean biology. Ocean color measurements will require a high level of stability and accuracy.

The desired signal is very small (usually less than 10%

of the total, satellite-sensed signal because of atmospheric

effects) as are interannual changes in biomass and productivity.

To meet the science objectives, the following capabilities must be developed in addition to making ocean color

measurements:

1. The development of fully coupled ocean and atmosphere models that include both biological and

physical processes will require a full suite of physical measurements concurrent with measurements of

ocean biology.

2. An active program of cross-calibration between the

sensors is essential to develop a statistically homogeneous, long-term (greater than 20 years) data

record which can be used to study low-frequency

events such as the El Ni ̃no Southern Oscillation

(ENSO). This program must include some overlap

period between the sensors and an active in situ

calibration and validation program.

3. Access to the data and the analogous algorithms

must be ensured.

The net result of this research will be an improved understanding of the processes that control carbon cycling

and storage in the ocean. The availability of a multidecade, consistent time series on ocean pigment and primary productivity will allow the scientific community to

study the role of low frequency variability in ocean biology.

For example, ENSO events occur roughly every 3–4 years

so that a 20-year time series should contain about five such

events. The impact of ENSO events should be characterizable with a high degree of statistical robustness. More

importantly, this long time series, if properly calibrated,

will allow scientists to determine the ocean’s response to

long-term climate change.

By using numerical models that assimilate observations

from satellites and in situ sensors, predictions could be

made about the interactions between atmospheric forcing

and primary productivity. However, data assimilation requires that the variance (error) structure is known of both

the data sets being assimilated and the model relationships. For example, the temporal and spatial variance

spectrum of light utilization parameters would be a key

component of a productivity model that relies on assimilation techniques. At present, the understanding of the

time and space variability of most biological properties is

quite crude. However, such measurements are not beyond

the scope of many planned and operational global oceanography programs. If the ultimate goal is the prediction

of ocean carbon cycling in response to changes in atmospheric forcing, then collection of such data must begin, as

well as the development of assimilation models.

Although the focus of this discussion is on global-scale

processes, small-scale studies will also benefit from access

to ocean color observations. For example, studies of coastal

dynamics, river plumes, and fisheries have made extensive

use of 1 km resolution CZCS data (Abbott and Chelton

1991). International efforts such as the Land Ocean Interaction in the Coastal Zone (LOICZ) program and the

Global Ocean Ecosystems dynamics (GLOBEC) program

will require high spatial resolution ocean color observations. In particular, high spectral resolution observations

will be necessary in order to distinguish the various dissolved and particulate components of the upper ocean in

both turbid and productive coastal waters.

2.1 Recommendations

2.1.1 Management Issues

The goal of a 20-year time series of global ocean color

observations requires an unprecedented level of coordination between US federal agencies and their international

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Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

partners. Sensor design and calibration should be welldocumented such that data processing can take sensor performance into account. Data systems must be designed so

that the processing history can be preserved and data and

algorithms can be easily shared. Such coordination, however, must take place in an era of constrained financial resources. New methods for management must be explored.

1. An interagency working group on satellite ocean

color research and applications should be formed

by the Committee on Environment and Natural Resources (CENR) with representation from all interested US agencies. A charter for this working group

should include both US and foreign missions. It

should serve as the focal point for foreign collaboration. This group must also consider the necessary modeling activities and physical observations

needed to analyze and interpret ocean color data.

2. The National Aeronautics and Space Administration (NASA) should convene a meeting of the appropriate project and program personnel (including

contract management) along with representatives

of the ocean color research community as soon as

possible to develop an overall ocean color program.

This program should consist of plans for research,

software development, data processing and delivery,

funding, and management.

3. SeaWiFS and the Earth Observing System (EOS)-

Color efforts should be considered by the EOS Data

Information System (EOSDIS) as the prelaunch system capability tests which will facilitate the transition from 4 km SeaWiFS data to 1 km Moderate

Resolution Imaging Spectrometer (MODIS) data.

4. The MODIS Oceans Team should be designated

the EOS-Color Science Team, which would be expanded upon the results of an EOS-Color NASA

Research Announcement (NRA). NASA should negotiate clear agreements with the MODIS Oceans

Team regarding deliverables and funding. These

agreements must be coordinated across the full set

of ocean color activities so an efficient, realistic plan

is developed.

5. NASA should plan an EOS-Color NRA for the 1996–

97 time frame.

6. NASA should encourage investigator relationships

between US and foreign scientists. This may require

agreements on data delivery and policies, in which

case NASA, the European Space Agency (ESA),

and the National Space Development Agency

(NASDA) of Japan should establish appropriate understandings as soon as possible.

2.1.2 Calibration and Validation Issues

Each ocean color sensor must be calibrated and an initial in situ validation cruise will be required shortly after

each launch. The vicarious method developed by Gordon

and co-workers (Evans and Gordon 1994) provides a powerful technique to calibrate the entire ocean color system.

An extensive calibration program is planned for the EOS

sensors; these efforts must be coordinated with the methods described in this document. The issue of international

coordination also arises in this context; extensive in situ

observations are costly, and cooperation between the various international partners could reduce the costs for each

country.

Given that there will be periods when more than one

sensor is in orbit at any one time, maximum priority should

be given towards conducting calibration and validation

cruises to compare the sensors during these overlap periods. Collecting extensive calibration and validation measurements should help develop a consistent time series of

ocean color measurements from this diverse set of sensors.

This would also ensure radiometric continuity between the

missions which, to the extent that the system algorithms

(atmospheric and bio-optical) provide accurate products,

would facilitate continuing studies of interannual variability. Clearly, this intercalibration effort will require cooperation on an international level. Recommendations to

achieve these goals follow.

a. Calibration and validation cruises must take place

as soon after launch as possible in regions with appropriate bio-optical properties.

b. Feasibility studies should be conducted on the use of

high-altitude, oligotrophic lakes as calibration and

validation sites.

c. Calibration and validation cruises must be located

in both northern and southern waters to investigate

thermal effects on sensor performance.

d. Calibration and validation cruises should be planned

for other bio-optical water types, but these need not

be completed during the initial period of sensor operation.

e. NASA should encourage investigators to collaborate with their international colleagues to develop a

global network of bio-optical moorings.

2.1.3 Data System Issues

The primary goal of a 20-year time series requires that

the data processing and distribution system be designed to

safeguard the raw data and the calibration and validation

information, to enable reprocessing, and to ensure efficient

transfer of data and algorithms to US and international

researchers. The data system cannot view itself in isolation

from contemporaneous data centers or systems that may

precede or follow it. High priority must be given towards

ensuring compatibility of these basic services. While a data

system may focus on a specific mission, e.g., SeaWiFS,

its role in the larger constellation of ocean color missions

must be retained. It must be carefully integrated into a

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Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

data systems strategy that ensures ease of use of other

Earth data sets. Particular attention should be paid to

retention of the sensor design, calibration, and validation

information. This will allow future researchers to reprocess

the data in a consistent manner.

NASA must work to eliminate all restrictions on

access to ocean color observations, consistent with

the EOS data policy. This policy must apply to

both US and foreign researchers.

Consistency should be maintained between the various sensor data sets as they move from one data

processing and delivery system to another.

SeaWiFS and the Ocean Color Temperature Sensor

(OCTS) from Japan, should serve as a testbed for

such exchanges between international partners. Although the primary focus may be at the investigator

level, NASA may need to support efforts on data

policies, data exchange, and satellite downlinks.

2.1.4 Convergence

As more nations begin ambitious programs for space

based research on the Earth system, there appears to be

considerable overlap between observing capabilities. The

distinctions between the different sensors are sometimes

subtle. With increasing budget pressures, there is substantial pressure to merge these various observing capabilities.

While the scientific rationale for long-term, continuous observations of ocean processes is well in hand, the appropriate sampling strategies are not in place, in part because of

the lack of understanding of the critical processes and their

associated temporal and spatial scales. The next decade

should focus on the necessary studies to develop such an

operational observing system that can adequately resolve

these processes in order to develop sound predictions of

the coupled ocean and atmosphere system and how it will

respond to climate change. In essence, convergence should

be viewed as an opportunity to move from purely sciencedriven observations towards observations for monitoring

and predicting, which must remain firmly based on scientific understanding of ocean processes. Although national

interests are often involved in the launching of satellite

remote sensors, the opportunity presented by the multiple

ocean color missions must be used to design an effective international program. The following are recommendations

for achieving this effectiveness.

a. NASA should coordinate research activities with

the other sponsoring agencies to develop the observing and sampling requirements for an ocean color

system which will make the essential measurements

for ocean monitoring and prediction.

b. An interagency effort needs to be implemented to

define new products for the coastal zone and to collect, process, and distribute the LAC data.

c. NASA must support efforts to link ocean models

with both physical and biological data and ensure

that lessons learned from both modeling and data

analysis are used in the design of ocean color observing systems.

3. OCEAN COLOR RESEARCH

3.1 Research Priorities

An ad hoc committee was formed in 1991 to report on

ocean color research in the pre-EOS and EOS eras. The

committee recommended the following scientific objectives:

1. Improve the quantitative understanding of the ocean’s

role in the global carbon cycle. Specifically, ocean color

imagery, in situ bio-optical measurements, numerical

models, and measurements from other space sensors

(for example, infrared thermometers and scatterometers) will be used to:

a) improve estimates of the production and fate of particulate and dissolved organic carbon (DOC) in the

global ocean;

b) estimate the effects of phytoplankton blooms on the

exchange rates of carbon dioxide (CO2) between the

atmosphere and the upper ocean;

c) describe the evolution of the coupled biological and

physical processes in the upper mixed layer; and

d) provide the first quantitative estimates of interannual to decadal changes in global ocean primary

production.

2. Improve the quantitative understanding of how light

absorption by the upper ocean affects the ocean heat

budget;

3. Improve the quantitative understanding of how phytoplankton blooms affect the production and air-to-sea

exchange of dimethyl sulfide (DMS) and other trace

gases that may affect cloud formation and other atmospheric processes; and

4. Understand the relationship between phytoplankton

and other components of the marine ecosystem as related to fisheries, environmental stress, and resource

management.

The long-term scientific goal is to understand not only

how ocean biological processes affect the global carbon cycle, but how they will change in response to changes in

physical forcing on local, regional, and global scales. An

understanding of the coupled dynamics of ocean biology,

ocean physics, and atmospheric forcing on the oceanic upper mixed layer is the ultimate objective.

In addition to these scientific objectives, ocean color

measurements will provide valuable information for managing ocean resources. For example, CZCS data were used

successfully in several fisheries studies for both operational

and research, e.g., Fiedler et al. 1984. Other applications,

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Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

such as the monitoring of coastal water movements and

detection of eddies and fronts for shipping, will also be

conducted using ocean color observations.

3.2 Observation Plan

Beginning in 1994, there should be nearly continuous

ocean color measurements for the next 20 years. SeaWiFS

will provide the first data set, beginning in 1994 with a

planned 5-year mission. It will be followed by OCTS on

the first Advanced Earth Observation Satellite (ADEOS1) launched by NASDA in 1996, and by MODIS on the

first EOS morning (AM-1) platform scheduled for 1998.

A follow-on SeaWiFS-class sensor will also be launched in

1998 (EOS-Color) as will the Medium Resolution Imaging

Spectromenter (MERIS) on the Environmental Satellite

(ENVISAT) to be launched by the European Space Agency

(ESA). A second MODIS will be launched on the second

EOS (PM-1) platform in 2000. The Global Imager (GLI)

will also be launched by NASDA in 2000. After this point,

there will be two copies of MODIS in orbit at any one time

for the 15-year EOS mission.

3.2.1 Implementation Priorities

The ad hoc committee proposed several implementation priorities to accomplish the science objectives, using

the satellite missions as the basic observational framework.

These priorities are:

a) two-day global coverage at 1 km resolution with the

sensor meeting the technical specifications at least

at the level of SeaWiFS (continuous record) and direct read-out of LAC data using off-the-shelf equipment;

b) in-water measurements to validate water-leaving radiances and to evaluate regional chlorophyll a algorithms and other bio-optical variables;

c) develop coupled biological and physical numerical

models that incorporate ocean productivity and its

effects on air and sea CO2 and trace gas exchanges,

fates of organic carbon, and ocean heat budgets using as inputs: satellite ocean color imagery, in situ

data, and derived products from other satellite sensors such as wind stress, SST, and solar insolation;

d) acquire measurements centered near 412 nm for estimates of detrital carbon and improved estimates

of chlorophyll a in oceanic and coastal waters, and

at the sunlight-induced fluorescence band (around

685 nm) for improved estimates of coastal chlorophyll a concentrations and for determining the physiological state of phytoplankton (to improve estimates of primary production); and

e) space based observations with full-spectral coverage from 400 nm through the near-IR (800 nm) to

resolve accessory pigments and for refined estimates

of chlorophyll a, detrital carbon, and other in-water

constituents.

These priorities serve well as an initial start for a research plan. However, some important issues for future

missions should be addressed. First, multiple global observations at 1 km spatial resolution on a daily basis will

greatly improve scientific understanding of the role of mesoscale processes in the upper ocean. Given that eddy sizes

in many parts of the ocean are of the order of 10 km, the

initial Global Area Coverage (GAC) SeaWiFS spatial resolution of 4 km will not be adequate to resolve such features. Coupled with cloud patterns, more frequent sampling will also be necessary to resolve the temporal variability of these features. Recent field and model studies have

shown that variability on these space and time scales plays

a critical role in the coupling of the atmosphere and the

upper ocean and in the control of biological productivity.

Second, improved sensor performance beyond SeaWiFS is

essential to detect chlorophyll a fluorescence and to characterize completely the optical properties of the upper ocean,

but no planned sensor will have the necessary high spectral resolution across the visible wavelengths. The original

MODIS-T (which was tilted to minimize sun glint) sensor

met these specifications.

3.2.2 Requirements for Observations

Given nearly-continuous ocean color measurements and

the long-range goal of understanding the coupled physical

and biological system, there are several requirements for

observations. First, the development of fully coupled ocean

and atmosphere models that include both biological and

physical processes will require a full suite of physical measurements concurrent with measurements of ocean biology.

Second, an active program of cross-calibration between the

sensors is essential to develop a statistically homogeneous,

long-term (greater than 20 years) data record which can

be used to study low-frequency events such as the ENSO.

This program must include some overlap period between

the sensors and an active in situ calibration and validation program. Third, the data should be processed and

archived by several groups so that access to the data and

the corresponding algorithms is ensured. These requirements will be challenging, given that the time series will

be comprised of measurements from several sensors from

various countries.

Although these challenges are not insurmountable,

planning must begin immediately to achieve the fundamental goal of a consistent, long-term record. Numerous examples exist, such as the Advanced Very High Resolution

Radiometer (AVHRR) and the Active Cavity Radiometer Irradiance Monitor (ACRIM), where such a consistent

record could not be assembled even when similar sensors

from an individual nation were used to collect the record.

3.2.3 Field Measurements

In the context of a satellite ocean color program, field

measurements should be focused on calibration and validation of the sensors, as well as algorithm development

5
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

and validation of products. The SeaWiFS Project has defined a suite of measurements and protocols that should

serve as a baseline for future field programs (Mueller and

Austin 1992). Sampling strategies should consist of both

intensive, focused cruises, and extensive, less intense measurements from moorings and drifters.

Algorithm and numerical model development will take

place as part of investigator-driven field programs, rather

than as part of specific flight projects. The exception

would be new algorithms designed to take advantage of

new sensor capabilities, such as the 412 nm band for dissolved organic matter (DOM). In terms of numerical model

development, specific activities need to be directed towards

characterizing the spatial and temporal variability of the

critical variables of the models as well as the relationships

between processes. This characterization is essential if construction of models that can assimilate satellite data is to

be realized. Although this activity is beyond the scope

of an instrument flight project, it must be conducted in

a systematic manner, and not be restricted to a few locales. Critical information must be delivered back to the

flight project to ensure instrument performance and data

product definition.

The field component of satellite missions must work

in close cooperation with existing and planned field programs, especially those with a global focus such as the Joint

Global Ocean Flux Study (JGOFS). NASA must work cooperatively with agencies that control ship funding and

schedules to ensure that these vital field measurements are

supported. In the past, coordination between agencies responsible for satellite observations and agencies responsible

for ship observations has been difficult to achieve.

3.3 Convergence of Ocean Color Missions

As more nations begin ambitious programs for space

based research on the Earth system, there appears to be

considerable overlap between observing capabilities. The

distinctions between MODIS, MERIS, and GLI are sometimes subtle. With increasing budget pressures, there is

substantial pressure to merge these various observing capabilities. While the scientific rationale for long-term, continuous observations of ocean processes is well in hand,

the appropriate sampling strategies are not in place, in

part because of the lack of understanding of the critical

processes and their associated temporal and spatial scales.

The next decade should focus on the necessary studies to

develop such an operational observing system which can

adequately resolve these processes in order to develop good

predictions of the ocean and atmosphere system and how

it will respond to climate change. In essence, convergence

should be viewed as an opportunity to move from purely

science-driven observations towards observations for monitoring and predicting, which must remain firmly based on

the scientific understanding of ocean processes. Although

national interests are often involved in the launching of

satellite remote sensors, the opportunity presented by the

multiple ocean color missions must be used to design an

effective international program.

Along with the joint scientific and calibration studies

described earlier, examination must begin of the optimal

sampling strategies for the various ocean color missions.

Although crossing times and orbital altitudes have been

established for all of the planned missions, slight changes

in these parameters can greatly affect the type of sampling

patterns that will be obtained by the full suite of ocean

color missions. These issues include:

Does diel variability in phytoplankton fluorescence need to be resolved, and what is the optimal set of measurements that will resolve these

time scales?

How do morning and afternoon overpasses interact with the variations in the cloud fields?

What are the impacts of not flying a near-noon

orbit on data quality?

How does clear-weather sampling change with

location and season?

In essence, a complete analysis of all error sources in

the observing system (including both sensor and sampling

errors) is needed in the context of the underlying biological

variability. This analysis must consider the impact of these

errors on scientific return. Close coordination between the

various agencies responsible for ocean color observations

will be required to develop an effective strategy that is

based on scientific requirements.

In addition to sampling, studies should be conducted

on the instrument characteristics required to make the

necessary observations. For example, which wavelengths

need to be measured? What signal-to-noise ratio (SNR) is

required? Although the fundamental phytoplankton pigment observing requirements are understood, other variables such as pigment groups and chlorophyll a fluorescence

are only in the experimental stage. Thus, this opportunity

should be used to develop the observation requirements as

well.

3.4 Advances in Scientific Understanding

With the CZCS, it was only possible to estimate total pigment concentrations as there was insufficient spectral resolution to separate chlorophyll a from its associated

degradation products. Although this approach worked reasonably well, several studies have shown that the bio-optical algorithms fail in the presence of DOM, such as humic

acids, which occur in coastal waters, in river plumes, and

in the open ocean. SeaWiFS and follow-on sensors will

have channels near 412 nm to correct pigment estimates

and to estimate the concentration of colored dissolved organic matter (CDOM). Although there remain challenges

for atmospheric correction at these short wavelengths, the

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Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

availability of these measurements may extend the range

of water types, which can be observed quantitatively from

space.

Additional wavelengths and increased sensitivity will

also permit chlorophyll a to be measured separately from

other pigments. Certainly MODIS will be able to make

this measurement and perhaps SeaWiFS. Other accessory

pigments, such as phycoerythrin, will require at least the

increased spectral resolution of MODIS and probably additional bands between 580 nm and 610 nm. Extensive airborne active and passive data have provided strong evidence that the phycoerythrin influence is contained within

the ocean color spectrum (Hoge and Swift 1990), but appropriate wavelength bands must be provided to extract

the actual pigment concentration.

3.4.1 Identifying Pigment Groups

One of the challenges remaining in bio-optical research

is the use of full spectral measurements to separate all of

the materials suspended and dissolved in the upper ocean

and to correct for bottom reflectance in coastal waters,

e.g., Lee et al. (1992) and Carder et al. (1993a). For example, can increased spectral resolution measurements be

used to identify pigment groups within the phytoplankton,

thus obtaining information on species composition? Can

specific degradation products be identified? What minimal

wavelength set and what concentration levels are required

to derive this information? There is evidence from laboratory studies and limited in situ research that this approach

can be used to characterize the bio-optical properties of the

ocean. By using inversion techniques, it is possible to derive many of the bio-optical properties based on measurements of the complete spectrum of water-leaving radiance

(Carder et al. 1993a and 1993b). The challenge for the

next 10 years is to collect the necessary field data that will

improve bio-optical models and strengthen the scientific

underpinnings of this approach.

Such information on pigment groups is particularly important in studies of ocean carbon cycling. The patterns

of cycling and vertical fluxes depend on the species structure of the phytoplankton community. Long-term changes

in species composition, in response to changes in atmospheric forcing, is an important feedback in global climate

change. Subtle shifts from one phytoplankton community

to another can have dramatic impacts, yet little is known

about large spatial scale changes in community structure.

For example, the reduction of the ozone layer in the Southern Hemisphere results in increased ultraviolet (UV) radiation reaching the surface of the ocean. Preliminary studies

indicate that the response to this increased UV radiation

is species-dependent; changes in species composition will

likely ripple throughout the entire ecosystem (Smith and

Baker 1989).

Estimates of CDOM are also important in understanding carbon cycling. The amount of carbon in all DOM is

thought to be as much as the entire terrestrial biomass.

Processes that affect the partitioning of carbon between

DOM and particulate forms will also impact carbon cycling. Partitioning, however, has been accomplished near

the shore using hyperspectral data from aircraft (Carder

et al. 1993a). Limitations due to the spatial and spectral

resolution of planned ocean color sensors (approximately

1 km with one band every 10–20 nm) will reduce their utility in coastal regions.

Rivers are major sources of fresh water, sediments, nutrients and DOM to the coastal zone, in addition to pollutants that may be transported in soluble and particulate

forms. Since CDOM from rivers is rather conservative with

respect to salinity, it can be viewed from aircraft or space

and used to trace terrigenous effluents and to quantify

coastal salinity (Carder et al. 1993b). As riverine nutrients are incorporated into biomass by phytoplankton, the

balance between absorption by CDOM and phytoplankton

shifts, and a partition between mixing effects (CDOM) and

growth and loss effects on phytoplankton biomass (chlorophyll a) may be achieved. Furthermore, knowledge of the

river flux, plume area, and salinity provides valuable information necessary for estimating plume thickness from

space; these data are important to calculating the light

field in and beneath the plume (M ̈uller-Karger et al. 1989).

Near the major rivers of the world, this approach can

be attempted using ocean color sensors with 1 km resolution. For smaller rivers and estuaries, higher resolution is

required to resolve smaller patch sizes and to correct for

interference from bottom reflection which can perturb lowresolution coastal imagery. Hyperspectral imagery with

spatial resolutions of about 100 m appears appropriate to

help in assessing the flux of materials across the land-sea

boundary as well as their influence on primary production,

sediment dynamics, and pollution.

3.4.2 Interpreting Ocean Color

Any rise in sea level or coastal subsidence (for example,

the Mississippi delta), may greatly affect nutrient fluxes,

land usage, and nursery grounds for important fisheries.

To interpret ocean color in the coastal zone where perhaps the strongest influence of humankind on the ocean

is likely to occur, a significant improvement in the performance of the LANDSAT class of sensors is required, with

a movement away from hyperspatial sampling and toward

hyperspectral sampling. Improved SNR can be achieved

by using larger pixels, e.g., 60–90 m and increased dwell

or integration time in order to cope with a need for 10–

15 nm sampling with contiguous bands, e.g., Carder et al.

(1993a).

Although improved estimates of phytoplankton biomass

and perhaps the separation of biomass into contributions

by major phytoplankton groups will be of great value, scientists must look beyond these static variables to measurements of dynamics, specifically primary productivity

7
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

and cycling of DOC. Although several approaches to estimating primary productivity using remotely sensed data

have been described over the last 10 years, at present, scientific understanding and data sets are still inadequate.

Most models rely on the basic biomass estimates collected

from ocean color sensors to infer production rates. Various empirical methods are used to derive light adaptation

and other physiological parameters to improve these rate

estimates. Existing models explain less than 50% of the

variance, and the model predictions are only within about

an order of magnitude of the actual values (Balch et al.

1992, Platt and Sathyendranath 1993, and Balch 1993).

However, there has been much recent progress, and it is

expected that improved models will appear in the next

year.

3.4.3 Discrepancies in Productivity

The challenge for remote sensing and biological oceanography is to understand the reasons for these discrepancies between actual and predicted productivity and to

determine the appropriate time and space scales that can

be modeled. No doubt some of the discrepancies result

from the differing sampling characteristics of the satellitebased approach and the in situ measurements; that is, the

satellite averages over depth and over area, whereas ships

sample discrete points. The use of aircraft sensors to extend the ship measurements over wide areas of the satellite

image should improve the estimates. However, this cannot

explain all of the variability. When physiological information is added into the productivity models, the quality

of the predictions increases substantially. Clearly, models based only on biomass are missing critical information.

This is not a surprising result—the same results have been

noted with terrestrial ecosystems. Although biomass is related to productivity, it is not the only determinant.

Much of the variability in the standing stock productivity relationship is a result of physiological processes, either

due to adaptation or changes in species composition (Platt

and Sathyendranath 1993). At present, species changes

and the use of other variables to parameterize adaptation

are generally ignored. For example, temperature may be

used to infer nutrient availability (through mixing) as well

as respiration. Presumably, similar relationships could be

used involving SST, wind stress, and latent and sensible

heat fluxes to derive vertical mixing rates which could then

be used to infer light and nutrient supply rates. Although

such an approach explicitly includes processes that are only

parameterized in simpler models, they are burdened with

many other parameters that must be defined, such as adaptation rates.

3.4.4 Promising Lines of Research

In terms of ocean color studies, there are at least two

promising lines of research. First, existing research indicates that information on the photoadaptive state will significantly improve productivity estimates. Although the

relationship of sun-stimulated fluorescence to photoadaptive parameters is not completely understood (especially

for surface, light-inhibited populations), fluorescence bands

will be included on MODIS, GLI, and MERIS. This information will provide direct estimates of the physiological

state of the phytoplankton and, coupled with biomass estimates using measurements from other wavelengths, will

improve productivity models (Chamberlin et al. 1989 and

Kiefer and Reynolds 1992). The availability of morning

and afternoon MODIS sensors early in the next century

will allow the study of some aspects of diel variability, at

least in regions of the world ocean that are not obscured by

glint during one of the passes. Measurement of diel variations in sun-stimulated fluorescence might further improve

models of phytoplankton growth rates. However, considerable field work remains before sun-stimulated fluorescence

can become a standard tool for estimating productivity.

The second line of research is to expand the productivity models to incorporate more biological and physical

processes explicitly. Clearly such an approach must reflect

the increased understanding of the processes that regulate

growth rates. A balance must be maintained between increasing the realism of the productivity models and adding

unnecessary detail. As noted earlier, realistic models increase the number of free parameters that must be estimated.

The net result of this research will be an improved understanding of the processes that control carbon cycling

and storage in the ocean. The availability of a multidecade, consistent time series on ocean pigment and primary productivity will allow the scientific community to

study the role of low frequency variability in ocean biology.

For example, ENSO events occur roughly every 3–4 years

so that a 20-year time series should contain about five such

events. The impact of ENSO events should be characterizable with a high degree of statistical robustness. More

importantly, this long time series, if properly calibrated,

will allow scientists to determine the ocean’s response to

long-term climate change.

By using numerical models that assimilate observations

from satellites and in situ sensors, predictions could be

made about the interactions between atmospheric forcing

and primary productivity. However, data assimilation requires that the variance (error) structure is known of both

the data sets being assimilated and the model relationships. For example, the temporal and spatial variance

spectrum of light utilization parameters would be a key

component of a productivity model that relies on assimilation techniques. At present, the understanding of the

time and space variability of most biological properties is

quite crude. However, such measurements are not beyond

the scope of many planned and operational global oceanography programs. If the ultimate goal is the prediction

of ocean carbon cycling in response to changes in atmospheric forcing, then collection of such data must begin, as

well as the development of assimilation models.

8
Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

Although the focus of this discussion is on global-scale

processes, small-scale studies will also benefit from access

to ocean color observations. For example, studies of coastal

dynamics, river plumes, and fisheries have made extensive

use of 1 km resolution CZCS data (Abbott and Chelton

1991). International efforts such as the Land Ocean Interaction in the Coastal Zone (LOICZ) program and the

Global Ocean Ecosystems dynamics (GLOBEC) program

will require high spatial resolution ocean color observations. In particular, high spectral resolution observations

will be necessary in order to distinguish the various dissolved and particulate components of the upper ocean in

both turbid and productive coastal waters.

4. Concerns

There are numerous concerns associated with ocean

color research, running the gamut from management issues, to those regarding the sensors themselves. In this

section, some of these issues are discussed.

4.1 Management Oversight

The goal of a 20-year time series of global ocean color

observations requires an unprecedented level of coordination between US federal agencies and their international

partners. Sensor design and calibration should be welldocumented such that data processing can take sensor performance into account. Data systems must be designed so

that the processing history can be preserved and data and

algorithms can be easily shared. Such coordination, however, must take place in an era of constrained financial resources. New methods for management must be explored.

The programmatic direction for current and planned

work in ocean color remote sensing during the next decade

is not very well focused. Several federal agencies, e.g., the

US Navy, the National Oceanic and Atmospheric Administration (NOAA), the National Science Foundation (NSF),

and NASA have interests in ocean color research and applications in the US. Similarly, there is strong international

interest in Japan and Europe. NASA and NSF have taken

the lead in national and international coordination through

sponsorship of meetings, but there is currently no specific

US federal focal point for such activities nor any ad hoc or

standing group which coordinates US federal policy. Historically, NASA has taken the lead in this area, however

there is no longer a civil service associated with this portfolio.

A loose triumvirate of program managers is acting as

an advisory group for the oceans with the biogeochemistry

program manager taking the lead on ocean color matters.

A diffuse federal focus coupled with a diffuse programmatic

base in NASA has forced the development of a variety of ad

hoc efforts to deal with issues such as SeaWiFS calibration

and validation, ship time, etc., and has left the community

with an unclear idea of which agency is responsible for

which activities. The challenge is even greater in regards

to foreign missions. In a cost-constrained environment, all

of the available resources must be leveraged where possible. For example, shared cruises could help reduce ship

time costs. Although SeaWiFS has extensive international

involvement, there must be similar efforts focusing on the

whole spectrum of ocean color missions.

4.2 Pre-EOS Missions

With the launch of SeaWiFS in 1994, the oceans community will again have access to high quality ocean color

data after an eight-year gap. SeaWiFS has an established

science team who will ensure that the data are processed

and calibrated to the highest standards. It should be recalled that SeaWiFS has had a science oversight committee

throughout its definition, design, and construction phase.

4.2.1 EOS-Color Background

The EOS-Color mission arose from the EOS program

as a substitute for MODIS-T, which was deselected from

the EOS payload. With the launch of the nadir-viewing

MODIS (formerly MODIS-N) on the first EOS morning

(AM-1) platform, it was realized that the coverage of the

ocean would be greatly reduced, given the contamination

by sunglint. EOS-Color is designed to provide measurements to complement the single MODIS sensor until the

first EOS afternoon (PM-1) platform is launched in 2000.

Two MODIS sensors will provide complete global coverage

in the same amount of time as a tilting sensor. EOS-Color

was conceived as a sensor with identical specifications as

SeaWiFS, using the data buy model.

There are a number of advantages to the data buy

model. SeaWiFS is the first ocean satellite mission which

may take less than four years from inception to launch.

Historically such missions have taken 5–10 years to complete. Ideally, a similar program should be established for

EOS-Color. However, only recently has there been an organization established within the EOS Project to ensure

that the EOS-Color mission is designed and implemented.

With the establishment of a group designated with the

responsibility for EOS-Color, the risks of it becoming an

orphan in an era of constrained resources have diminished.

However, note that EOS-Color is often forgotten in various

reports, such as those from the EOSDIS Core System.

It is not known which of several mechanisms may be

chosen to implement EOS-Color. Time is growing short

for formalization of the EOS-Color mission so that a platform and sensor will be available in 1997–98 as a SeaWiFS

follow-on, even if a mechanism similar to SeaWiFS is utilized. If the EOS-Color sensor is not similar in design to

SeaWiFS, then it will be more difficult to cross-reference

sensor calibrations, and particularly data algorithms, in

order to achieve the goal of a consistent time series. These

issues should be resolved as soon as possible.

9
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

4.2.2 EOS-Color Science Issues

The global biogeochemistry community has made it

clear that the most important attribute of satellite ocean

color missions during the 1990s should be continuity so

that a decadal time series can be constructed. Events such

as the Mt. Pinatubo eruption which resulted in global cooling, are also thought to have impacted the carbon cycle in

both oceanic and terrestrial ecosystems to an extent that

the rate of atmospheric CO2 increase slowed significantly

for the last three years. The absence of an ocean color

sensor during this period has hampered critical studies of

the Earth’s carbon cycle. Improvement in sensor spectral

coverage is a secondary requirement.

The EOS-Color sensor specifications should provide

continuity with the SeaWiFS spectral and SNR performance. That is, EOS-Color can have additional bands with

higher digitization rates and SNR goals, but at a minimum

it should provide continuity to the SeaWiFS mission. Initial discussions with the Hughes Santa Barbara Research

Center (SBRC) indicates that additional channels beyond

the SeaWiFS baseline entails trade-offs which must be considered. However, there will be improvements in sensor

technology over the next few years which may allow these

additional bands. Such studies should begin as soon as

possible to determine their scientific and financial impact

on the mission.

Implicit in the planning for the EOS-Color baseline element is the need for temporal coverage with similar illumination conditions to SeaWiFS; this element will affect

orbital parameters such as crossing time. The most noticeable changes to EOS-Color would be an upgrade to

the onboard recorder capabilities so that 1 km data can

be collected globally, along with 12-bit digitization of the

data to improve SNR and to accommodate high quality

measurements over land. These improvements will greatly

simplify the integration of global high resolution data that

is, at present, problematic for SeaWiFS and will improve

sensor sensitivity in low chlorophyll a regions of the world

ocean. The continuity requirement also implies that ancillary support fields such as ozone, surface wind and pressure, and in situ calibration and validation observations

must be consistently available.

4.2.3 OCTS

The other pre-EOS mission is OCTS which is planned

for ADEOS. ADEOS is scheduled to e launched in 1996

and will carry a suite of sensors, including the NASA scatterometer (NSCAT). OCTS will have performance characteristics that are better than CZCS but not of SeaWiFS

quality. However, the availability of simultaneous vector

winds (from NSCAT) and SST (from the IR bands on

OCTS) will allow sophisticated studies of upper ocean dynamics. For example, it may be possible to estimate CO2

gas flux across the air-sea interface. It must be remembered, however, that OCTS was conceived primarily as

an engineering experiment in sensor design, and it is not

driven by science requirements such as those used to design

SeaWiFS, EOS-Color, and MODIS.

Currently, NASA and NASDA have ongoing discussions concerning a Memorandum of Understanding (MOU)

for ocean color and in situ data exchange between their two

scientific and technical communities. Representatives from

each of the respective scientific communities serve on the

other science team. NSF and NASDA have sponsored several workshops to coordinate ocean color science. These

workshops have also facilitated coordination of instrument

and data processing design. However, reciprocal access

to SeaWiFS and OCTS data has not been completely defined, nor have procedures been established to ensure data

compatibility.

4.3 Calibration and Validation

Through experience gained using the CZCS, the ocean

color community learned the painful process of retrieving

useful data from a sensor with slowly degrading performance and at times, strangely perturbed data (Gordon et

al. 1983). It is very difficult to determine a sensor’s calibration once it has been launched (Viollier 1982, Gordon et al.

1983, Hovis et al. 1985, Mueller 1985, and Gordon 1987).

Operating on a spacecraft shared by many sensors, the

CZCS time-shared many of the resources of the platform

such as power, recording, and communications, and operated at a maximum of 10 minutes per orbit. Such cycling

likely contributed to sensor instability through changes in

the thermal and power environments of the instrument.

The CZCS performed under such conditions, with decreasing efficiency and stability with time, for nearly eight

years. Because of the relatively large atmospheric contribution to the total observed radiances (Gordon 1981)

and the great sensitivity of the bio-optical algorithms to

the estimated water-leaving radiances (Clark 1981), small

errors in the calibration can induce sizable errors in the

derived geophysical products, rendering them useless for

many applications. On must remember that typical values

of remote-sensing reflectance (Rrs = LW /Ed where Rrs

is the reflectance, LW is the water-leaving radiance, and

Ed is the downward irradiance) for open ocean waters are

less than 0.008, so the relative stability of the instrument

performance is extremely important.

4.3.1 The CZCS Method

The method used to achieve vicarious calibration for

CZCS is described in detail in Gordon (1987) and more recently by Evans and Gordon (1994). By observing the apparent changes in water-leaving radiance values for clearwater regions (e.g., the Sargasso Sea) where stable values of normalized water-leaving radiance are the norm,

the clear, normalized water-leaving radiances, LWN (443),

LWN (520), LWN (550), were assumed to be 1.40, 0.48, and

10
Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

0.30 μW cm−2 nm−1 sr−1, respectively. The Angstrom exponents were assumed to be zero, corresponding to standard marine aerosols. The calibration was initialized after launch by forcing agreement between the sensor determined radiance and the expected radiance based upon

radiometric measurements made at the surface under very

clear atmospheric conditions. Since the calibration changed

with time, most applications occurred under more turbid

atmospheric conditions and different illumination geometries than for the initial data sets. Calibration coefficients,

derived for other scenes, were adjusted by water-leaving

radiance measurements.

Finally, a compromise calibration curve, as a function

of time, was derived based upon the best agreement between sensor-retrieved pigments and measured pigments,

since high-quality water-leaving radiance measurements

were available for only a few of the campaigns made during the operation of the CZCS. Thus, the CZCS calibration

was not strictly radiometric, but was a calibration of the

entire system including the sensor and algorithms. The vicarious calibration of the 443 nm band is tenuous because

of the great variability in LWN (443) even in clear-water.

Clearly, this approach ignores real variability that may be

present in the ocean, such as in the central gyres, so other

methods must be developed for long-term studies.

4.3.2 The SeaWiFS Method

The calibration of SeaWiFS will include both onboard

and vicarious approaches. SeaWiFS will have a deployable

diffuser plate and will be capable of periodically imaging

the moon by maneuvering the spacecraft. The diffuser

provides the means of making reflectance measurements

from the spacecraft, and the moon observation can correct

for long-term changes in the albedo of the diffuser plate.

Optical moorings will be maintained at clear-water sites

to continuously measure LWN (λ), and research campaigns

to and around the moorings will provide additional data

for vicarious calibration activities.

It is necessary to vicariously calibrate each ocean color

sensor since it is likely that the calibration will change significantly during launch. The vicarious calibration requires

extensive measurements of the optical properties of the atmosphere and ocean nearly simultaneously with a satellite

overpass. The required data cannot be obtained by simply comparing the output of two different satellites, e.g.,

MODIS and EOS-Color, when contemporaneously viewing

the same oceanic area. This is due to the highly variable

aerosol component of the signal, to variations in reflectance

with time of day, and to differences in the sensors themselves. Thus, a dedicated initialization cruise is a minimum

requirement for each ocean color sensor. After initialization, one can monitor the calibration of the two sensors by

comparing water-leaving radiances over regions with homogeneous optical properties, e.g., the Sargasso Sea. Consistency between derived radiances would suggest that the

calibration has remained stable since the last comparison.

Clear-water calibration sites in the Northern and Southern Hemispheres are needed to evaluate any effects of thermal cycling on sensor performance. It is preferable to have

multiple sites viewable on a single orbit, with northern and

southern sites in the Atlantic and Pacific oceans and a site

in the Indian Ocean. It is hoped that by controlling orbital

temperature fluctuations on the sensor to less than 2◦ C,

a high degree of performance stability can be achieved on

the sub-orbital time scale where diffuser-plate calibration

data for drift correction are unavailable.

4.3.3 Other Concerns

The ocean color sensor to follow SeaWiFS may be unable to view the moon by spacecraft maneuvering if flown

on a multi-sensor bus unless a special mirror or tilt mechanism is built into the design, e.g., MODIS and the High

Resolution Imaging Spectrometer (HIRIS) types of designs.

Moon-view capability should be a requirement for all postSeaWiFS ocean color sensors. However, if lunar viewing is

possible only through the use of special optics as opposed

to direct viewing, then particular attention must be paid

towards minimizing polarization of these systems.

It is unlikely that SeaWiFS or the EOS-Color sensor

can survive the vibrational and thermal environments of

launch without changing its calibration. Calibration errors

relative to the solar constant of the order of 5% are likely

after launch. This level of radiance error is of the order

of LW (λ), a totally unacceptable level of error even under

the best of prelaunch calibration scenarios.

Presumably the diffuser plate albedo will suffer little

degradation during launch. However, when deployed for

calibrating SeaWiFS or EOS-Color in the reflectance mode,

condensates and other particles will adhere to the surface

of the diffuser, and high-energy photons may degrade it.

Even if the prelaunch reflectance values for the diffuser surface were as accurate as 2% and no degradation occurred

after launch, that still would result in about a 40% error

in derived values of reflectance for the ocean.

For SeaWiFS and EOS-Color, a more vigorous radiometric approach will be taken. More high quality waterleaving radiance measurements from field studies are anticipated, especially in the vicinity of the calibration mooring

sites. Furthermore, rather than simply making comparisons of satellite derived versus measured pigments, comparisons of the satellite derived versus measured absorption coefficients and diffuse-attenuation coefficients can be

made, eliminating the errors induced by uncertainties in

the pigment-package effect and by variations in absorption

due to CDOM, e.g., Carder et al. 1991 and Gordon 1991.

Although the above discussion was framed in terms of

SeaWiFS and EOS-Color, the same issues apply to OCTS,

MERIS, GLI, and the MODIS sensors. Simply stated, each

sensor must be calibrated and an initial in situ validation

cruise will be required shortly after each launch. The vicarious method developed by Gordon and co-workers (Evans

11
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

and Gordon 1994) provides a powerful technique to calibrate the entire ocean color system.

An extensive calibration program is planned for the

EOS sensors; these efforts must be coordinated with the

methods described here. The issue of international coordination also arises in this context; extensive in situ observations are costly, and cooperation between the various

international partners could reduce the costs for each country.

4.3.4 Mission Overlap

The final point in the issue of calibration is the overlap between the various missions. Given that there will

be periods when more than one sensor is in orbit at any

one time, maximum priority should be given towards conducting calibration and validation cruises to compare the

sensors during these overlap periods. For example, in 1998,

SeaWiFS, OCTS, EOS-Color, MERIS, and MODIS should

all be in orbit. GLI will follow in 2000. Collecting extensive calibration and validation measurements should help

develop a consistent time series of ocean color measurements from this diverse set of sensors.

A six-month overlap between ocean color sensors, e.g.,

between SeaWiFS and EOS-Color, would enable recalibrating the likely degraded SeaWiFS with the new EOSColor. This would also ensure radiometric continuity between the two missions which, to the extent that the system algorithms (atmospheric and bio-optical) provide accurate products, would facilitate continuing studies of interannual variability. Clearly, this intercalibration effort

will require cooperation on an international level.

4.4 Data System Issues

The primary goal of a 20-year time series requires that

the data processing and distribution system be designed to

safeguard the raw data and the calibration and validation

information, to enable reprocessing, and to ensure efficient

transfer of data and algorithms to US and international

researchers. The data system cannot view itself in isolation from contemporaneous data centers or systems that

may precede or follow it. High priority must be given towards ensuring the compatibility of these basic services.

While a data system may focus on a specific mission, e.g.,

SeaWiFS, its role in the larger constellation of ocean color

missions must be retained. It must be carefully integrated

into a data systems strategy that ensures ease of use of

other Earth data sets.

Particular attention should be paid to retention of the

sensor design, calibration, and validation information. This

will allow future researchers to reprocess the data in a consistent manner. Rather than becoming a standard product

assembly line, the SeaWiFS data system should be able to

locate and retrieve the raw satellite data and apply any algorithm. Interfaces should be clearly defined so that future

advances in computer technology can be inserted. This requires a level of flexibility in the basic system design that

is not usually found in most data systems.

4.4.1 SeaWiFS

Distribution of SeaWiFS GAC derived products will be

provided by the GSFC Version 0 (V0) Distributed Active

Archive Center (DAAC). Data will be available via standard media or network access and will be governed by the

EOSDIS data charging policy. The SeaWiFS Science Team

should work with the SeaWiFS Project and V0 DAAC

to ensure that access to SeaWiFS data products satisfies

the needs of the SeaWiFS investigators. Additionally, the

methods for delivery of near-real time products for support

of cruise activities need to be identified.

Standard level-1, -2, and -3 products will be produced

by the SeaWiFS Project, which include reduced resolution

browse images and several time scales for temporal composites. In addition to the data services, standard SeaWiFS processing software will be available through the

DAAC. The browse capability will be available to registered SeaWiFS investigators through network accessible X

Window software. Data will be available following the embargo period specified in the Orbital Sciences Corporation

(the manufacturer of the SeaWiFS instrument) SeaWiFS

data purchase agreement with NASA.

4.4.2 The DAAC

The DAAC will distribute standard products as received from the SeaWiFS Project and provide for the generation of special products whose preparation costs would

be borne by the requesting investigator. Special products

could include subsetting by selected area. A series of sectors is being used by the Physical Oceanography DAAC

at the Jet Propulsion Laboratory (JPL) to distribute SST

and CZCS data that cover portions of the ocean basins.

Availability of these sectors for the new sensors would permit simpler data set manipulation by a wider user group.

Mechanisms should be identified and implemented, however, to enable dynamic subsetting of the archived data.

Also, it is noted that the DAAC has not been designed

to accommodate either raw or processed LAC (full spatial

resolution) data. Users may access catalogs that contain

the holdings of the various receiving sites that have agreed

to provide such services. However, there are no plans at

present to produce data sets composed of the full resolution, 1 km data, such as chlorophyll a in the US Exclusive

Economic Zone (EEZ).

Although there is interest in acquiring some data products directly from investigators, the basic requirement

should be flexible processing so that new algorithms can

be applied to the entire data set as scientific understanding of ocean color remote sensing evolves. The data system should be viewed as a processing and delivery system,

rather than just a storehouse for predefined standard products.

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Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

4.4.2 EOSDIS

Eventually, the needs for ocean color research will transcend those of a specific flight project (SeaWiFS). The need

to negotiate agreements with foreign data centers, as well

as the need to maintain continuity over the full suite of

ocean color missions, will require a data system with a

much larger mandate. It is clear that EOSDIS must assume responsibilities for SeaWiFS (and its successors) in

the near future. Transition of processing or services from

the SeaWiFS Project to EOSDIS should be seamless. New

capabilities can be added, but transition to the new environment should not introduce changes (or degradation) in

definition or access to products, quality, or timeliness in

delivery.

4.4.3 Data Access

Global change research is based on the premise that access to consistent, high quality data sets will be maintained

through successive generations of sensors. For ocean color

research, this implies a need to retain timely access to data

sets such as CZCS. The DAAC must provide fast access

and distribution of CZCS data as a requirement equal in

importance to the support of future data sets, e.g., SeaWiFS, MODIS, etc.

The present SeaWiFS data policy will require the EOS

data policy to be modified to include additional access and

use constraints for proprietary data sets. This policy does

not address the point at which the data provider is no

longer able to restrict distribution of multiple generation

data products. For example, do the restrictions that pertain to the original proprietary data set automatically extend to include a heat flux map that was computed in part

by incorporating a diffuse attenuation field derived by using the satellite observed radiances?

The implications of incorporating proprietary data sets

in the broader EOS data product inventory need to be articulated. The present SeaWiFS data policy, if interpreted

in the most restrictive manner, will not permit the dissemination of digital global change results to a wide range of

Earth science applications and users.

4.4.4 OCTS, MERIS, and GLI

NASA and NASDA are negotiating an MOU which lays

the framework for exchange of SeaWiFS and OCTS level

1, 2, and 3 data sets. Given the existence of access restrictions for at least one of the data sets, what is the appropriate route for US investigators to apply for access to OCTS

data and what limitations exist for use and release of data

or publication of results? Again, the need to collaborate

with the entire ocean color research community on both

science and calibration and validation issues, requires that

close ties be established between US and international scientists and agencies in conjunction with their respective

projects. Delivery and timeliness should be complementary for the two data sets. Special arrangements should

be made to support calibration and comparison of the two

data sets. It is expected that this proposed relationship

will be continued with GLI.

At present, there are no formal arrangements between

ESA and NASA on the incorporation of MERIS into the

time series of ocean color observations. In part, this is because the MERIS development activities are somewhat behind those of MODIS. Like OCTS, MERIS is viewed as an

experimental sensor with programmable bands which will

be used to explore new algorithms for land, atmosphere,

and ocean processes. MERIS is not an operational ocean

color sensor in the sense of SeaWiFS. It is unlikely that

it will be used to collect global ocean color measurements

on a consistent, daily basis; there are, however, obvious

possibilities for cooperation.

A critical issue facing the scientific use of data from

non-US sensors is the lack of support for calibration and

validation or analysis activities by US agencies. Presently,

there is no mechanism for a US investigator to obtain funding to analyze data from OCTS or MERIS. More importantly, there are no funds to support cross-calibration studies. As Earth science becomes increasingly dependent on

international partnerships to obtain critical Earth science

data, US agencies must be willing to support science and

calibration and validation activities that rely on non-US

sensors.

4.4.5 EOS-Color and MODIS

It is anticipated that the EOS-Color instrument will be

very similar to SeaWiFS, but perhaps with a radiometric

sensitivity that approaches MODIS. This being the case,

only a slight modification of the SeaWiFS and MODIS

algorithms will be required. For example, the look-up tables for the contribution by molecular scattering to the

sensor radiance will have to be recomputed for the actual

EOS-Color spectral functions. Other lookup tables may

have to be recomputed as well (depending on the structure

of the SeaWiFS and MODIS algorithms). As it is expected

that the SeaWiFS algorithms will be updated continually

as improvements are made, little effort should be required

to incorporate SeaWiFS and MODIS improvements into

EOS-Color.

The data distribution policy for EOS-Color should follow rules applicable to NASA furnished EOS sensors and

not be subject to SeaWiFS specific access and distribution

restrictions.

The EOS-Color mission is scheduled for a time frame

consistent with the launch of MODIS. It is reasonable to

assume that the EOSDIS programming and facilities support that are available to MODIS will also be available

to EOS-Color. The specific product generation facilities

could include dedicated EOS-Color, MODIS Team Leader,

or EOSDIS computer and personnel resources. The data

delivery policies and mechanisms should parallel those for

MODIS consistent with the data downlink capabilities of

the spacecraft.

13
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

Additional support may be required for sensor initialization cruises depending on the applicability of planned

MODIS experiments to support the EOS-Color sensor after launch. Support for radiative transfer modeling or

bio-optical algorithms will be required to the extent that

channel selection or sensor characteristics depart from SeaWiFS specifications. It is expected that the experience derived from the SeaWiFS mission and from the preparation

for MODIS will minimize special activities for EOS-Color.

However, additional time will be required to initialize, calibrate, and ensure quality control for the EOS-Color mission; availability of personnel resources will depend on the

phasing of the EOS-Color and MODIS missions.

4.5 Convergence

The planned ocean color missions over the next 10

years must not be viewed as interchangeable—each sensor

is being designed according to scientific and engineering requirements from each sponsoring agency. Although there

is overlap, it is a mistake to assume that one sensor can

simply be replaced by another. The goal of the science

community is a continuous observing system to monitor

and predict changes in the Earth system. Thus, the next

decade should focus on understanding the critical Earth

system processes and their associated scales of variability. In this regard, scientists must be able to define both

the measurement and sampling characteristics of a future

ocean color observing system. Such an evaluation must

include the instrument characteristics (bands, SNR, etc.)

and sampling (orbits, number of sensors, etc.).

An understanding is needed of all of the sources of error in estimating critical variables such as phytoplankton

biomass and primary productivity. The past focus with

CZCS has been on algorithm and calibration errors; future work must also consider sampling errors (Chelton and

Schlax 1991). The impacts of these errors must then be assessed on the potential scientific return from the observing

system. For example, is the cost of a higher SNR justified in terms of improved scientific understanding and

prediction, or is the improvement only marginal? How

much investment must be made in long-term moorings for

calibration given the total system (sensor plus sampling)

error?

Numerical models of the physical and biological processes in the upper ocean will play an important role in

these studies. Models will provide the underpinning for

any ocean prediction system. However, it is apparent that

the models are too primitive at present, even in the area of

physical oceanography. The ties must be strengthened between modeling and observing systems so that the two approaches can complement each other. Because such models must rely on both physical and biological data sets, the

development of an ocean color observing system must also

specify the necessary data sets on physical processes.

At present, there is very little interagency coordination

at this level. The responsible agencies are just beginning

to explore fundamental issues such as calibration and data

systems, but the missions are still viewed as essentially

separate. The science community must use this opportunity of multiple sensors to conduct the necessary studies

and evaluations. This must be an international effort from

the outset with an eye towards developing a cost effective

system for making ocean color observations over the long

term in the context of climate change. Tradeoffs between

sensor capabilities and cost must be made in light of the

overall science return of the mission.

5. An Implementation Plan

This section discusses issues that need to be addressed

in order to implement the plan.

5.1 Science Oversight

The development of a 20-year time series of ocean color

observations from a disparate set of sensors will require an

enormous effort and cooperation between many agencies

and several countries. At present, there is no formal group

at the government level in the US that has responsibilities

for these activities.

1 Recommendation: CENR should form an interagency working group on satellite ocean color research and applications with representation from all

interested US agencies. A charter for this working

group should include both US and foreign missions.

It should serve as the focal point for foreign collaboration. This group must also consider the necessary

modeling activities and physical observations that

will be required to analyze and interpret ocean color

data.

Presently, NASA has three ocean color missions in various stages of planning and implementation, each with its

own management structure. Given the interlocking web

of funding, algorithm development, and management, a

coherent, coordinated plan must be developed as soon as

possible. Not only will this result in a more effective use

of investigators’ time, it will also provide a roadmap so

that the research community and NASA can identify how

resources are being allocated.

2 Recommendation: NASA should convene a meeting

of the appropriate project and program personnel,

including contract management, along with representatives of the ocean color research community as

soon as possible to develop an overall ocean color

program. This program should consist of plans for

research, software development, data processing and

delivery, funding, and management.

5.1.1 EOS-Color

Although the initial plan is for EOS-Color specifications to be identical to those of SeaWiFS, there are some

14
Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

potential improvements that must be investigated from a

scientific, technical, and financial point of view. These include lossless data compression, or additional recorder capacity, so that 1 km resolution data can be collected globally; improved digitization (12 bits versus 10 bits for SeaWiFS); increased SNR; and the possibility of additional

bands. With a launch date of 1998, these studies should

begin as soon as possible. The impacts of EOS-Color on

EOSDIS and other aspects of the EOS Project also need

to be evaluated.

3 Recommendation: An EOS-Color Mission Working

Group should be designated during calendar year

1994. This should include both science and project

representation. This group should consist of members of the MODIS Oceans Team and the SeaWiFS

Team. It should be tasked with providing the science oversight for the EOS-Color mission.

5.1.2 EOS-Color and SeaWiFS Interfaces

The community has expressed a clear desire that an

effort be initiated to produce a consistent, decadal scale,

global time series of satellite ocean color observations. This

suggests that science, mission management, and data management will have to be coordinated between SeaWiFS,

EOS-Color and MODIS so that products, data sets, calibration, validation, etc., are consistent across these efforts.

To address these issues, there must be a consistent view

from the scientific community, from NASA, and other federal agencies. Community consensus should be fostered by

formation of interlocking science teams for the missions,

while a single program manager should be designated to

coordinate these missions in NASA. Federal interagency

issues should be addressed by the aforementioned interagency group.

Coupled with interlocking science teams and interagency management must be a coordinated approach to

data management. Scientific need and available resources

necessitate a single, workable interface to ocean color data

fields, not several. Given the current EOSDIS architecture

it seems that the most effective mechanism would be to

generalize the current MODIS arrangement with EOSDIS

to include EOS-Color as an early EOSDIS, prelaunch (preMODIS) data stream. This would build upon the SeaWiFS

and EOS DAAC structure currently being implemented

to provide SeaWiFS data fields to the community. However, it is also clear that the present DAAC plans for SeaWiFS will not accommodate LAC (1 km resolution) data.

Clearly, there will need to be a transition from SeaWiFS

to MODIS which has 1 km resolution. The data system for

SeaWiFS and EOS-Color could help in this transition.

4 Recommendation: EOSDIS should consider SeaWiFS and EOS-Color as a prelaunch system capability test.

5.1.3 The Science Teams

The MODIS Oceans Team was chosen to provide guidance for the MODIS-T and MODIS-N instruments with

respect to ocean color and SST parameters. Thus, the

MODIS Oceans Team is the natural unit to provide guidance for the development of the EOS-Color instrument.

Augmentation of team responsibilities would be an efficient, timely mechanism to expedite EOS-Color instrument scientific design and mission planning. The recent

inclusion of the MODIS Oceans Team in the SeaWiFS Science Team has established a workable venue for coordination between EOS-Color, MODIS, and SeaWiFS. This

same venue would be equally usable for EOS-Color.

5 Recommendation: The MODIS Oceans Team

should be designated the EOS-Color Science Team,

which would be expanded upon the results of an

EOS-Color NRA. NASA should negotiate precise

agreements with the MODIS Oceans Team regarding deliverables and funding. These agreements

must be coordinated across the full set of ocean

color activities so that an efficient, realistic plan is

developed.

The SeaWiFS NRA makes it clear that the NRA process is a very good mechanism for encouraging international collaboration, as well as an excellent way to broaden

the US satellite ocean color community. Rather than a second announcement for SeaWiFS efforts in the mid-90s, it

may be more appropriate for NASA to issue an EOS-Color

NRA two years prior to launch. This NRA could then capitalize on SeaWiFS and OCTS observations with a view

toward a decadal time series and the use of ocean color

heavily focused on primary productivity, integrated ocean

models, etc.

6 Recommendation: NASA should plan for an EOSColor NRA for the 1996–97 time frame.

5.1.4 OCTS, MERIS, and GLI

As with SeaWiFS, international participation on science teams has been extremely valuable. Similar crossappointments should be established for OCTS, MERIS,

and GLI. Such relationships strengthen scientific ties and

help leverage resources of all participating countries.

7 Recommendation: NASA should encourage investigator relationships between US researchers and

their foreign colleagues. This may require agreements on data delivery and policies, in which case

NASA, ESA, and NASDA should establish appropriate understandings as soon as possible.

5.2 Calibration and Validation

Initial calibration and validation cruises for each mission must be performed in waters with no significant horizontal gradients in the water-leaving radiances and with

15
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

vertically isotropic fields of inherent optical properties. For

initial calibration and validation research campaigns, this

dictates that waters be used with low pigment concentrations which have little sub-pixel scale or mesoscale patchiness.

Effects of spacecraft navigational errors and sub-pixel

patchiness must not be allowed to contribute to radiance

variations in excess of the noise inherent in the instrument.

In the subtropical gyres, these conditions can usually be

met if cold-core eddies are absent. Such eddies are usually

detectable from both AVHRR and ocean color imagery.

Phytoplankton chlorophyll a and phycoerythrin pigment can be easily mapped using aircraft laser systems.

Also, concurrent SST and airborne expendable bathythermograph (AXBT) data can be used to define the complete volumetric temperature field. Finally, the airborne

passive sensors can supply downwelling irradiance and upwelling radiance within the calibration and validation region. Coupled with ship transects (Smith and Baker 1985)

and buoys, the complete multi-platform sensor suite (Smith

et al. 1987) can be brought to bear on the characterization

of the in-water optical properties.

8 Recommendation: As soon after launch as possible,

calibration and validation cruises must take place

in regions with appropriate bio-optical properties.

To reduce atmospheric effects and to extend clear-water

calibration and validation studies to higher latitudes, consideration should be given to using and instrumenting large,

oligotrophic mountain lakes such as Lake Tahoe, Lake Titicaca, and Lake Baikal for calibration and validation activities for EOS-Color. Logistical costs would be greatly

reduced for lake moorings and cruises, and aerosol optical thicknesses would be relatively thin and more easily

monitored from a stable, shore-based facility. These measurements may help to more effectively separate sensor calibration issues from atmospheric correction errors and difficulties with pigment algorithms.

9 Recommendation: Feasibility studies should be conducted on the use of high-altitude, oligotrophic lakes

as calibration and validation sites.

5.2.1 Required Cruises

Shortly after launch, at least two vessels should be positioned in the Pacific, one each in southern and northern

clear waters, most likely near 30◦ N and 30◦ S latitudes.

They should be positioned so that both would be near

the center of the swath on a given orbit and should be

well away from eastern boundaries. Two additional vessels

could be used in the Atlantic in similar positions if the orbit

is ascending. This deployment should permit detection of

any significant thermal effects on the sensor performance

over the 60◦ latitude separation between ships, and will

provide several summer-winter pairs and spring-fall pairs

of observations during the first 90 days after sensor turnon. It ensures that solar zenith angles as low as 7◦ and

greater than 50◦ will be encountered by at least one ship in

clear water for calibration initialization activities. At least

one time during this initialization period, the ship tracks

should converge for intercalibration purposes. Clear lake

measurements can extend the range of sun angles and latitudes encountered to provide further checks on the thermal

stability of the sensor.

10 Recommendation: In order to investigate thermal

effects on sensor performance, calibration and validation cruises must be located in both northern and

southern waters.

Additional cruises will be required to evaluate instrument and algorithm performances for eastern-boundary

and high-latitude settings, regions subjected to infusions

of desert aerosols, and for various major river plumes and

coastal environments. These waters are expected to affect

algorithms in the following ways:

1. High-latitude, spring bloom regions and easternboundary upwelling produce phytoplankton which

are large with significant nonlinear light absorption effects due to pigment packaging. Degradation

products from senescent blooms, e.g., CDOM and

detritus, provide excess absorption relative to Case

1 waters (Carder et al. 1991).

2. High-latitude stations will test the robustness of the

method as they have low sensor signals, large solar

slant paths through the atmosphere, and high wind

stress, e.g., large foam areas, marine aerosol concentrations, and wave slopes.

3. The eastern tropical Atlantic and the northwest Pacific are subject to large inputs of mineral aerosols

from the Sahara and the Gobi deserts, respectively.

There is evidence that, unlike typical marine aerosols, such dust absorbs strongly in the blue region

of the spectrum. It is essential to verify that the atmospheric correction algorithms perform properly

in such regions to enable the derivation of accurate

bio-optical parameters and to assess the influence

of such materials on productivity.

4. River plumes will provide site-specific particle albedos and terrigenous CDOM in addition to largecelled, diatom-rich phytoplankton assemblages nearshore and smaller cells offshore. Much of the color

in the plumes may be due to CDOM.

5. Coastal environments are expected to be site specific due to unique colors of suspended sediments and

terrestrial-marine mixes of CDOM, as well as optically complicated due to the shorter time and space

scales of variation.

These cruises are deemed to be of secondary importance during the initial 90 days of sensor operation since

sensor calibration cannot be easily accomplished in such

16
Abbott, Brown, Evans, Gordon, Carder, M ̈uller-Karger, and Esaias

waters. Resources can be diverted to these other areas

after sensor initialization is complete. The measurements

and protocols required for the calibration and validation

cruises are detailed in Mueller and Austin (1991).

Note that the Commonwealth Scientific and Industrial

Research Organization (CSIRO) of Australia, is developing calibration sites for both land and ocean observations.

Given that there is the possibility that SeaWiFS may return useful data from land surfaces, it is recommended that

NASA coordinate with Australian researchers on the use

of these sites for both SeaWiFS calibration and intercalibration with other sensors.

11 Recommendation: Although not needed during the

initial period of sensor operation, calibration and

validation cruises should be planned for other biooptical water types.

5.2.2 Expansion of Moorings

International partners, such as Japan, have plans for

bio-optical moorings to support their ocean color missions.

By providing data from NASA supported moorings to these

partners in exchange for access to data from their mooring, this critical sensor calibration activity can be effectively expanded at minimal cost. Not only should data be

exchanged, but information on calibration techniques and

protocols should be transferred so that these data can be

used effectively.

12 Recommendation: NASA should encourage investigators to collaborate with their foreign colleagues

to develop a global network of bio-optical moorings.

5.3 Access to Data

The restrictions imposed by data purchase agreements,

such as SeaWiFS, are counter to the open access policy

established by EOS. Derived products, such as heat flux,

that may be based in part on SeaWiFS data may be subject

to commercial restrictions. NASA must work to eliminate

these restrictions whenever possible. Although EOS-Color

may be a data purchase agreement, NASA must ensure

that there is no embargo period for data access nor any

restrictions on the distribution of data or derived products.

13 Recommendation: NASA must work to eliminate

all restrictions on access to ocean color observations,

consistent with the EOS data policy. This policy

must apply to both US and foreign researchers.

The transition between processing systems for a given

sensor should not result in a change of the product. To the

extent that the sensor specifications permit, with the introduction of a new sensor type, products associated with

the previous sensors should be continued. The SeaWiFS

system, product format, or data delivery mechanisms may

need to evolve to become and remain compliant with EOS

standards as these become better defined with the implementation of EOSDIS.

14 Recommendation: Consistency should be sustained

between the various sensor data sets as they move

from one data processing and delivery system to

another.

In the next few years, ocean color data from foreign

partners will become increasingly important. However, the

mechanism for data transfer, criteria for timeliness and

formats, and other requirements, have not been defined.

With the need to integrate both sensor and in situ data

sets, NASA must develop effective working relationships

with its international partners to obtain maximum scientific return at minimum cost. These relationships should

be established at the investigator level with the support of

NASA.

15 Recommendation: SeaWiFS and OCTS should act

as a testbed for such exchanges between international partners. Although the primary focus may be

at the investigator level, NASA may need to support efforts on data policies, data exchange, and

satellite downlinks.

5.4 Convergence

Each of the planned ocean color missions, while similar

in their basic observing capabilities, is being designed with

unique engineering and scientific requirements as well as

limitations. While calibration information and data access

will help develop a consistent, ocean color time series, the

international science community must use this opportunity

to design a comprehensive ocean color observing system.

Such a system must measure the critical processes at the

appropriate scales. At present, the basic phytoplankton

pigment measurement is understood, but not all of the

critical processes, or their scales of variability, are known

in order to design an effective measurement system.

16 Recommendation: NASA should coordinate research activities with the other sponsoring agencies

to develop the observing and sampling requirements

for an ocean color system that will make the essential measurements for ocean monitoring and prediction.

While a baseline set of SeaWiFS products will be available from EOSDIS, there is currently no defined set of

LAC (1 km) products. An effort needs to be coordinated

to define such high spatial resolution products and formats which are required by coastal resource managers and

other operational users. These plans must be implemented

to make full use of SeaWiFS for coastal management.

17 Recommendation: An interagency effort needs to be

implemented to define new products for the coastal

zone and to collect, process, and distribute the LAC

data.

Coupled physical and biological models must be developed in concert with the observing systems. Too often,

data sets and models are produced in isolation without

17
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

regard to the needs and limitations of the other. The

strengths and weaknesses of both models and data must be

evaluated so that scientists can develop useful predictive

models of the ocean system. These studies must not focus

solely on ocean color data, but on the full suite of physical

and biological measurements that can be made from space.

18 Recommendation: NASA must support efforts to

link ocean models with both physical and biological data and ensure that lessons learned from both

modeling and data analysis are used in the design

of ocean color observing systems.

Glossary

ACRIM Active Cavity Radiometer Irradiance Monitor

ADEOS Advanced Earth Observing Satellite

AM-1 Not an acronym, used to designate the morning

platform of EOS

AVHRR Advanced Very High Resolution Radiometer

AXBT Airborne Expendable Bathythermograph

CDOM Colored Dissolved Organic Matter

CENR Committee on Environment and Natural Resources

CSIRO Commonwealth Scientific and Industrial Research

Organization (of Australia)

CZCS Coastal Zone Color Scanner

DAAC Distributed Active Archive Center

DMS dimethyl sulfide

DOC dissolved organic carbon

DOM dissolved organic matter

EEZ Exclusive Economic Zone

ENSO El Ni ̃no Southern Oscillation

ENVISAT Environmental Satellite

EOS Earth Observing System

EOSDIS EOS Data and Information System

ESA European Space Agency

GAC Global Area Coverage

GLI Global Imager

GLOBEC Global Ocean Ecosystems dynamics

GSFC Goddard Space Flight Sensor

HIRIS High Resolution Imaging Spectrometer

IR Infrared

JGOFS Joint Global Ocean Flux Study

JPL Jet Propulsion Laboratory

LAC Local Area Coverage

LANDSAT Land Resources Satellite

LOICZ Land Ocean Interaction in the Coastal Zone

MERIS Medium Resolution Imaging Spectrometer

MODIS Moderate Resolution Imaging Spectrometer

MODIS-N Nadir-viewing MODIS instrument

MODIS-T Tilted MODIS instrument to minimize sun glint

MOU Memorandum of Understanding

NASA National Aeronautics and Space Administration

NASDA National Space Development Agency of Japan

NOAA National Oceanic and Atmospheric Administration

NRA NASA Research Announcement

NSCAT NASA Scatterometer

NSF National Science Foundation

OCTS Ocean Color Temperature Sensor

OSC Orbital Sciences Corporation

PM-1 Not an acronym, used to designate the afternoon

platform of EOS

POC Particulate Organic Carbon

SBRC Santa Barbara Research Center

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SNR Signal-to-Noise Ratio

SST Sea Surface Temperature

UV Ultraviolet

V0 Version 0

Symbols

Ed Reflectance.

LW Water-leaving radiance.

LWN (λ) Normalized water-leaving radiance.

Rrs Reflectance

λ Wavelength

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The SeaWiFS Technical Report Series

Vol. 1

Hooker, S.B., W.E. Esaias, G.C. Feldman, W.W. Gregg, and

C.R. McClain, 1992: An Overview of SeaWiFS and Ocean

Color. NASA Tech. Memo. 104566, Vol. 1, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 24 pp., plus color plates.

Vol. 2

Gregg, W.W., 1992: Analysis of Orbit Selection for SeaWiFS:

Ascending vs. Descending Node. NASA Tech. Memo.

104566, Vol. 2, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16 pp.

Vol. 3

McClain, C.R., W.E. Esaias, W. Barnes, B. Guenther, D. Endres, S. Hooker, G. Mitchell, and R. Barnes, 1992: Calibration and Validation Plan for SeaWiFS. NASA Tech.

Memo. 104566, Vol. 3, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 41 pp.

Vol. 4

McClain, C.R., E. Yeh, and G. Fu, 1992: An Analysis of GAC

Sampling Algorithms: A Case Study. NASA Tech. Memo.

104566, Vol. 4, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 22 pp., plus color plates.

Vol. 5

Mueller, J.L., and R.W. Austin, 1992: Ocean Optics Protocols. NASA Tech. Memo. 104566, Vol. 5, S.B. Hooker and

E.R. Firestone, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 43 pp.

Vol. 6

Firestone, E.R., and S.B. Hooker, 1992: SeaWiFS Technical

Report Series Summary Index: Volumes 1–5. NASA Tech.

Memo. 104566, Vol. 6, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 9 pp.

Vol. 7

Darzi, M., 1992: Cloud Screening for Polar Orbiting Visible

and IR Satellite Sensors. NASA Tech. Memo. 104566, Vol.

7, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 7 pp.

19
Ocean Color in the 21st Century: A Strategy for a 20 -Year Time Series

Vol. 8

Hooker, S.B., W.E. Esaias, and L.A. Rexrode, 1993: Proceedings of the First SeaWiFS Science Team Meeting. NASA

Tech. Memo. 104566, Vol. 8, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 61 pp.

Vol. 9

Gregg, W.W., F.C. Chen, A.L. Mezaache, J.D. Chen, J.A.

Whiting, 1993: The Simulated SeaWiFS Data Set, Version 1. NASA Tech. Memo. 104566, Vol. 9, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 17 pp.

Vol. 10

Woodward, R.H., R.A. Barnes, C.R. McClain, W.E. Esaias,

W.L. Barnes, and A.T. Mecherikunnel, 1993: Modeling of

the SeaWiFS Solar and Lunar Observations. NASA Tech.

Memo. 104566, Vol. 10, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 26 pp.

Vol. 11

Patt, F.S., C.M. Hoisington, W.W. Gregg, and P.L. Coronado,

1993: Analysis of Selected Orbit Propagation Models for

the SeaWiFS Mission. NASA Tech. Memo. 104566, Vol.

11, S.B. Hooker, E.R. Firestone, and A.W. Indest, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16 pp.

Vol. 12

Firestone, E.R., and S.B. Hooker, 1993: SeaWiFS Technical Report Series Summary Index: Volumes 1–11. NASA Tech.

Memo. 104566, Vol. 12, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 28 pp.

Vol. 13

McClain, C.R., K.R. Arrigo, J. Comiso, R. Fraser, M. Darzi,

J.K. Firestone, B. Schieber, E-n. Yeh, and C.W. Sullivan, 1994: Case Studies for SeaWiFS Calibration and Validation, Part 1. NASA Tech. Memo. 104566, Vol. 13,

S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 52 pp., plus

color plates.

Vol. 14

Mueller, J.L., 1993: The First SeaWiFS Intercalibration RoundRobin Experiment, SIRREX-1, July 1992. NASA Tech.

Memo. 104566, Vol. 14, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 60 pp.

Vol. 15

Gregg, W.W., F.S. Patt, R.H. Woodward, 1994: The Simulated SeaWiFS Data Set, Version 2. NASA Tech. Memo.

104566, Vol. 15, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 42 pp., plus color plates.

Vol. 16

Mueller, J.L., B.C. Johnson, C.L. Cromer, J.W. Cooper, J.T.

McLean, S.B. Hooker, and T.L. Westphal, 1994: The Second SeaWiFS Intercalibration Round-Robin Experiment,

SIRREX-2, June 1993. NASA Tech. Memo. 104566, Vol.

16, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 121 pp.

Vol. 17

Abbott, M.R., O.B. Brown, H.R. Gordon, K.L. Carder, R.E.

Evans, F.E. Muller-Karger, and W.E. Esaias, 1994: Ocean

Color in the 21st Century: A Strategy for a 20 -Year Time

Series. NASA Tech. Memo. 104566, Vol. 17, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 20 pp.

20
 Form Approved

 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering

 and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of

 information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite

 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED

 June 1994 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

 SeaWiFS Technical Report Series

 Volume 17–Ocean Color in the 21st Century: A Strategy for a 20-Year Time Series Code 970.2

 Series Editors: Stanford B. Hooker and Elaine R. Firestone

6. AUTHOR(S)

 Mark R. Abbott, Otis B. Brown, Robert H. Evans, Howard R. Gordon,

 Kendall L. Carder, Frank E. Muller-Karger, and Wayne E. Esaias

Laboratory for Hydrospheric Processes

Goddard Space Flight Center

Greenbelt, Maryland 20771 94B00091

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING

 AGENCY REPORT NUMBER

National Aeronautics and Space Administration

Washington, D.C. 20546–0001 TM–104566, Vol. 17

11. SUPPLEMENTARY NOTES

12a. DISTRIBUTION/AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE

 Mark R. Abbott: Oregon State University, Corvallis, Oregon; Otis B. Brown, Robert H. Evans, and Howard R. Gordon:

University of Miami, Miami, Florida; Kendall L. Carder: University of South Florida, St. Petersburg, Florida; Frank E. MullerKarger: NASA Headquarters, Washington, DC; and Elaine R. Firestone: General Sciences Corporation, Laurel, Maryland

13. ABSTRACT (Maximum 200 words)

14. SUBJECT TERMS 15. NUMBER OF PAGES

 16. PRICE CODE

17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT

 OF REPORT OF THIS PAGE OF ABSTRACT

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION

 REPORT NUMBER

Unclassified–Unlimited

Subject Category 48

 -

SeaWiFS, Oceanography, Calibration, Validation, Data System, Ocean Color, EOS-Color, 20

CZCS, EOSDIS, MODIS

Report is available from the Center for AeroSpace Information (CASI),

7121 Standard Drive, Hanover, MD 21076–1320; (301)621-0390

Beginning with the upcoming launch of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), there should be almost

continuous measurements of ocean color for nearly 20 years if all of the presently planned national and international

missions are implemented. This data set will present a unique opportunity to understand the coupling of physical and

biological processes in the world ocean. The presence of multiple ocean color sensors will allow the eventual development

of an ocean color observing system that is both cost effective and scientifically based. This report discusses the issues

involved and makes recommendations intended to ensure the maximum scientific return from this unique set of planned

ocean color missions. An Executive Summary is included with this document which briefly discusses the primary issues

and suggested actions to be considered.

 Unclassified Unclassified Unclassified Unlimited

 REPORT DOCUMENTATION PAGE OMB No. 0704-0188

NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. 239-18, 298-102