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| **FIRE PHASE III RESEARCH PLAN**                                      |
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| **SYSTEMATIC INVESTIGATIONS OF CLIMATICALLY**                         |
|                                                                       |
| **IMPORTANT CLOUD SYSTEMS**                                           |
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|                                                                       |
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| **DRAFTING PANELS:**                                                  |
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| **UPPER TROPOSPHERIC CLOUD SYSTEM PANEL:**                            |
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|                                                                       |
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| > **D. O\'C. Starr, T. Ackerman, S. Cox, A. DelGenio,**               |
| >                                                                     |
| > **M. Hardesty, A. Heymsfield, P. Minnis, K. Sassen,**               |
| >                                                                     |
| > **G. Stephens, and F. Valero**                                      |
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|                                                                       |
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| **BOUNDARY LAYER CLOUD SYSTEM PANEL:**                                |
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|                                                                       |
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| > **D. Randall, C. Bretherton, J. Curry, C. Fairall,**                |
| >                                                                     |
| > **S. Kreidenweis, R. Kropfli, D. Lenschow, D. Lilly,**              |
| >                                                                     |
| > **W. Schubert, J. Ogren, and B. Wielicki.**                         |
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|                                                                       |
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| > **Available From:**                                                 |
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| > **FIRE Project Office**                                             |
| >                                                                     |
| > **M.S. 483**                                                        |
| >                                                                     |
| > **NASA Langley Research Center**                                    |
| >                                                                     |
| > **Hampton, VA 23681-0001**                                          |
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| ***July 1994***                                                       |
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**TABLE OF CONTENTS**

**EXECUTIVE SUMMARY** 1

**1. INTRODUCTION** 9

**2. HISTORY OF FIRE** 11

**3. PAST, PRESENT, AND FUTURE** 15

**4. UPPER TROPOSPHERIC CLOUD SYSTEMS** 21

4.1. Objectives of FIRE III 21

4.2. Critical Scientific Questions to be Addressed 23

4.3. Research Strategy 29

4.4. Conclusions 41

4.5. References 43

**5. ARCTIC CLOUD SCIENCE PLAN** 61

5.1. Introduction 61

5.2. Scientific Issues and Objectives 65

5.3. Field Measurements 85

5.4. Modeling Studies 111

5.5. Conclusions 117

5.6. References 122

**6. FIRE MANAGEMENT AND SCIENTIFIC ORGANIZATION** 133

6.1. Management 133

6.2. Project Management 135

6.3. FIRE-III Science Team 135

6.4. Data Management and Protocol 136

6.5. National and International Collaborations 137

**APPENDIX A -
ACRONYMS.**\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\...\....
139

**EXECUTIVE SUMMARY**

The First ISCCP Regional Experiment (FIRE) has conducted basic research
on climatically important cloud systems. FIRE was conceived in 1982 as a
national US research program responding to the needs of ISCCP
(International Satellite Cloud Climatology Project), an international
WMO program. Throughout its history, FIRE has been especially interested
in the cloud - climate connection. As a result, integrated,
interdisciplinary studies involving experimentalists, theoreticians and
modelers have been planned and executed by the broad-based community of
FIRE scientists. These specialists span the fields of radiation, cloud
microphysics and dynamics ranging from cloud scale to the general
circulation.

Previous FIRE research has centered on midlatitude cirrus cloud systems
and subtropical marine boundary layer cloud systems. It has enhanced our
ability to both monitor these systems from satellites and to include
their radiative effects in models of various scales. It has greatly
increased our understanding of the control of these cloud systems by the
large-scale circulation and has greatly enhanced our ability to
realistically simulate these systems in GCMs. Modeling studies and field
campaigns have greatly enhanced our understanding of these two
climatically important cloud regimes. FIRE GCM research has added to our
understanding of the importance of these cloud regimes in the climate
system.

FIRE has identified serious deficiencies in our ability to observe
climatically important cloud systems. New instrumentation, platforms and
observational techniques are required prior to mounting future field
campaigns. Special observational needs are listed below:

*• Individual particle and volume-average radiative properties;*

*• Radiative flux measurements;*

*• Microphysical properties;*

*• Aerosol properties;*

> *• Ice forming nuclei;*
>
> *• Chemical species (including water vapor);*
>
> *• Continued development and exploitation of remote-sensing systems;*
>
> *• New/improved methods for satellite data utilization/application in
> the EOS era;*
>
> *• Platform development*
>
> *UAV\'s*
>
> *NCAR WB 57*
>
> *NOAA Gulfstream IV*

*FIRE Phase III has two primary components.*

**An Upper-tropospheric cloud component** which consists of continuing
investigations of middle latitude cirrus cloud systems with a methodical
transition of emphasis to tropical upper-tropospheric cloud systems;

**A Boundary-layer/Arctic Stratus component** which consists of
continuing investigations of subtropical marine stratocumulus systems
and a new thrust aimed at Arctic Stratus cloud systems.

Specific research goals common to both the upper tropospheric and
boundary layer components of FIRE III are:

> Apply FIRE Phase I and II model and field campaign results to the
> improvement and evaluation of cloud-system parameterizations employed
> in large eddy simulation (LES) and global climate models (GCMs).
>
> Apply FIRE Phase I and II field campaign and theoretical results to
> develop and verify improved techniques for the inference of cloud
> radiative and microphysical properties from satellite and surface
> based data.
>
> Define the total water substance (vapor, liquid and ice) environment
> and transports associated with cloud systems.
>
> Define, design, test and implement measurement systems to observe
> key.microphysical and radiative properties of cirrus and boundary
> layer clouds and cloud systems.
>
> Advance our understanding of climatically important cloud systems, the
> variability of their microphysical and radiative properties, the key
> processes involved in their formation and dissipation, and their roles
> in regulating the flow of energy between the surface and the
> atmosphere.
>
> Provide a methodical transition from FIRE Phases I and II
> accomplishments to a coherent research plan for the next generation of
> research on climatically important cloud systems.

The **FIRE III Upper Tropospheric Cloud Component** will adopt the
following strategies.

> The continued analysis of the wealth of observations obtained during
> the FIRE
>
> Phases I and II field campaigns and the FIRE extended time
> observations.
>
> The definition and execution of limited highly-focused observational
> programs to complement our current understanding of cirrus cloud
> systems.
>
> The assessment of the need for and subsequent definition and execution
> of a major field campaign focused on tropical upper-tropospheric cloud
> systems.

Critical questions to be addressed in the upper-tropospheric cloud
component are:

*What are the distributions and amounts of ice mass and total water in
the upper troposphere?*

> • How can ice mass be determined from remote sensors and how can
> these. . measurements be validated?
>
> • How do the total water, the ice mass and their distributions depend
> on large-scale meteorological parameters such as temperature, vertical
> motion, wind shear, etc.?
>
> • How are the total water mass and ice mass distributions related to
> detrainment from deep convective cloud systems?
>
> • How do the local and regional evolutions of total water and cloud
> ice mass distributions and their small-scale variability depend on the
> ice formation process (e.g. synoptic ascent versus convective
> detrainment?

*What are the microphysical properties of upper tropospheric clouds?*

> • How do the particle sizes, shapes and phase depend on the large
> scale environment?
>
> • How does microphysical composition affect the evolution of the cloud
> system and the tropospheric water budget (interactions between cloud
> layers, vertical water transports, precipitation at the surface)?
>
> • What are the microphysics of cirrus formed at extremely low
> temperatures?
>
> • How do aerosols impact the microphysical development of cirrus
> clouds?

*What are the radiative properties of upper-tropospheric clouds and how
do they relate to the ice mass, and the microphysical and macrophysical
characteristics of the cloud?*

> • What are the scattering phase functions, asymmetry parameters, and
> optical extinction parameters associated with microphysical
> distributions?
>
> • How can these radiative properties be directly and accurately
> observed from airborne, satellite and surface-based platforms?
>
> • Can these radiative properties be usefully expressed in terms of an
> effective particle size that is consistent with cloud ice path and
> optical depth?
>
> • How do the vertical and horizontal structures of cirrus clouds
> affect their bulk radiative properties and how does this impact the
> remote sensing of cloud microphysical properties?

*How representative are midlatitude continental cirrus of upper
tropospheric clouds in other regions of the globe?*

> • Will GCMs be able to use a single universal cirrus parameterization
> for all. . latitudinal and regional domains?
>
> • Are tropical cirrus cloud systems sufficiently different from their
> midlatitude. . cousins to call for a tropical cirrus field campaign?

The **FIRE III Boundary Layer/Arctic Stratus Cloud Component** will
adopt the following strategies:

> • The continued analysis of the wealth of observations obtained during
> the FIRE-San Nicholas Island and ASTEX field campaigns and the FIRE
> extended time observations.
>
> • The definition and execution of a field campaign to assess the roles
> of arctic stratus clouds in the high latitude climate system.

The extension of FIRE research into the Arctic is motivated by:

> • Errors in simulations of the present-day Arctic climate by GCMs and
> the disagreements among the models concerning Arctic climate-change
> predictions;
>
> • Questions about possible amplification of global change in the
> Arctic and. . disagreement between models and observations;
>
> • Questions concerning the stability of the Arctic ice pack;
>
> • The lack of in situ data to validate and improve satellite
> retrievals and GCM. . performance in the Arctic.

Arctic clouds are important for a wide variety of climate processes such
as:

> • Arctic and global radiation balance;
>
> • Interactions with large-scale dynamical systems such as cold-core
> cyclones;
>
> • Maintenance of the pole-to-equator temperature gradient;
>
> • Sea ice characteristics such as temperature, albedo, ice volume and
> rate of. . transport to the North Atlantic.

The FIRE Arctic stratus cloud system emphasis beautifully complements
the SHEBA (Surface HEat Budget in the Arctic) program and the ARM North
Slope of Alaska program.

Key scientific questions to be addressed in the Arctic FIRE are:

> • What are the key deficiencies of current climate model simulations
> of the present Arctic climate, especially with respect to clouds and
> their effects on the surface energy budget?
>
> • How do the extreme static stability and low atmospheric water vapor
> content of the Arctic lower troposphere, particularly during winter,
> affect the flow of energy across the air-sea interface?
>
> • How do leads and polynas affect the area-averaged exchanges of
> energy and chemical species across the air-sea interface?
>
> Whereas only about 1-2% of the surface is occupied by leads in the
> winter, it has been hypothesized that leads contribute about 50% of
> the surface source of moisture and heat on the polar ice cap in
> winter. Leads are the only channel for release to the atmosphere of
> gases generated in the ocean by biological processes.
>
> • What is the mechanism that leads to the spectacular
> multiple-layering of Arctic summer stratus?

Key questions arising from a parochially radiative perspective are:

> • What are the effects of springtime Arctic haze on the absorption of
> solar radiation in polar clouds?
>
> • What is the relationship between cloud optical properties and CCN
> and IFN abundances?
>
> • How do the optical properties of the Arctic surface (albedo,
> emissivity, etc.) vary in response to changes in snow characteristics
> (thickness, age, temperature, contamination), thinning of the ice, and
> melt pond formation?
>
> • How do the large solar zenith angles characteristic of the Arctic
> alter the macroscopic optical properties of the clouds and the
> surface, and how should remote sensing strategies be altered to
> account for this?
>
> • What is the role of \"clear-sky\" ice crystal precipitation in
> determining the surface longwave radiation, and in snow accumulation?

Key questions in the atmospheric chemistry and cloud microphysics
sectors are:

> • What processes produce CCN and IFN in the Arctic, or transport them
> into the Arctic, or remove them from the Arctic atmosphere and how do
> these processes vary with season?
>
> • What are the chemical composition and size distributions of CCN and
> IFN?
>
> • What are the chemical compositions of these particles?
>
> • What determines their effectiveness in nucleating cloud particles?
>
> • What is the effect of the relative abundance of CCN and IFN upon the
> phase of the cloud particles?
>
> • What is the relationship between the cloud droplet size distribution
> and the size and chemical composition of the CCN?
>
> • What is the relationship between the crystal habit and size
> distribution and the size and chemical composition of the IFN?
>
> • What is the importance of sedimentation (for diamond dust) and
> precipitation (for ice and liquid water clouds) in determining CCN and
> IFN populations?

In addressing the questions presented above, FIRE III recognizes a
strong common interest with other programs. Those most directly related
include SHEBA (Surface HEat Budget in the Arctic), SASS (Subsonic
Assessment Program), DOE/ARM (Department of Energy/Atmospheric Radiation
Measurements); MCTEX (Marine Continental Thunderstorm Experiment), GEWEX
(Global Energy and Water Experiment); and ROCEW (NSF - Role of Clouds,
Energy and Water). There is also considerable international activity in
these same cloud-climate research arenas. Past FIRE collaboration with
scientists from the United Kingdom, France, Germany and Russia is
expected to continue. FIRE welcomes the collaboration with other
programs and other countries in its quest to better understand the roles
of clouds in the Earth\'s climate system.

**1. INTRODUCTION**

In humankind\'s continuing quest to better understand and adapt to the
environment around us, questions concerning global warming and
anthropogenic influences on the environment have become more prominent
in the past decade. Many of the effects of human activity on the
environment are cumulative and have long-lasting consequences; therefore
considerable urgency has arisen to better understand the complex
relationships that exist among the many forces governing the earth\'s
climate system, and to apply this understanding to mitigate and adapt to
both natural and anthropogenically forced climate variations. FIRE (the
First ISCCP Regional Experiment; ISCCP is the International Satellite
Cloud Climatology Project) was first organized by a group of atmospheric
scientists and federal agencies in 1984 to address one of the most
fundamental of the forcing variables of the climate system - Clouds and
Radiation.

That cloud systems play crucial roles in the earth\'s climate system is
universally accepted. The complexity of these roles demands a
continuing, methodical, scientific investigation if we are to reach our
goal of being able to understand, simulate and anticipate climate
change. While clouds have become a focal point for much study, it is
important to remember that clouds represent only one component in the
atmosphere\'s water cycle, albeit a very \"visible\" one; a study of
cloud systems and their accurate simulation in climate models must
include the entire water cycle ranging from evaporation at the surface,
to advection of water vapor, to condensation within clouds and finally
precipitation, whether it reaches the ground or not. While all cloud
systems from the robust midlatitude cyclone and cumulonimbus super cell
to tenuous cirrus clouds and seemingly docile stratus are important to
climate studies, some are potentially more important to climate studies
than others because of their pervasive nature, both geographically and
temporally. It is this focused relevance on the climate problem that has
guided FIRE researchers to select specific types of cloud systems for
study.

Because of the complexity and urgency of the cloud-radiation-climate
problem, several strategies have been pursued in parallel: Monitoring,
Modeling and Field Campaigns. ISCCP was designed to provide the first
global monitoring of cloud systems. In spite of its limitations, it has
provided the most complete, objective global cloud census to date.
Modeling of cloud systems has enjoyed dramatic gains over the past two
decades; these models range from simple one and two dimensional
structure models, to complex high resolution three dimensional (3-D)
primitive equation models, to a variety of general circulation and
climate models. At this time one of the largest uncertainties in the
large scale models is their treatment of cloud systems. With our
inability to bring the atmosphere into the laboratory, and with the
inadequate understanding and representation of cloud systems in models,
field campaigns are required to gain understanding and to verify and
improve both our monitoring and modeling capabilities for these systems.
The synergism among these three strategies has proven to be essential
for our progress toward our goals of understanding, mitigating and
adapting to climate variability and change.

This document proposes a strategy for addressing the outstanding
problems in the critically important research area of cloud-climate
relationships. The Research Plan represents a natural extension of
previous FIRE research. It has been drafted with the collaboration of
many FIRE Science Team members, and thus represents the most
contemporary and authoritative thinking about the future direction for
cloud-radiation- climate research. The following sections describe the
research plan for FIRE Phase III.

Section 2 provides a brief historical background of the FIRE program.

Section 3 describes the relationships between past FIRE objectives and
those of the future. The continuity of personnel, resources and mission
are cited as major factors in FIRE\'s achievements. The continued
analysis of FIRE I and II data sets and the development of new
instrumentation are emphasized as important parts of future FIRE
activities as is.

In Section 4, a research plan for the continuing investigation of upper
tropospheric clouds is presented. This plan outlines a methodical
strategy for coupling past and present cirrus cloud studies with the
next phase of FIRE. The emphasis is on continued analysis of previous
FIRE studies, the integration of these results into large scale models
and satellite monitoring systems and the development of new
instrumentation to probe the microphysical and radiative properties of
clouds. The desirability and need for a field campaign into the tropical
latitudes later this decade will be assessed.

Section 5 presents an explicit plan to study Arctic Stratus cloud
systems. Although the analysis of subtropical, marine stratus cloud
systems will continue, Arctic stratus cloud systems have been identified
as a key cloud-climate focus. This plan complements a study of the
Arctic surface energy budget program SHEBA.

Section 6 introduces the management and scientific organization which
will support the FIRE science activities during FIRE III.

**2. HISTORY OF FIRE**

FIRE was conceived as an ISCCP Regional Experiment in 1982. Since its
inception FIRE has been guided by working scientists through interactive
discussion, proposal submission and peer review. Another characteristic
of FIRE is the interdisciplinary mix of scientists. FIRE has become an
interdisciplinary \"melting pot\" bringing together specialists in
microphysics, radiation, instrumentation and modeling, working on a
common set of problems related to cloud-climate issues. In the same
spirit, multiple agencies have worked together and supported FIRE
research programs. This collaborative funding has made it possible to
maintain continuity of purpose and scientific personnel, and has enabled
FIRE to pursue longer term objectives so critical to basic science. At
the same time, the program has benefited from new ideas and personnel
joining the FIRE effort along the way. In light of the demands of longer
term objectives, FIRE has taken very seriously its responsibility to
train young scientists in cloud radiation research. This challenge has
been met with the active participation of graduate students and post
doctoral researchers in FIRE research. It is the aim of the FIRE
scientific community to retain these characteristics of the past which
have proven to be so successful.

FIRE\'s Successes to Date:

*The first serious communication across the microphysical, dynamical,
and radiative science communities for both theoretical modeling and
observations of clouds.*

• The entire community has been greatly enriched and educated. Problems
are being approached from directions not imagined just a few years ago.
FIRE scientists feel as if they are on a race course with many exciting
things to look at and not enough time to do them all. Synergism is
happening now, not five years after publication, when the data are often
too \"cold\" to go back to for molding into the shape needed by the
modeler, or when the expertise critical to proper interpretation of the
data has gone off to work on some other problem.

*FIRE has made significant progress in all of the areas critical to
understanding the roles of clouds in the climate system.*

For example:

• For global observations, FIRE has defined the accuracy of ISCCP cloud
amount, height, and optical depth for many of the earth\'s cloud
systems, especially critical cirrus and boundary layer cloud (1,2,3,4).
FIRE has also shown how to improve the accuracy of cirrus optical depths
and heights, along with stratus heights for the next version of ISCCP
(5,6,7,8). Overall, the conclusion is that ISCCP is more accurate by far
than any current global climate model, and that the ISCCP data can be
used by modelers for critical cloud radiation verification. FIRE has
also demonstrated new capabilities for satellites to remotely sense
cloud particle size and phase. FIRE research has greatly impacted the
spatial resolution and spectral channel selection for the MODIS
(9,10,11,12) instruments: the next generation satellite cloud radiometer
and arguably the first instrument including accurate and stable
calibration designed to quantitatively measure key cloud properties.

• For cloud microphysics and radiation, FIRE has finally opened
Pandora\'s box: what do we do for ice crystal clouds? FIRE uncovered the
importance of small ice crystals for cirrus radiative effects
(13,14,15,16,17), defined a new set of questions to be answered, showed
the great superiority of hexagonal crystal scattering phase functions
over spheres for a wide variety of cirrus cloud cases
(15,18,19,20,21,22,23,24,25,26,27) and independent instrument
measurement tests, and defined the need for new ice particle instruments
and funded their further development. Although FIRE has not answered all
cirrus ice questions, or removed all uncertainties in how to model
cirrus, it has greatly reduced the previous uncertainties. For water
droplet clouds, FIRE has raised new questions about the reproducibility
of FSSP (Forward Scattering Spectrometer Probe) data. At the same time,
new optical probes show promise for determining radiative \"effective
radius\" as well as LWC (Liquid Water Content) (28) and extinction
coefficient. The next phase of FIRE will incorporate both the old (FSSP,
2D) probes and the new particle probes. FIRE has observed and modeled
the effects of CCN concentrations on cloud droplet
populations/distributions and the subsequent effects upon the cloud
radiative properties (29,30,31,32).

• Improved flux radiometers were flown on the ER-2 and Sabreliner
aircraft and were well-matched to radiometers on the ground, providing a
high-quality, full-column description of the radiative fluxes for FIRE
Cirrus-II (33,34,35,36,17,37). At the same time, ground-based active
sensors (both lidar and radar) (38,39,40,41,42,43,44) as well as the
airborne cloud lidar on the ER-2 provided a detailed description of the
cloud location, structure, and ice water profile. Coordination between
the aircraft and ground-based sensors was much improved in comparison to
FIRE Cirrus-I (45,46,47,5,48,49), i.e., greater coincidence. Significant
improvements were also made in capabilities for spectral coverage and
resolution in comparison to FIRE Cirrus-I. New measurements of the
spectral albedo of cirrus clouds were obtained and expanded knowledge of
the spectral-dependence cloud radiative properties is anticipated. There
is strong potential for significant impacts on future satellite-based
cloud observing capabilities

• For cloud dynamics, FIRE has focused on improving cloud scale (such as
LES) and mesoscale cloud models to help scientists better simulate and
understand the dynamics of these systems (50,51,52,53,31,54,55). FIRE
produced the first detailed simulations of stratocumulus break-up.
Through this work, the importance of solar radiation for cloud break-up
has been established. The relevance of cloud-top entrainment instability
has also been clarified, and new criteria for its onset have been
developed. In addition, FIRE has produced the first highly detailed
simulations of the interactions of stratocumulus cloud dynamics, aerosol
physics, cloud microphysics, and radiative transfer. Again, the breadth
of these activities is striking, and their obvious relevance to
understanding the role of clouds in climate is great.

• Real time data from ASTEX were furnished to ECMWF for incorporation
into the operational forecast model (56). Operational and research
forecast models were employed in the field phases for both marine
boundary layer and cirrus layer field campaigns.

• Cloud modeling studies have shown that many of the important physical
processes governing the microphysical development and the vertical
transport of ice depend strongly on the small-scale dynamical
development within cirrus clouds (57,58,59,60). In turn, radiative
processes, that are highly sensitive to the cloud ice mass distribution
including macroscopic organization and internal structure, have been
shown to significantly regulate cloud dynamical development. These
conclusions are supported by the analysis of high-resolution in situ and
active remote sensing observations that show the prevalence of mesoscale
and small-scale organization within cirrus clouds systems.

• For cloud radiation, FIRE has made progress in several critical areas.
Examination of the three dimensional (3-D) nature of boundary layer
clouds has shown that at least over ocean, plane parallel radiative
transfer theory appears to be adequate as long as the frequency
distribution of optical depth is defined. Two unexpected FIRE results
are: that gaussian distributions of cloud optical depth occur only for
overcast conditions (on a 60 km scale) (61); and that many, if not most,
boundary layer clouds over ocean are not \"black\" in the thermal
infrared (62).

Ship tracks have dramatically demonstrated the critical role played by
CCN in clouds and their impact on cloud radiative properties (particle
size and optical depth) (32,63). FIRE measurements show the lack of any
large \"anomalous absorption\" in cloud particles and suggest that the
remaining discrepancies are likely to be found in water vapor absorption
and/or 3-D effects (64). The recent LOWTRAN 7 version predicts just such
an increase in water vapor absorption from far wing line absorption. In
addition, a new cloud nephelometer has been developed at the request of
FIRE. This should provide better determinations of the asymmetry
parameter. New theoretical results and laboratory results are becoming
available for non-spherical particle scattering.

• FIRE GCM result highlights include the following: FIRE data enabled
the development of empirical relationships between cirrus cloud optical
properties and temperature (63); these relationships are suitable either
for direct incorporation into GCMs, or for evaluation of the results
from more advanced models that directly predict both cirrus optical
properties and temperature (65,20). Our improved understanding of the
physics of stratocumulus cloud break-up, in terms of solar warming,
drizzle, and cloud-top entrainment instability, has led to the
development of new parameterizations of the stratocumulus transition
(66,67,68,69). FIRE data are also being used to develop new
semi-empirical parameterizations of cloud amount, that will be directly
incorporated into at least one GCM in the very near future.

In addition, FIRE data has helped to convince climate modelers of the
importance of cloud-aerosol interactions for determining the macroscopic
optical and hydrological properties of the clouds. FIRE GCM results have
shown a dramatic sensitivity of the tropical water vapor distribution to
upper tropospheric clouds; these results will help guide future FIRE
studies of middle and upper tropospheric cloud systems (70).

• FIRE has nurtured the development, deployment and application of
multiple remote sensing systems for observing cloud layer dynamics,
microphysics, thermodynamics and radiative properties. The list is
extensive and will continue to grow, but currently includes, wind
profilers, Doppler- millimeter, infrared and visible - radars/lidars,
radio acoustic sounding systems, interferometers and radiometers. FIRE
can boast many firsts in the initiation and application of these
techniques. Information gleaned from these systems in the future will be
critical in improving our understanding of climatically important cloud
systems.

**3. PAST, PRESENT, AND FUTURE**

The past, present and future FIRE research programs are closely linked.
Continuity of goals, personnel and resources have been key to the many
successes of FIRE. That which was learned in the early phases of FIRE
has been built upon to make further advances in later stages of FIRE.
Working relationships that were forged in FIRE I became increasingly
productive in FIRE II (e.g. between experimentalists and theorists,
between microphysics and radiation specialists, between in situ and
remote sensing advocates, and among aircraft, surface based and
satellite constituencies). This continuity on many different levels
resulted in a much higher efficiency of data utilization and
interdisciplinary communication. Investigations begun as FIRE I produced
results and publications well after FIRE II began and insights gained in
FIRE II have resulted in additional analyses of FIRE I data.

Continuing support for both data analysis and modelling activities based
on Phases I and II and ASTEX is crucial to realize FIRE\'s overall
scientific goals and insure our understanding of climatically important
mid latitude cirrus and marine boundary layer cloud systems. Previous
field campaigns yielded a wealth of information on and insight into how
cloud amount and radiative properties are related to multiple scales of
dynamic forcing, thermodynamic structure, and microphysical processes.
Much of the data analysis for the FIRE II and ASTEX experiments will
continue for the next several years. An especially exciting feature of
FIRE and ASTEX is the integrated nature of the data sets, in which local
and remote sensing observations from surface sites, large scale and
regional scale analyses from forecast models, satellite and aircraft
data are blended. This type of study requires the collaboration of
multiple investigators and typically requires several years to bring the
effort to fruition.

A number of modeling studies are under way for both marine boundary
layer and cirrus cloud systems. Particular thrusts include modelling the
diurnal cycle of mean boundary layer clouds, modelling the transition
between solid stratocumulus and trade- cumulus boundary layers,
modelling cloud/aerosol/drizzle/radiation feedbacks, and understanding
mesoscale variability. Cirrus cloud system modelling studies are aimed
at simulating time and space distributions of ice water, incorporating
distributions of CCN and ice nuclei into models, and determining just
what level of detail about ice crystal shape, size and orientation is
required to specify radiative properties.

FIRE III will benefit from continuity of personnel, instrumentation and
goals with its predecessors, FIRE I and II. An important part of FIRE
III is the continuing analysis of FIRE and ASTEX data sets along with
further exploration of outstanding problems related to midlatitude
cirrus and marine boundary layer cloud systems. It is important to note
the close relationships between the FIRE I and II efforts and those
proposed for FIRE III. FIRE I and II investigations were conducted in
the mid latitudes; interestingly FIRE III, described in the following
sections, extends the scope of FIRE to lower latitude, high altitude
cloud systems (Section 4) and higher latitude, low altitude cloud
systems (Section 5).

The development of instrumentation and techniques to observe key
properties of cloud systems is a high near-term priority of FIRE Phase
III. The inability to observe these properties on the cloud-scale is
currently a barrier to a better understanding of these cloud systems.
Advances in the areas mentioned in Table 3.1 are critical to the future
success of both components of FIRE Phase III - Upper tropospheric cloud
systems and Arctic boundary layer cloud systems.

New Satellite Instrumentation

There will be two major improvements in satellite data which will impact
the plans for the FIRE III time period. First, an improved geostationary
satellite (GOES Next, or GOES-I) has been launched. Second, starting in
1997, the Earth Observing System (EOS) platforms will provide new data
on cloud properties and radiative fluxes. FIRE will be a critical tool
to validate the accuracy of these new data sources. At the same time,
once validated, these data sources will provide key information on
clouds and radiative fluxes for use in global, mesoscale, and cloud
scale modeling efforts in FIRE III. A brief summary of the new
capabilities is given below.

The new GOES satellite provides the spectral channels of both AVHRR and
HIRS at time resolutions as small as 15 minutes. Unlike the previous
GOES, navigation accuracy is expected to be on the order of 1 km, an
order of magnitude improvement. The new GOES will allow substantially
improved cloud property determination at high time resolution for
studies of the time evolution of cloud fields.

New EOS platforms include TRMM (Tropical Rainfall Measurement Mission)
to launch in August 1997, and EOS-AM to follow in June 1998. Instrument
improvements include:

a). TRMM will have a combination of instruments to examine both the
latent heating (precipitation) and radiative heating of the tropics.
TRMM has:

> • PR: Precipitation Radar (PR) to vertically profile rainfall rates,

Table 3.1 - New Instrumentation Needs

+-----------------------------------+-----------------------------------+
| **KEY AREAS**                     | **SPECIFIC NEEDS**                |
+-----------------------------------+-----------------------------------+
| Basic individual particle and     | Laboratory and airborne           |
| volumetric average radiative      | nephelometers                     |
| properties                        |                                   |
|                                   | High spectral and angular         |
|                                   | resolution radiometers            |
|                                   |                                   |
|                                   | New concepts                      |
+-----------------------------------+-----------------------------------+
| Basic radiative flux measurements | Spectral, angular resolving       |
|                                   | instruments                       |
|                                   |                                   |
|                                   | New concepts                      |
+-----------------------------------+-----------------------------------+
| Microphysical properties          | Improve consistency and accuracy  |
|                                   | of particle size and water        |
|                                   | content observations from         |
|                                   | existing instrumentation (FSSP,   |
|                                   | 2D, JW, etc.)                     |
|                                   |                                   |
|                                   | Improve ability to observe shape  |
|                                   | and orientation of non spherical  |
|                                   | particles                         |
|                                   |                                   |
|                                   | Extend observable particle size   |
|                                   | range to both smaller and larger  |
|                                   | sizes                             |
|                                   |                                   |
|                                   | New concepts                      |
+-----------------------------------+-----------------------------------+
| Aerosols                          | Expand CCN, CN aircraft           |
|                                   | observations to include chemical  |
|                                   | composition                       |
|                                   |                                   |
|                                   | Observe Ice Forming Nuclei from   |
|                                   | aircraft                          |
+-----------------------------------+-----------------------------------+
| Chemical Species (includes water  | Real time aircraft sampling       |
| vapor)                            |                                   |
+-----------------------------------+-----------------------------------+
| Continue development and          | Millimeter radar                  |
| exploitation of remote sensing    |                                   |
| systems                           | Interferometry                    |
|                                   |                                   |
|                                   | Lidar applications:               |
|                                   |                                   |
|                                   | > Raman lidar                     |
|                                   | >                                 |
|                                   | > Differential absorption lidar   |
|                                   | > (DIAL)                          |
|                                   | >                                 |
|                                   | > Other - including Doppler and   |
|                                   | > polarization applications       |
|                                   |                                   |
|                                   | Wind profiler applications        |
|                                   |                                   |
|                                   | Multiple, integrated systems      |
|                                   |                                   |
|                                   | New concepts                      |
+-----------------------------------+-----------------------------------+
| Satellite                         | New/improved concepts of data     |
|                                   | utilization/application           |
+-----------------------------------+-----------------------------------+
| Platform development              | Remotely piloted vehicles         |
|                                   |                                   |
|                                   | NCAR WB 57                        |
|                                   |                                   |
|                                   | NOAA Gulfstream IV                |
+-----------------------------------+-----------------------------------+

> • TMI: TRMM Microwave Imager: an improved SSM/I passive microwave
> scanner
>
> • VIRS: Visible and Infrared Scanner: an AVHRR-like scanner with
> onboard visible channel calibration, 2 km field of view, and a new 1.6
> µm spectral channel for particle size/phase determination.
>
> • CERES: Clouds and the Earth\'s Radiant Energy System scanner: an
> improved ERBE scanner for measurement of broadband fluxes with a 10 km
> nadir field of view and improved onboard calibration.

The TRMM investigation will estimate latent heating profiles for the
tropics, while the EOS CERES investigation will use VIRS, CERES, and TMI
to estimate cloud properties in the atmosphere as well as radiative
fluxes at the top of the atmosphere, at the tropopause, at 500 hPa, and
at the surface. Both FIRE and ARM are expected to provide critical
validation data for the CERES cloud and radiation data products.

b). EOS AM is a 1030 am sunsynchronous platform which will include a
suite of instruments useful to FIRE III.

> • MODIS: the Moderate Resolution Imaging Spectrometer is the first
> spaceborne instrument designed with cloud property retrieval as a
> prime objective. This instrument has greatly improved onboard
> calibration (blackbodies, lamps, solar diffuser, lunar viewing,
> spectrometer) as well as improved spatial resolution (0.25 to 1.0 km
> field of view) and improved spectral coverage. Channels include those
> used recently for cloud studies using AVHRR, Landsat, and HIRS, in
> addition to new channels at 1.38 µm for cirrus detection over low
> clouds and at 8.5 µm for thermal infrared particle size determination
> at night.
>
> • CERES: a broadband scanning radiometer identical to that flown on
> TRMM. The CERES investigation will merge the MODIS/CERES data with the
> VIRS/CERES data on TRMM to improve the resolution of the diurnal cycle
> of global cloud and radiation fields.
>
> • MISR: Multi-Angle Imaging Spectro-Radiometer. MISR views the
> spectral solar reflected radiation from 9 angles with a spatial
> resolution of 250 meters over a swath of 300 km. MISR will provide
> global data similar to that FIRE obtains using the new EO camera on
> the ER-2 aircraft. This data is key for studying the effects of cloud
> inhomogeneity, and for providing an independent stereo cloud height
> technique.
>
> • ASTER: Advanced Spaceborne Thermal Emission and Reflection
> Radiometer. ASTER is a Landsat like instrument (15 to 90 meter field
> of view over a 60 km swath) which adds 8.5 and 12 micron spectral
> channels in the thermal infrared. This instrument will provide unique
> data for testing the impact of spatial averaging and sub-pixel cloud
> on the MODIS, VIRS, AVHRR, and GOES derived cloud properties

c\) Additional platforms which may be useful include the Japanese/French
ADEOS II which will be launched in 1996 including an advanced AVHRR-like
scanner (OCTS) and the POLDER (Polarization and Directionality of Earth
Reflectances) which has a 6 km field of view with channels from 0.4 to
0.9 micron. Unfortunately, the current data policy on ADEOS appears to
severely limit any potential access of this data by any FIRE
investigators. Similar issues arise with the use of ERS-1 data from the
ATSR (along-track scanning radiometer) instrument.

It is appropriate to note that many of the objectives of FIRE III
outlined below have much in common with the NASA AEAP/SASS program.
Previous FIRE investigations provide important background data and
knowledge for both FIRE III and NASA AEAP/SASS. Likewise, there are a
substantial number of investigations outlined below that are meaningful
to both programs. This merging of purpose, personnel, instrumentation,
effort and resources will be beneficial to both programs and is welcomed
by the FIRE community.

**4. UPPER TROPOSPHERIC CLOUD SYSTEMS**

A primary objective of FIRE since its inception has been to better
understand upper tropospheric clouds. This understanding is critical to
the inclusion of these clouds and their effects in climate models.
During FIRE I and II these investigations were focused primarily in the
midlatitudes.

4.1. Objectives of FIRE III

To facilitate continued progress toward achieving the overall goals of
FIRE with respect to upper tropospheric cloud systems, FIRE research
will be comprised of the following three primary components during Phase
III:

> *The continued analysis of the wealth of observations obtained during
> the FIRE Cirrus-I and Cirrus-II field campaigns and the FIRE
> extended-time observations.*

Two essential aspects of this activity are the *integration of various
observations* to enable a comprehensive description of the cirrus cloud
systems that were observed and to apply those results in the evaluation
and *improvement of various models* including radiative transfer models,
cloud process models, regional cloud system models, and ultimately
global climate models (GCMs). These are complex tasks, generally
requiring an iterative approach, that are fundamental to advancing
present understanding of upper tropospheric cloud systems.

> *The definition and execution of limited, highly-focused observational
> programs to complement our current understanding of cirrus cloud
> systems.*

A major accomplishment of FIRE has been the development and application
of new instrumentation and associated analysis techniques to observe
important physical properties of cirrus clouds. These advances have been
driven by requirements derived from FIRE research. Attempts to integrate
various observations and incorporate those results in models have
identified critical deficiencies in knowledge and understanding and
served to focus FIRE efforts to address those deficiencies. A program of
highly-focused but limited-in-scope field activities is needed to
support the continued development and testing of new instrumentation and
observing capabilities thereby ensuring the most expeditious progress
toward the goals of FIRE. In addition, such missions would be very
suitable for addressing important outstanding issues related to the
potential role of aerosols in determining cirrus cloud properties and
the impact of subsonic aircraft emissions at cruise altitudes on climate
in concert with the NASA AEAP Subsonic Assessment Program (SASS).

> *The assessment of the need for and subsequent definition and
> execution of a major field campaign focused upon tropical upper
> tropospheric cloud systems.*

Satellite observations and results from global climate models strongly
suggest that tropical upper tropospheric cloud systems play a very
important role in the global climate system. Yet, present knowledge of
these clouds is highly uncertain mostly due to the lack of adequate
observations. It is unknown how different tropical cirrus systems may be
from the mid-latitude cirrus cloud systems that have been the primary
subject of FIRE Phases I and II. Significant improvements in observing
platforms and instrumentation are anticipated in the next few years that
would allow a strong tropical cirrus field experiment. Analysis of the
limited observations obtained during the FIRE Pilot Tropical Cirrus
Experiment conducted during TOGA-COARE and the Central Equatorial
Pacific Experiment (CEPEX) will likely enable a more quantitative
evaluation of the need for a major tropical field campaign on cirrus
clouds and help hone the process of defining and designing such a
campaign. The present consensus view of the community is that a
well-designed major field campaign directed at tropical upper
tropospheric cloud systems would provide very significant scientific
benefit.

The following objectives are adopted for FIRE Phase III and constitute a
specific framework to guide the aforementioned primary areas of
activity:

> OBJECTIVE 1: Apply FIRE Phase I and II process model and field
> campaign results to the improvement and verification of cirrus cloud
> system parameterizations employed in limited-area eddy simulation
> (LES) models and global climate models (GCMs).
>
> OBJECTIVE 2: Apply FIRE Phase I and II field campaign and theoretical
> results to develop and verify improved techniques for the inference of
> cirrus cloud presence and radiative as well as microphysical
> properties from satellite data.
>
> OBJECTIVE 3: Define the total water substance (vapor, liquid and ice)
> environment and transports associated with upper tropospheric cloud
> systems.
>
> OBJECTIVE 4: Define, design, test and implement measurement systems to
> observe key microphysical and radiative properties of cirrus clouds
> and cirrus cloud systems.
>
> OBJECTIVE 5: Advance our understanding of cirrus cloud systems, the
> variability of their microphysical and radiative properties, the key
> elements in their formation and dissipation, and their roles in
> partitioning energy between the surface and the atmosphere.
>
> OBJECTIVE 6: Provide a methodical transition from FIRE Phase I and II
> accomplishments to a coherent research plan for the next generation of
> research on upper tropospheric cloud systems.

4.2. Critical Scientific Questions to be Addressed

A number of key scientific questions must be addressed by FIRE Phase III
research on upper tropospheric cloud systems if the above objectives are
to be achieved. For the most part, the issues are similar to the
scientific questions addressed during FIRE Phases I and II. FIRE Phase I
was, of necessity, an exploratory endeavor. Many deficiencies in basic
understanding and observing capability were identified as the
observations of cirrus cloud properties were analyzed and modeled and a
truer picture of the nature of cirrus clouds evolved. These findings
guided the design of Phase II, including the development of various new
instruments to make the required measurements. Analysis of the data
collected during FIRE Phase II is well-underway. However, the more
complex integrated analyses (multi-parameter) are at an early stage.
Preliminary LES model simulations of the observed cloud systems have
been completed but the iterative process of model validation and
improvement is still in the early stages. Based on the accomplishments
and results from FIRE Phases I and II, the issues and needs are now
better defined. In particular, specific requirements for additional
observing capability have been clearly identified. In addition as noted
previously, FIRE Phase III is very concerned with the nature and role of
tropical upper tropospheric cloud systems. This is a new thrust for FIRE
and has the potential for significant advancement in an area that is
likely to be of great importance to the global climate system. Critical
scientific questions and issues to be addressed by FIRE Phase III
research on upper tropospheric cloud systems are introduced below:

*1. What are the distributions and amounts of ice mass and total water
in the upper troposphere?*

Related issues:

> • How does the ice mass and its distribution depend on large-scale
> meteorological parameters such as temperature, vertical motion, wind
> shear, etc.?
>
> • How is ice mass distribution related to detrainment from deep
> convective cloud systems?
>
> • How does the local and regional evolutions of the cloud ice mass
> distribution and variability depend on the formation process (e.g.,
> synoptic ascent versus convective detrainment)?
>
> • How may ice mass be determined from remote sensors (satellite,
> airborne and/or surface- based) and how can these measurements be
> validated?

Knowledge of the distribution of ice mass in the upper troposphere is
absolutely essential for validation of GCMs. The prognostic cloud
schemes developed for current GCMs predict the vertically integrated
cloud ice water path (IWP) on the basis of uncertain microphysical
parameterizations and can be significantly affected by errors in the
predicted large-scale convergence of water vapor and convective
transports (70). Even the assignment of phase within the cloud,
crucially important to the proper diagnosis of cloud radiative
properties, is highly uncertain for cloud temperatures between 0 and
-40oC. The climatic states determined by these models are highly
sensitive to these uncertainties (71). Recent observations of the global
distribution of vertically integrated liquid water path over oceanic
regions and satellite passive microwave observations (72,73,74,75) will
lead to significant improvements in the models. Unfortunately, there are
no analogous large-scale data sets with which to validate model
predictions of IWP.

While new methods for the remote sensing of ice water content are under
development (76), additional in situ data and sampling strategies will
be required to validate these emerging techniques. Such observations are
crucial for quantitatively determining the factors that control the
distribution of ice water content and its evolution.

*2. What are the microphysical properties of upper tropospheric clouds?*

Related issues:

> • Are there relationships between the particle size, shape, number
> concentration, and phase and the large-scale environment?
>
> • How does microphysical composition affect the evolution of the cloud
> system and the tropospheric water budget (interactions between cloud
> layers, vertical water transports, precipitation at the surface)?
>
> • What are the microphysics of cirrus formed at extremely low
> temperatures?
>
> • How do aerosols impact the microphysical development of cirrus
> clouds?

Aside from their radiative effects which are discussed below, cirrus
microphysical properties are important to the overall water budget of
the upper troposphere and to the large-scale evolution and lifetime of
cirrus systems. The existing cloud particle size spectra determines both
the cloud water fallout rate (vertical transport) and the evaporation
rate of water at cloud edges.

Since cirrus ice particles occur with a variety of crystal shapes having
different terminal velocities, it is important to know how to predict
crystal habit as a function of large-scale environmental parameters
(57,58). The local dynamical environment may play a significant role in
determining cloud microphysical properties. Analysis of FIRE and other
observations (39) (e.g., ICE) indicate that the presence of buoyancy
(gravity) waves (77), quasi two-dimensional mesoscale eddies and the
development of convective circulations are each likely to have a
pronounced effect on cloud microphysical development.

Besides the direct effect on the upper tropospheric water budget and
cloud ice mass, ice fallout from cirrus clouds may also act to enhance
precipitation formation in underlying clouds via ice phase accretion or
glaciation of supercooled liquid water by the seeder-feeder process,
especially when the upper troposphere clouds are vertically extensive.
Since the relative amounts of ice phase and liquid phase clouds may
change in a changing climate, it is crucial to understand the
microphysical distinctions between cirrus and altostratus or altocumulus
clouds that form under similar large-scale dynamical and thermodynamic
conditions (57,78). To the extent that liquid and ice phase upper
tropospheric clouds have different lifetimes and different radiative
properties, the liquid-ice transition has direct implications for
cloud-climate feedback (79,80). Although temperature is a major factor
determining the liquid-ice transition, other factors are also likely to
be important given the lack of a clear demarcation in the available
observations.

There is also a hint that cirrus crystal precipitation and subsequent
evaporation may play an important role in determining the water mass
distribution of the upper troposphere. The evaporation of cirrus
crystals may prove to be the dominant source of humidification for some
intermediate upper tropospheric levels.

Because of the multiplicity of paths by which ice can form in clouds
(deposition, freezing, diffusional growth, rimming), it is also
important to know whether relative humidity should be assessed using the
reference of saturation with respect to the liquid phase, ice phase, or
an intermediate value, in regions where liquid, ice and mixed-phase
clouds can all exist (0 to -40oC).

The microphysical properties of ice crystals are essentially unknown at
temperatures lower than -65oC (19,20). These properties must be
documented in order to understand (79,80,81) the evolution and apparent
ubiquitous nature of very thin cirrus near the tropical tropopause. A
persistent and extensive veil of thin tropical cirrus was observed in
earlier tropical experiments, BOMEX (1969), GATE (1974) and most
recently throughout most missions during the FIRE Pilot Tropical Cirrus
Experiment. The potential effects of a ubiquitous thin cirrus layer on
satellite-based remote sensing and on the maintenance of upper
tropospheric thermal and moisture structures in the tropics could be
very significant.

The role of aerosols in cirrus development is poorly understood; there
is a basic need to understand the distinction between cirrus fed by
ocean-derived aerosols pumped into the upper troposphere by convection
or large-scale ascent, cirrus affected by aerosols derived from
continental or industrial sources, and cirrus affected by stratospheric
aerosols as a result of tropopause penetration or
stratosphere-troposphere mixing. Observations from FIRE Cirrus-II
indicate that incorporation of aerosols of stratospheric (volcanic)
origin may have a dramatic effect on cloud microphysical properties
(82), while model simulations using the best current nucleation schemes
show a much less dramatic effect (53).

Resolution of questions about the potential magnitude of aerosol effects
and consequently an assessment of the detail required in the
microphysical treatments used in models is a key focus for FIRE Phase
III. In addition, an assessment of the potential microphysical effects
of aerosols will strongly support efforts to assess the climatic effects
of atmospheric emissions by subsonic aircraft that is presently a major
concern (NASA AEAP/SASS).

*3. What are the radiative properties of upper tropospheric clouds and
how do they relate to the ice mass, microphysical and macrophysical
characteristics of the cloud?*

Related Issues:

> • What are the scattering phase functions, asymmetry parameters, and
> optical extinctions associated with the microphysical distributions?
>
> • How may these radiative properties be directly and accurately
> observed from airborne, satellite and surface-based platforms?
>
> • To what extent can these radiative properties be usefully expressed
> in terms of an effective particle size that is consistent with cloud
> ice path and optical depth?
>
> • How do the vertical and horizontal macrostructure of cirrus clouds
> affect their bulk radiative properties and how does this impact the
> remote sensing of cloud microphysical properties?

Although substantial progress has been made during FIRE Phase I and II,
the relationship between the optical properties of ice clouds and their
microphysical properties is still not well-understood
(15,18,19,20,21,22,23,24,25,26,27). Modeling studies have shown how the
effects of scattering by non-spherical particles significantly impact
the distribution of radiance and, hence, the remote sensing (passive or
active) of cirrus properties based on observed radiances. The recent
revision of the ISCCP algorithm for ice phase clouds is a application of
what has been learned from FIRE. The present lack of understanding is
largely a consequence of the continued lack of definitive quantitative
knowledge of the fundamental scattering properties of highly irregular
ice crystals. This is a complex issue requiring a high degree of
interaction between theorists and observationalists. There has been
significant progress in developing and applying theoretical methods to
treat scattering by intricately shaped larger ice crystals
(21,22,23,24). However these methods are not very appropriate for the
smaller ice crystals that have now been observed. Instrumentation has
also been developed to enable a more sophisticated inference of cirrus
scattering properties than was previously possible (45). Nonetheless,
continued effort must be made to develop methods to measure these
properties using both in situ (airborne) and remote sensing techniques.

Instrumentation that provides direct measurements of ice crystal
extinction, asymmetry factor, scattering phase function and single
scattering albedo are urgently needed. Unless these observations are
obtained by the most direct means possible, the present uncertainties
are unlikely to be resolved.

It is not clear, how detailed a knowledge of these cloud optical
properties is needed to determine broadband flux distributions in ice
clouds. For example, for the purposes of cloud process models, cloud
system models (LES) and GCMs, it may be adequate to treat scattering in
cirrus clouds using a simple asymmetry parameter rather than fully
incorporating the detailed scattering phase function. On the other hand,
satellite monitoring of clouds and their microphysical properties, and
the earth\'s radiation budget will likely require a more exacting
treatment of radiative transfer. Although perhaps not essential for all
applications, the fundamental intrinsic radiative properties of clouds
should be observed. From a knowledge of these basic properties,
simplification may be sought for specific application (e.g. dynamic
modeling, remote sensing, etc.).

*4. How representative are midlatitude continental cirrus of upper
tropospheric clouds in other regions of the globe?*

The cirrus cloud systems observed during FIRE Cirrus-I and Cirrus-II
were primarily associated with synoptic-scale baroclinic wave
disturbances and jet stream circulations in midlatitude continental
locations. Cloud formation resulted from the forced ascent of relatively
moist air within these midlatitude circulations. The sources of moisture
and aerosols for these cloud systems were often remote (83). Cases were
observed during FIRE Cirrus-II where convective injection of moisture
into the middle and upper troposphere over the eastern subtropical
Pacific Ocean and subsequent incorporation into the observed midlatitude
cloud systems via transport by the subtropical jet stream (84). Other
cases were also observed where midlatitude cyclones, in some instances
containing vigorous deep convection, played a major role in pumping
moisture to upper levels. Cycling of upper tropospheric moisture through
a succession of cirrus cloud systems as the air moved through a series
of synoptic-scale regions of ascent (and descent) was also observed
(85,86).

The moisture and aerosol sources for tropical cirrus, on the other hand,
is primarily the vertical transport and detrainment associated with the
mesoscale convective cloud clusters that define the rising branches of
the Hadley and Walker circulations within the tropics. Indeed, many of
the tropical cirrus cloud systems are a direct result of convective
transport whether being actively fed by detrainment from deep
precipitating convective cloud systems (precipitating mesoscale anvil
systems) or aged anvils that are no longer attached to an active
convective source. The lifetimes of the optically thick mesoscale cirrus
anvil systems are greatly prolonged by the local dynamic response to the
associated diabatic heating, i.e., generation of a mesoscale updraft in
the upper troposphere. Tropical cirrus cloud systems are also generated
in the absence of a local convective moisture source in apparent
response to large-scale dynamical forcing. Large-scale dynamical
processes also appear to play a significant role in the evolution of
mesoscale anvil systems in some cases. A pervasive and a very extensive
layer of optically thin cirrus (87) has been observed at very cold
temperatures near the tropical tropopause during previous programs
dating back as far as 1969. Although the nature of this ubiquitous cloud
layer is not understood, it is likely that its moisture was of
convective origin, as in other tropical cirrus.

From the global modeling stand point, it is crucial to know if the
dynamical environments in which different types of cirrus occur result
in qualitatively distinct modes of microphysical and radiative behavior,
including structural heterogeneity, or whether different cirrus types
can be represented using a single universal cirrus parameterization
applied to different regions of parameter space (67). There may also be
important distinctions based on the source and history of the air in
which the clouds form. For example, convectively-generated cirrus anvils
may initially have a different microphysical composition due to the
known land-ocean differences in convective updraft velocities.
Similarly, air that has been lifted relatively slowly to the upper
troposphere via large-scale synoptic processes, and possible a
succession of condensation/evaporation cycles, will likely have a
different aerosol makeup than air that was rapidly injected via deep
convection.

4.3. Research Strategy

The research products of FIRE (scientific results, models, data,
analysis products, and observing capabilities) can be utilized to
improve monitoring of global cloudiness and radiation and to improve the
treatment of upper tropospheric clouds in global climate models. It is
essential that the critical scientific questions be addressed in the
context of these applications. Immediate improvements can be made based
upon the results of FIRE Phase I and FIRE Phase II, such as the recent
improvement in the operational ISCCP algorithm for retrieval of upper
tropospheric cloudiness parameters and its subsequent utilization for
evaluation of GCM simulations. However, as evidenced by the critical
scientific questions posed in Section 4.2, much remains to be
accomplished. To most effectively utilize the available resources to
address these issues and, ultimately, to evolve a more complete and
accurate understanding of the role of upper tropospheric cloud systems
in a changing global climate system, a comprehensive research strategy
is required. FIRE Phase III research will be comprised of the following
three components:

> *1). The continued analysis of the wealth of observations obtained
> during the FIRE Cirrus-I and Cirrus-II field campaigns and the FIRE
> extended-time observations.*
>
> *2). The definition and execution of limited, highly-focused
> observational programs to complement our current understanding of
> cirrus cloud systems.*
>
> *3). The assessment of the need for and subsequent definition and
> execution of a major field campaign focused upon tropical upper
> tropospheric cloud systems.*

Development and application of new measurement technologies and analysis
techniques are integral components of activities (2) and (3). Addressing
the scientific issues identified herein definitely requires continued
advances in instrumentation and the acquisition and analysis of data
that could not be obtained using the available capabilities at the time
of FIRE Cirrus-II.

The FIRE Cirrus-I and Cirrus-II intensive field observations (IFO) data
sets, the FIRE Pilot Tropical Cirrus Experiment data, and the FIRE
extended-time observations (ETO) are continuing to be developed with
state-of-the-art technology and analysis methods. Perhaps their greatest
untapped scientific value resides in the integration of the results from
multiple sensors and platforms. This process of integrating the
observations and applying them in various studies, especially for model
evaluation and improvement, is a complex process generally involving an
iterative approach. This endeavor is presently in its initial stages.
Consequently, FIRE Phase III will promote the continued analysis of the
IFO and ETO data sets in order to derive their full benefit and maximize
progress toward the goals of FIRE.

*What are the distributions and amounts of ice mass and total water in
the upper troposphere?*

The distribution of ice mass in the troposphere has an important effect
on the transfer of energy within the Earth-atmosphere system, primarily
through its effects on radiative processes. The effects of the
associated latent heat release are also significant. Ice processes in
the upper troposphere play a significant role in regulating the upper
tropospheric water budget with additional consequential radiative
implications (71,88).

While the emphasis of FIRE III is on ice phase clouds, the four
dimensional distribution of total water substance in the upper
troposphere is critical to understanding cirrus cloud systems - their
evolution, their microphysics and their radiative impacts (89,90).
Satellite (91,92,93) and some in situ instrumentation are currently
yielding initial data on upper tropospheric water vapor and liquid
distributions; observation of ice mass distribution is more problematic.
Several studies have investigated the distributions of water vapor mass
(89,94,75) and solid/liquid mass (72) but they have been few in number
and somewhat restricted by instrumentation and technique limitations.

A first order approach to the description of ice mass distribution is a
description of the time-dependent horizontal and vertical distributions
of upper tropospheric cloud amount. The ISCCP is presently generating a
global cloudiness description that is consistent with the level of
sophistication typically employed in GCMs over the last decade, i.e.,
interactive diagnosis of cloud amount. However, as GCMs evolve to
include more complete representations of the global hydrologic cycle and
cloud processes, a more definitive description of the ice mass
distribution is now required. Explicit prognostic treatment of cloud
water and cloud ice are now being developed and applied. It is essential
that such developments be guided by observations. *At a minimum, a
description of the horizontal distribution of vertically integrated ice
water path is urgently needed.* Knowledge of the vertical distribution
of ice water content (IWC) is also very important as is some
quantitative understanding of the variability of ice mass within typical
GCM grid volumes (subgrid-scale variability).

At present, satellite-based remote sensing of ice mass distribution is
limited by the observations available from which to develop techniques
to infer IWP from diagnosed cloud radiative properties, such as optical
depth, and cloud temperature. Such techniques are under development
(95). They rely on the physical correspondence between optical depth and
IWP, which is likely to be significantly better than that found between
precipitation rate and satellite-observed visible and infrared
radiances. Efforts are also underway to develop new capabilities for
airborne and satellite-based, short-wavelength cloud radar observations,
where the physical correspondence between the observed microwave
radiances and IWC (or IWP) is much stronger (see next section) (76).

Analyses of FIRE data, especially integrated
multiparameter/multiplatform analyses, will provide the essential
observational foundation to provide a more complete description of the
distribution of cloud fraction and IWP, as well as supporting
development of additional observing capabilities.

FIRE observations were taken by surface-based, airborne, and
satellite-based sensors. Data from active sensors, such as lidar and
radar, can detail the vertical structure and temporal evolution of the
cloud field. A key aspect of the FIRE Cirrus-II data is the availability
of coincident observations at multiple wavelengths, ranging from the
ultra-violet (Raman lidar) through the visible (polarization lidar) to
the infrared (Doppler CO2-lidar) and microwave (3-mm and Doppler 8.6-mm
radar) portions of the spectrum. While the data obtained at longer
wavelengths (radar) are dominated by the interactions with the larger
cloud particles, the response of the shorter wavelength sensors (lidars)
is more strongly influenced by the smaller cloud particles and
structural aspects of the larger crystals (particle habit). For example,
noticeable discrepancies have been found in the cloud boundaries derived
from simultaneous observations of the same target cloud by different
surface-based active sensing systems (44), even for cloud-base height.
Comparative studies using FIRE data are leading to a greatly improved
understanding of the correspondence between the observed signals and
cloud physical properties. New processing techniques are being developed
that objectively derive the altitudes of cloud top and base for all of
the layers of clouds passing overhead (44) as well as the vertical
distribution of IWC and IWP in the column (42,96).

Data from airborne lidar and radiometers are also available. Lidar
observations provide a measure of horizontal and vertical cloud
structure along the flight path. The passive radiometric observations,
though similar to satellite-based observations, have much finer spatial
resolution and greater spectral coverage enabling the application of
more advanced methods to derive cloud field parameters. The available
satellite observations provide the broader spatial and temporal coverage
that will be required for integration with the meteorological analyses
and cloud system modeling efforts.

A significant number of in situ (airborne) observations of ice particle
size spectra were also obtained (97,14). Analyses of these in situ
microphysical measurements, primarily from particle spectrometer probes,
currently provide the best \"cloud-truth\" estimates of the distribution
of IWC, as well as an obvious determination of cloud presence. *It is
essential that in situ microphysical data taken during FIRE and related
projects be processed as soon as possible using consistent data analysis
methods.* While the in situ data may be directly compared to satellite
observations, they are more effectively matched with the
higher-resolution and vertically-resolved radar, lidar and
interferometer data. These data, individually or in combination, may be
related to IWC and then can be used as the basis for development and
evaluation of methods for retrieving IWP from the available satellite
observations. Joint analyses using the combined data sets are very
strongly encouraged.

Improvements in present methods for deriving cloud distributions from
satellite observations come from a variety of theoretical and multiple
sensor studies (98,99,100,101,102). Results from these studies can be
directly used to further validate the ISCCP retrievals of cloud amount
and cloud height and thereby improve the utility of these global data
for comparison with GCM results (103,104). Development of methods to
provide a more complete cloud field description from satellite data,
especially methods for estimating cloud-base height and multilayered
cloud structure, (105,106) should be vigorously pursued because of the
strong influence on tropospheric radiative flux divergence and surface
radiative budget. While cloud base is difficult to estimate from passive
systems, some headway has been made in this area during FIRE (107,108).
In addition, new techniques are under development to provide a means for
detecting multilayered cloud structure in some cases (48). Analysis of
long term (ETO) data sets (surface-based lidar and radiometers) are
essential for the compilation of climatologically significant statistics
on cloud type, height, thickness and heterogeneity.

The dependence of upper tropospheric ice mass on meteorological
conditions must be assessed through comparative studies using regional
meteorological analyses derived from the extensive FIRE Cirrus-II
rawinsonde and wind profiler data sets and high-quality regional cloud
field analyses derived from the corresponding satellite observations
(109). The meteorological analyses include conventional analyses as well
as state-of-the-art data assimilation using a mesoscale-resolution,
isentropic model (110). Diagnostic calculations of cloudiness and cloud
IWP obtained through the application of various current and
newly-developed GCM cirrus cloud parameterizations, analyzed
meteorological fields, and comparisons with independent measures of
cloudiness and IWP will provide a quantitative basis for evaluating the
applicability of these models and guide future improvements.

Regional cloud-system modeling approaches (53,51,52) will also be used
to investigate the time-dependent distribution of ice mass and cloud
amount and their relationships to environmental conditions for selected
well-observed FIRE Cirrus-II cases. These efforts are highly
developmental and will be strongly coupled to the comparative analysis
efforts. Again, the availability of high-quality, multiparameter,
regional, cloud-field analyses derived from the satellite observations
is crucial. These LES models operate at much finer horizontal and
vertical resolution than GCMs and may be configured for nested grids.
These grids may telescope from a coarse outer-boundary grid (roughly
comparable that of operational limited-area forecast models) to an
intermediate cloud-system resolving grid, to an inner grid approaching
the fine scale of a cloud-process model. These models allow explicit
resolution of mesoscale fixtures and have recently incorporated
sophisticated experimental parameterizations of microphysical processes,
including nucleation. *Cloud system models provide the most logical and
straightforward means to bridge the tremendous scale gap between
observations and GCMs.* They are well-suited as a test bed for
development and evaluation of parameterizations for eventual inclusion
into GCMs (69).

Cloud modeling studies have shown that many of the important physical
processes governing microphysical development and the vertical transport
of ice depend strongly on the small-scale dynamical development within
cirrus clouds (30,58,59,60,111,112,113). Continued efforts using
ultra-high-resolution cloud-process models, in conjunction with analysis
of high-resolution observations, to understand the nature of cloud
physical processes and their relationship to local environmental
conditions will provide the understanding necessary to guide development
of cloud-process modules for inclusion in the regional models noted
above.

The nature, causes, and effects of subgrid scale variability is a
fundamental concern for modeling cirrus clouds at any scale, especially
at the larger scales in GCMs. Progress can only be assured through a
vigorous and integrated effort to model cirrus clouds over the entire
range of scales known to be important to cirrus cloud development where,
at each scale, the modeling efforts are evaluated with and guided by
appropriate observations.

Initial consideration of tropical upper tropospheric cloud systems will
rely on the analysis of data obtained in previous campaigns such as the
FIRE Pilot Tropical Cirrus Experiment during TOGA-COARE and CEPEX (114).
These studies will utilize satellite and airborne remote sensing data,
including airborne lidar, a limited sample of microphysical observations
(one aircraft generally at a single flight level in the lower part of
the cirrus cloud layer) and more limited satellite observations (GMS
rather than GOES). These data will enable some quantification of the
characteristics of convectively-spawned anvil-cirrus formations and the
subsequent evolution of these extensive upper tropospheric cloud
systems. Comparison to FIRE observations of midlatitude cirrus clouds,
generally forced by synoptic scale uplift, will provide some measure of
the dependence of ice mass distribution characteristics on the cloud
formation process and environmental conditions.

*What are the microphysical properties of upper tropospheric clouds?*

The size distribution and shapes of the ice crystals comprising a cirrus
cloud have a strong influence on the radiative scattering properties of
the cloud. Thus, the details of microphysical composition strongly
influence the remote sensing of the cloud properties and help determine
the cloud bulk radiative properties. Unraveling these dependencies is
one of the more formidable challenges to FIRE. As discussed in Section
4.2, microphysical composition also plays a major role in controlling
the cloud water budget and vertical structure through the effects of
particle sedimentation (fallout) (58,115,116). This, in turn, has a
dramatic effect on the bulk radiative properties, the associated
distribution of radiative heating, and the climate role of upper
tropospheric clouds. The possibility of ice, liquid, or mixed phase
conditions (co-existing crystals and supercooled cloud drops) at
temperatures between 0oC and about -40oC further complicates the
situation (79,80,117,118). As noted previously, establishing the factors
controlling cloud phase in this temperature regime is a very important
issue for FIRE Phase III.

Extensive measurements of the cloud particle size distribution have been
acquired during previous FIRE field campaigns via in situ sampling using
particle spectrometer probes. A significant sample of particle impactor
and particle replicator data (new instruments) was also obtained during
the FIRE Cirrus-II and FIRE Pilot Tropical Cirrus Experiment field
campaigns (114). It provides a measure of the number density of small
ice crystals and a much more definitive and detailed characterization of
the shapes of ice crystals. Similar high quality in situ data will also
be available from other programs such as CEPEX and ARM. Integrated
analysis of all the in situ microphysical data will provide a
characterization of the microphysical properties of the observed upper
tropospheric clouds. Procedures for quantitative analysis of the
impactor and replicator data are not completely mature and are still
very labor intensive. However, integration of these data into the
analysis of the data from spectrometer probes producing a consistent,
more complete and accurate microphysical description is highly
desirable.

Because of the limited spatial and temporal sampling, in situ data are
most suited to studies of individual clouds and cloud physical
processes. Extension of these descriptions to the spatial and temporal
scales required to address questions of relationships to large-scale
controls and the upper tropospheric water budget (cloud systems scale)
will require broader scale characterizations derived from satellite and
other remote sensing observations (18,118,119,120,121,122,123). However,
the in situ data are essential for the development and validation of
such techniques.

Comparisons of in situ data with the coincident observations obtained by
ground-based active and passive sensors will be invaluable for the
development of emerging techniques to retrieve particle phase (117), ice
particle effective size (96), and ice crystal habit (117,124,125).
Experimental methods to derive effective particle size in the vicinity
of cloud top based on passive radiometric observations from satellites
(126,127) and overflying aircraft also require coincident in situ
measurements to support further development and validation of the
techniques. To the extent that inferences of cloud microphysical
composition from active and passive radiometric observations can be
validated, these methods would enable a broader scale characterization
of cloud microphysical properties than is possible based on the
available in situ data observations. Such a capability is essential for
understanding relationships between cirrus cloud microphysics and the
larger scale environmental conditions.

For consideration of the evolution of ice mass distributions, definition
of the dependency of cirrus cloud microphysical composition on
environmental conditions and an assessment of their effects on the
evolution of cirrus cloud systems will require an integrated approach of
analysis and modeling over a broad range of scales (Section 4.3.1.1). In
fact, the ice particle size and habit distributions are integral
components of the ice mass balance problem. Model simulations of the
upper tropospheric ice mass budget are strongly determined by the
treatment of cloud phase and ice crystal size distribution and habit.

Ambient temperature is known to strongly influence cirrus cloud particle
size distribution and habit (128,129). However, the dynamical conditions
(stratiform versus convective or turbulent) are also significant factors
controlling particle habit and microphysical variability (30,113). This
indicates the likely importance of thermal stratification (static
stability) and vertical shear of the wind in determining cloud
microphysical composition. The strength of the large-scale vertical
motion may not be as important as the strength of embedded mesoscale
circulations, convection and buoyancy wave activity in determining ice
crystal size and habit distributions. A relationship between large-scale
control and cloud response is further complicated by the significant
effects of cloud processes (especially radiative processes) on the local
stratification and cloud dynamical development (57,58) and possibly on
the microphysical growth with clouds (17,130). Thus, a quantitative
understanding of the processes operating at the small and intermediate
scales will be needed to establish the factors determining cloud
microphysical composition. Analysis of FIRE observations strongly
coupled with efforts to model the physical processes at the cloud
system, cloud process, and microphysical scales will be key to achieving
the required understanding.

Until recently the impact of aerosols on ice-cloud microphysics, while
recognized as potentially important, was very poorly understood due to
the almost total lack of suitable observations. The limited aerosol
measurements obtained during FIRE Cirrus-II and the FIRE Pilot Tropical
Cirrus Experiment provide an opportunity to begin to assess this impact.
These aerosol data were obtained with coincident in situ measurements of
ice crystal size distribution and habit. Considerable variations in
aerosol loading were encountered during these experiments, including
dramatic changes in the concentration of upper tropospheric aerosols of
volcanic origin via stratosphere-troposphere exchange, differences
(131,132,133,134) in air mass history, and tropical maritime versus
midlatitude continental environments. This wide dynamic range provides a
good basis for initial empirical studies of aerosols effects in FIRE
Phase III. However, it is very likely that more comprehensive
measurements with improved instrumentation will be required for a
definitive assessment (Section 4.4). In conjunction with analysis of the
available observations, theoretical studies to assess the effects of
aerosol population (number, size distribution and composition) on ice
crystal nucleation and microphysical development are also strongly
encouraged.

*What are the radiative properties of upper tropospheric clouds and how
do they relate to the ice mass, microphysical and macrophysical
characteristics?*

One of the fundamental foci of FIRE Cirrus field campaigns was the
measurement of cloud optical properties and the solar and infrared
fluxes above, below, and within cirrus clouds. As noted previously,
techniques for direct observation of the most fundamental cloud optical
properties were not available. Thus, assumptions were required both in
the algorithms used to infer cloud optical properties from various
observations and in the models used to calculate the radiative fluxes
associated with those properties for comparison with the flux
observations. Numerous studies of cirrus cloud optical properties and
radiative transfer based on these data sets have been published (32, 33,
34, 35, 46, 47, 64, 106, 109, 130, 135, 136, 137, 138, 139). The studies
from FIRE Cirrus-I indicated significant discrepancies between the
measured optical properties and the associated radiative fields. For
example, cirrus clouds were found to be considerably brighter in the
visible (wavelengths) than expected.

It has been hypothesized that these discrepancies might be attributed to
the presence of relatively large concentrations (\~1000-1) of small
(\~10 µm) ice crystals that were not observable with the in situ
measurement capabilities at the time and, thus, were not taken into
account (16). There was substantial evidence that the asymmetry factor
incorporated in the radiative models used for the comparative
calculations needed to be much smaller than had been previously assumed
(17). Another explanation invoked the concept that a relatively large
irregularly-shaped ice crystal may effectively act as a cluster of much
smaller crystals (15) when considering the scattering of radiation. The
available observations derived from the FIRE Cirrus-I field measurements
and from laboratory studies were not adequate to resolve the
discrepancies. Developing techniques for explicit calculation of the
scattering of solar radiation by single ice crystals of complex shape
had not been implemented and acceptable methods for calculating the
scattering of infrared radiation by small ice crystals had not been
developed.

Following specification of the intrinsic radiative properties of clouds,
one must be able to incorporate these properties into a radiative
transfer model to produce useful, reliable energy fluxes. The number of
investigators working on these problems continues to grow. New
techniques capable of accounting for both the microphysical and
macrophysical complexities of cirrus cloud systems are being developed
(4, 15, 24, 140, 141, 142, 143, 144, 145, 146, 148, 149, 150, 151). New
instruments and modified observational strategies were employed in FIRE
Cirrus-II (125), and later in the FIRE Pilot Tropical Cirrus Experiment
and CEPEX, to address these issues (98, 99). In particular, an effective
means to directly measure (in situ) the number concentration of small
ice crystals (7 to 50 µm) was developed and great improvements were made
in existing capabilities to document ice crystal habit. The number of
small particles required to bring the optical properties and radiative
observations into agreement were not found in the in situ data although
both passive and active remote sensing techniques still implied the
presence of these small particles. On the other hand, the new
microphysical instrumentation provided clear indications of the
complexity of shapes and sizes of ice crystals in cirrus clouds. Of
particular importance is the clear evidence that cloud microphysical
properties (crystal sizes and habit) have a strong vertical dependence
within a typical cirrus cloud. As a consequence, efforts to match
radiative and microphysical observations may vary considerably when
considering the upwelling radiation above cloud top and the downwelling
radiation below cloud base.

Improved flux radiometers were flown on aircraft and were well-matched
to radiometers on the ground, providing a high-quality full-column
description of the radiative fluxes for FIRE Cirrus-II. At the same
time, ground-based active sensors (both lidar and radar) as well as the
airborne cloud lidar on the ER-2 provided a detailed description of the
cloud location, structure, and ice water profile. Coordination between
the aircraft and ground-based sensors was much improved in comparison to
FIRE Cirrus-I, i.e., greater coincidence. Significant improvements were
also made in capabilities for spectral coverage and resolution. New
measurements of the spectral albedo of cirrus clouds were obtained and
improved knowledge of the spectral-dependence cloud radiative properties
is anticipated. There is strong potential for significant impacts on
future satellite-based cloud observing capabilities (105).

Aircraft data sets of radiative fluxes, microphysics, and cloud
structure (lidar) were obtained in FIRE Pilot Tropical Cirrus Experiment
and CEPEX (ER-2 and a single in situ aircraft). These sets were acquired
in survey mode over the tropical western and central Pacific Ocean. With
the exception of several flights carried out over the DOE/ARM PROBE site
in Kavieng, Papua New Guinea, during TOGA-COARE, these sets lack the
ancillary ground-based information available for the FIRE IFO sets. Of
particular note is the new capability to observe the bi-directional
reflectance (bulk scattering pattern) of cirrus clouds from the ER-2
(45). Although these observations are not the direct measurements of
fundamental cloud radiative properties called for in Section 4.2, they
do provide a significantly less inferential measure of fundamental
scattering properties than many previous remote sensing measurements.

The highly variable macrophysical structure of many cirrus clouds
further complicates the analysis of their radiative properties (147,
148, 152, 153,1 54, 155). This is true for in situ aircraft
observations, and for remote sensing observation from beneath and above
(156, 157), and for computational analyses of the cloud layer\'s
radiative properties. This same highly variable nature of cirrus clouds
also complicates the inference of microphysical properties of the cloud
by remote sensing techniques. FIRE III will continue to address these
issues of relationships between middle and upper tropospheric cloud
macrophysical structures and radiative properties.

The FIRE data sets provide a wealth of opportunity to address the issues
of cirrus cloud optical properties and their relationship to radiative
fluxes and ice mass, as well as remote sensing. *Completion of the
analysis of FIRE Phase II observations and exploitation of those results
in evaluating and improving models of radiative transfer in cirrus
clouds is a high priority for the initial stage of FIRE Phase III.* The
detailed microphysical data can be used in conjunction with
computational algorithms to deduce cloud optical properties, such as
extinction coefficient and the asymmetry factor. In turn, the calculated
cloud optical properties can be used to compute radiative fluxes for
comparison with observations. Model-calculated radiative fluxes, as well
as more specific quantities such as beam radiances, should be compared
to observed radiative fluxes and spectrally-resolved radiances and
fluxes (140,141,144,145,146,158). Detailed descriptions of the particle
volume scattering phase functions can be used to provide additional
insight into satellite retrievals of quantities such as mean effective
particle size, cloud optical thickness and their relationships to cloud
IWP, and microphysical properties. It should also be noted that, in
addition to the enhanced quality of the available microphysical
observations, recently developed techniques for explicit calculation of
the scattering of solar radiation by single ice crystals of complex
shape (21,18,159) will more tightly constrain the
observation-versus-model comparisons.

These data sets also provide unique opportunities for direct evaluation
of the performance of cloud and regional cloud system (mesoscale) models
in terms of the predicted cloud optical properties and radiative fields.
High-resolution simulations of cirrus cloud development and life cycle
can be compared to appropriate high-resolution radiative observations
(aircraft and ground-based) while regional cloud system simulations can
be compared to the broader-scale satellite observations. At each scale,
the quality of the observations is enhanced via the integrated analysis
of the multiparameter-multiplatform observations discussed previously.

Extended exploitation of the FIRE Phase II data sets is essential for
the effective design of any future field campaigns. Clear definition of
mission goals, measurement requirements, and sampling strategies
absolutely depends on identification of the key outstanding scientific
issues and, in particular, identification of specific areas of
disagreement between observations and theory. Instrument development
needed to make the required measurements to resolve those discrepancies
must be defined. Such guidance is critical for development of effective
experiment planning.

. *How representative are midlatitude continental cirrus of upper
tropospheric clouds in other regions of the globe?*

It is crucial to know whether the different environments in which cirrus
clouds occur result in quantitatively and/or qualitatively different
modes of microphysical and radiative behavior, or whether, for example,
a single universal cirrus parameterization can be applied to different
regions of parameter space (67). There may be important differences in
cirrus clouds based on the source and history of the air in which the
clouds form, e.g., temperature, uplift velocity, and ambient aerosol
composition and concentration (13,159,160). Cirrus cloud ice water mass
distribution, microphysical properties, and optical properties will be
derived for pre-FIRE data and the midlatitude FIRE Cirrus-I and FIRE
Cirrus-II field experiments and the tropical FIRE Pilot Tropical Cirrus
Experiment and CEPEX data sets (114). Comparisons of these data can
begin to address the differences between midlatitude and tropical upper
tropospheric cloud properties. FIRE studies have successfully applied
numerous remote sensing techniques to infer the dynamic structure of
cirrus cloud layers (161,162,163,164). These results will be very useful
in assessing the requirements for further observations of tropical
cirrus clouds and in planning any subsequent tropical field experiments,
whether major campaigns or smaller highly-focused deployments.

Tropical data sets are more limited than what is available from the
midlatitude experiments in terms of satellite data (GMS rather than
GOES), description of the dynamical environment (much less rawinsonde
and profiler coverage, especially at the mesoscale), in situ data (a
single in situ platform versus three in FIRE Cirrus-II), and coincident
ground-based remote sensing observations. Moreover, no in situ data are
available for the cold upper portion of the observed tropical cirrus
cloud systems, including the ubiquitous thin cirrus cloud layer found at
the tropical tropopause. Nonetheless, the quality of the available
radiative, microphysical, and aerosol data are very comparable.

Comparisons of the observed physical properties of convectively-spawned
anvil-cirrus formations will be made with the properties observed for
midlatitude cirrus cloud systems. Examination of the temperature
dependence of cloud ice mass distribution and microphysical composition
(crystal size and habit distributions), as well as cloud optical
properties, will provide a measure of the dependence of cloud physical
properties on environmental conditions. Comparisons of cloud structure
and heterogeneity will prove especially useful. However, establishing
the dynamical background may not be feasible for the tropical data given
the paucity of the available observations. Model-based analyses of
large-scale vertical motion derived from the available rawinsonde and
profiler observations will be the primary source of information
(four-dimensional data assimilation for TOGA-COARE). However, it is not
presently known how reliable these analyses are or how representative
they might be for the observed cirrus cloud systems which are known to
develop appreciable mesoscale uplift through the effects of local
radiative processes and latent heating and cooling. Studies using
regional cloud system models will likely prove to be the means of
quantifying the effects of mesoscale forcing.

Quantifying the convective input to the tropical upper troposphere in
terms of ice mass and crystal population will be very challenging. Such
descriptions would be extremely useful for the analysis and modeling of
the subsequent evolution of convectively-spawned anvils. However,
present capabilities to derive such information are, at best, unproven.
In this area, FIRE will benefit significantly from TOGA-COARE research
on deep convection.

4.4. Conclusions

FIRE III will continue to make major contributions to our understanding
of upper tropospheric cloud systems. Some of these contributions will
stem from integrated multi- platform, multi-parameter, and
multi-technique studies which are in their initial phase. The
development of new instrumentation and techniques to observe key
microphysical and radiative properties of ice clouds will also further
our understanding of these climatically important cloud systems.

FIRE scientists will design and execute limited-scope field programs
(ETOs) to complement previous research and new instrumentation
development crucial to improving the understanding of upper tropospheric
cloud systems. Furthermore, in the short term, FIRE scientists will have
the opportunity to participate in other field campaigns which complement
FIRE\'s goals.

The climate system has been shown to be particularly sensitive to
tropical upper tropospheric cloud systems. FIRE III will assess the
similarities and differences between midlatitude cirrus and tropical
cirrus cloud systems; the outcome of this assessment will enable the
scientific community to make a sound decision about whether or not a
major field campaign to study tropical upper tropospheric cloud systems
is justified. Should a tropical field campaign be called for, FIRE III
will design and execute such a field campaign.

The ambitious goals of FIRE III can only be met with the active
collaboration among researchers from may different arenas. The
integrated studies referred to above emphasize this collaboration.
However, collaboration among agencies and programs is equally important
to the vitality of the scientific effort. FIRE III looks forward to the
continuing cooperation with DOE/ARM and NSF, and to new opportunities
for collaboration on problems of mutual interest with EUCREX, ROCEW,
MCTEX, SASS and GEWEX.

4.5. References

1\. Heck, P. W., W. L. Smith, Jr., R. Palikonda, D. F. Young and P.
Minnis, 1994: Satellite-derived cloud properties during TOGA/COARE.
Preprint volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28, 1994,
Nashville, TN.

2\. Jin, Y. and W. B. Rossow, 1994: Investigation and comparison of
ISCCP and HIRS high level clouds. *Proc. AMS 8th Conf. Atmos.
Radiation*, Nashville, TN, Jan. 23-28, 64-65.

3\. Rossow, W. B. and L. C. Garder, 1993a: Cloud detection using
satellite measurements of infrared and visible radiances for ISCCP. *J.
Climate*, **6**, 2341-2369.

4\. Gibson, G. G., P. Minnis, D. F. Young, P. W. Heck, and E. F.
Harrison, 1990: A comparison of ISCCP and FIRE satellite cloud
parameters. *FIRE Science Results 1989, NASA CP 3079*, 257-262.

5\. Ackerman S. A., and W. L. Smith, X. L. Ma, R. O. Knuteson and H. E.
Revercomb, 1993: Cirrus cloud retrievals from HIS observations during
FIRE II. Preprint volume, *FIRE Cirrus Science Conference*, June 14-17,
1993, Breckenridge, CO.

6\. Ackerman, S. A. and R. A. Frey, 1994: Climate monitoring using
collocated AVHRR and HIRS/2 observations. Preprint volume, *8th Conf. on
Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

7\. Chang, F.-L., J. A. Coakley, Jr. and L. L. Stowe, 1994: Cloud
properties retrieved from NOAA AVHRR data using spatial coherence CLAVR
and ISCCP techniques. Preprint volume, *8th Conf. on Atmos. Radiation,
Jan. 23-28,* 1994, Nashville, TN.

8\. Baum, B. A. and B. A. Wielicki, 1994: Cirrus cloud retrieval using
infrared sounding data: Multilevel cloud errors. *J. Appl. Meteor.,*
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9\. King, M. D., Y. J. Kaufman, W. P. Menzel and D. Tanre\', 1992:
Remote sensing of cloud, aerosol, and water vapor properties from the
Moderate Resolution Imaging Spectrometer (MODIS). *IEEE Trans. Geosci.
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10\. Lee, R. B. III, B. R. Barkstrom, S. L. Carmen, J. E. Cooper, M. A.
Folkman, P. J. Jarecke, L. P. Kopia, and B. A. Wielicki, 1993: The
Clouds and the Earth\'s Radiant Energy System (CERES) Experiment, Earth
Observing System (EOS) instrument and calibrations. *SPIE*, **1939**,
61-71.

11\. King, M. D., 1994: The application of EOS to studies of atmospheric
radiation and climate. Preprint volume, *8th Conf. on Atmos. Radiation*,
Jan. 23-28, 1994, Nashville, TN.

12\. Wielicki, B. A. and B. R. Barkstrom, 1991: Clouds and the Earth\'s
Radiant Energy System (CERES): An Earth Observing System experiment.
*AMS Second Symposium on Global Change Studies,* New Orleans, LA., Jan.
14-18,

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15\. Kinne, S. and Liou, K.-N. 1989: The effects of the nonsphericity
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17\. Stackhouse, P. W. and G. L. Stephens, 1994: Investigation of the
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18\. Minnis, P., D. F. Young, D. P. Garber, Y. Takano and K.-N. Liou,
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19\. Mitchell, D. L., W. P. Arnott, Y. Y. Dong, J. Hallett and K.
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20\. Mitchell, D. L., J. E. Kristjansson and M. J. Newman, 1994:
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21\. Takano, Y. and K. N. Liou, 1989: Radiative transfer in cirrus
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22\. Withrow, J. and S. K. Cox, 1993: Extinction efficiencies from DDA
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23\. Withrow, J. and S. K. Cox, 1994: Asymmetry parameter calculations
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24\. Flatau, P. J., 1994: Parameterization of scattering by
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25\. Fuller, K. A., G. L. Stephens, and B. D. Jersak, 1994: Some
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26\. Wielicki, B. A. R. Arduini and L. Parker, 1993: Remote sensing
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27\. Arnott, W. P., Y. Y. Dong, and J. Hallett, 1994: Extinction
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28\. Gerber, H., 1994: New microphysics sensor for aircraft use.
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29\. Duda, D. P., G. L. Stephens, and W. R. Cotton, 1994: Impact of
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32\. King, M. D., L. F. Radke and P. V. Hobbs, 1993: Optical properties
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33\. Ackerman, T. P., J. A. Valero, S. A. Kinne, P. Pilewskie, F. P. J.
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34\. Kinne, S., R. Bergstrom, T. P. Ackerman and J. DeLuisi, 1993:
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38\. Eloranta, E. W. and P. Piironen, 1994: Remote particle size
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46\. Anikin, P. P., and S. K. Cox, 1994: Cloud optical depths inferred
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47\. Anikin, P. P., S. K. Cox and J. M. Davis, 1994: Determination of
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48\. Baum, B. A., V. Tovinkere, J. Titlow, and R. M. Welch, 1994:
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49\. Baum, B. A., R. F. Arduini, B. A. Wielicki, P. Minnis, and S.-C.
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51\. Harrington, J. L., M. P. Meyers and W. R. Cotton, 1993: Mesoscale
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52\. Harrington, J. L., M. P. Meyers, P. J. DeMott, and W. R. Cotton,
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53\. Jensen, E. J., O. B. Toon and D. L. Westphal, 1993: Three
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54\. Westphal, D. L., E. J. Jensen and S. A. Kinne, 1994: Validation of
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55\. Raschke, E., 1994: Results of cirrus properties from the European
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72\. Greenwald, T. J., G. L. Stephens, and T. H. Vonder Haar, 1994: A
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76\. Evans, K. F., and G. L. Stephens, 1994: A theoretical study of
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90\. Randel, D. L., T. H. Vonder Haar and H. J. Ganse, 1994: The annual
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99\. Ackerman, S. A., W. L. Smith, J. D. Spinhirne and H. E. Revercomb,
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101\. Gumley, L. E., M. D. King and S.-C. Tsay, 1994: Multi-sensor
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102\. Minnis, P., P. W. Heck, and E. F. Harrison, 1990: The 27-28
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103\. Bucholtz, A., F. P. J. Valero and P. Pilewskie, 1994: Airborne
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104\. Christopher, S. A., A. M. V. Vorste, S. E. Watters and R. M.
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105\. Coakley, J. A., Jr., 1991: Reflectivities of uniform and broken
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109\. Gillies, S. C. and S. K. Cox, 1994: Shortwave radiative fluxes in
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110\. Benjamin, S. G., K. A. Brewster, R. Brummer, B. F. Jewett, T. W.
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111\. Gultepe, I. and D. O\'C. Starr, 1994: Microphysical and radiative
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112\. Gultepe, I. and D. O\'C. Starr, 1994: A comparison of evaporative
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115\. Orr, B. W. and R. A. Kropfli, 1993: Estimates of cirrus cloud
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128\. Heymsfield, A. J. and C. M. R. Platt, 1984: A parameterization of
the particle size spectrum of ice clouds in terms of the ambient
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129\. Inoue, T., 1985: On the temperature and effective emissivity
determination of semi-transparent cirrus clouds by bi-spectral
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130\. Wesley, D. A. and S. K. Cox, 1988: Radiative processes in upper
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131\. Dutton, E. G., 1994: Comparison of the solar radiative effects of
El Chichon and Mt. Pinatubo long-lived aerosols. Preprint volume, *8th
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132\. Minnis, P., E. F. Harrison, L. L. Stowe, G. G. Gibson, F. M. Denn,
D. R. Doelling, and W. L. Smith, Jr., 1993: Radiative climate forcing by
the Mount Pinatubo eruption. *Science*, **259,** 1411-1415.

133\. Minnis, P., 1994: Radiative forcing by the 1991 Mt. Pinatubo
eruption. Preprint volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28,
1994, Nashville, TN.

134\. Sassen, K., et al., 1993: The 5-6 December 1991 FIRE IFO II jet
stream cirrus case study: The influence of volcanic aerosols. Preprint
volume, *FIRE Cirrus Science Conference*, June 14-17, 1993,
Breckenridge, CO.

135\. Baum, B. A.; B. A. Wielicki, P. Minnis, and L. Parker, 1992: Cloud
property retrieval using merged HIRS and AVHRR data. *J. Appl. Meteor.*,
** **, 351-369.

136\. Beck, G. H., J. M. Davis and S. K. Cox, 1993: Spectral emissivity
of cirrus clouds. Preprint volume, *FIRE Cirrus Science Conference*,
June 14-17, 1993, Breckenridge, CO.

137\. King, M. D., L. F. Radke and P. V. Hobbs, 1990: Determination of
the spectral absorption of solar radiation by marine stratocumulus
clouds from airborne measurements within clouds. J*. Atmos. Sci.*,
**47**, 894-907.

138\. King, M. D. and S.-C. Tsay, 1994: Radiative and microphysical
characteristics of a multi-layered cloud system: preliminary results
from TOGA COARE. Preprint volume, *8th Conf. on Atmos. Radiation*, Jan.
23-28, 1994, Nashville, TN.

139\. Spinhirne, J. D., D. Hlavka and W. Hart, 1994: Observation of the
bi-directional and spectral reflectance of cirrus and other clouds.
Preprint volume, *8th Conf. on Atmos. Radiation,* Jan. 23-28, 1994,
Nashville, TN.

140\. Bergstrom, R. W., S. A. Kinne and O. B. Toon, 1994: Improved
prediction of atmospheric heating and cooling rates. Preprint volume,
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141\. Ellingson, R. G., W. J. Wiscombe, J. DeLuisi, S. H. Melfi and W.
L. Smith, 1993: Calibration of radiation codes in climate models:
comparison of calculations with observations from the SPECtral radiation
experiment (SPECTRE). Preprint volume, *FIRE Cirrus Science Conference*,
June 14-17, 1993, Breckenridge, CO.

142\. Ellingson, R. G., and S. Shen, 1994: The spectral radiation
experiment (SPECTRE): An overview - clear-sky observations and
validation of line-by-line models. Preprint volume, *8th Conf. on Atmos.
Radiation*, Jan. 23-28, 1994, Nashville, TN.

143\. Evans, K. F., 1994: Monte Carlo stochastic radiative transfer.
Preprint volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28, 1994,
Nashville, TN.

144\. Evans, K. F., 1993: Two-dimensional radiative transfer in cloudy
atmospheres: The spherical harmonic spatial grid method. *J. Atmos.
Sci.*, **50**, 3111-3124.

145\. Francis, P. N., R. W. Saunders, A. Jones and A. Slingo, 1994: An
observational and theoretical study of the radiative properties of
cirrus: some results from ice \'89. Preprint volume, *8th Conf. on
Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

146\. Fu, Q., K.-N. Liou and Y. Takano, 1994: Delta-four-stream
parameterization for radiative flux transfer in an antisotropic medium:
application to ice clouds. Preprint volume, *8th Conf. on Atmos.
Radiation*, Jan. 23-28, 1994, Nashville, TN.

147\. Gabriel, P. M. and K. F. Evans, 1994: Domain averaged solar
radiative fluxes calculated by first order closures in inhomogeneous
media. Preprint volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28,
1994, Nashville, TN.

148\. Killen, R. M. and R. G. Ellingson, 1994: Sensitivity of
atmospheric heating rate to cloud geometry and spatial distribution.
Preprint volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28, 1994,
Nashville, TN.

149\. Takara, E. E. and R. G. Ellingson, 1994: Monte Carlo simulation of
infrared radiative transfer through broken cloud fields. Preprint
volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28, 1994, Nashville,
TN.

150\. Zender, C. S and J. T. Kiehl, 1994: The radiative influence of
crystal habit and size in tropical anvils. Preprint volume, *8th Conf.
on Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

151\. Tsay, S.-C., M. D. King, P. M. Gabriel and G. L. Stephens, 1994: A
Fourier-Riccati approach to radiative transfer. Part II computations of
spectral reflectance and heating rates in cirrus-like clouds. Preprint
volume, *8th Conf. on Atmos. Radiation,* Jan. 23-28, 1994, Nashville,
TN.

152\. Sassen, K., D. O\'C. Starr and T. Uttal, 1989: Mesoscale and
microscale structure of cirrus clouds: Three case studies. *J. Atmos.
Sci.*, **46**, 371-396.

153\. Hammer, P. D., F.P.J. Valero and S. Kinne, 1991: The 27-28 October
1986 FIRE Cirrus case study: Retrieval of cloud particle sizes and
optical depths from comparative analyses of aircraft and satellite based
infrared measurements, *Mon. Wea. Rev.*, **119,** 1673-1692.

154\. Loeb, N. G. and R. Davies, 1994: Average effects of cloud in
homogeneity from ERBS scanner measurements. Preprint volume, *8th Conf.
on Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

155\. Macke, A., 1994: Scattering of light by irregular ice crystals in
three-dimensional inhomogeneous cirrus clouds. Preprint volume, *8th
Conf. on Atmos. Radiation,* Jan. 23-28, 1994, Nashville, TN.

156\. Eberland, W. L., J. M. Intrieri and G. Feingold, 1994: Cirrus
radiative and microphysical properties from combined lidar, radar and
infrared radiometer measurements at FIRE II. Preprint volume, *8th Conf.
on Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

157\. Wylie, D. P., W. Wolf and E. Eloranta, 1994: Visible and infrared
radiative relationships as measured by satellite and lidar. Preprint
volume, *8th Conf. on Atmos. Radiation*, Jan. 23-28, 1994, Nashville,
TN.

158\. Lin, X. and J. A. Coakley, 1994: Cloud properties from the
analysis of AVHRR observations for FIRE II. Preprint volume, *8th Conf.
on Atmos. Radiation*, Jan. 23-28, 1994, Nashville, TN.

159\. Mishchenko, M. I., B. E. Carlson and A. A. Lacis, 1994: Radiative
properties of non- spherical aerosols. Preprint volume, *8th Conf. on
Atmos. Radiation,* Jan. 23- 28, 1994, Nashville, TN.

160\. Minnis, P., E. F. Harrison and G. G. Gibson, 1987: Cloud cover
over the eastern equatorial Pacific derived from July 1983 ISCCP data
using a hybrid bispectral threshold method. *J. Geophys. Res.*, **92**,
4051-4073.

161\. Mace, G. G. and T. P. Ackerman, 1993: Cirrus cloud development in
a mobile upper tropospheric trough: the November 26 FIRE cirrus case
study. Preprint volume, *FIRE Cirrus Science Conference*, June 14-17,
1993, Breckenridge, CO.

162\. Mace, G. G., T. Ackerman, D. O\'C. Starr and P. Minnis, 1994:
Modulation of cloud optical properties by vertical circulations
associated with a jet streak exit region: the November 26 FIRE cirrus
case study. Preprint volume, *8th Conf. on Atmos. Radiation*, Jan.
23-28, 1994, Nashville, TN.

163\. Rawlins, F., and J. S. Foot, 1990: Remotely sensed measurements of
stratocumulus properties during FIRE using the C130 aircraft
multichannel radiometer. *J. Atmos. Sci.*, **47,** 2488-2503.

164\. Song, R. and S. K. Cox, 1993: Vertical velocity in cirrus case
obtained from wind profiler. Preprint volume, *8th Conf. on Atmos.
Radiation*, Jan. 23-28, 1994, Nashville, TN.

**5. ARCTIC CLOUD SCIENCE PLAN**

5.1. Introduction

Arctic air-sea-ice processes influence global climate by modifying the
surface albedo and regulating the thermohaline circulation of the global
ocean. Arctic sea ice covers roughly 107 km2, or about 7% of the
Earth\'s surface, with an average albedo on the order of 70%. Variations
of sea ice properties alter the planetary albedo and the heat conduction
from ocean to atmosphere. The Arctic Ocean is strongly illuminated by
the sun during the summer, so that, in the absence of clouds, replacing
the ice by open ocean with an albedo on the order of 7% could increase
the solar radiation absorbed in high latitudes by as much as 200 W m-2
in the summer months. This additional energy input into the Arctic ocean
could possibly prevent sea ice from forming during the winter.

In fact, climate models subjected to a doubling of CO2 simulate Arctic
warming on the order of 10 K, primarily in winter. This strong warming
is due in part to the positive feedback associated with melting and/or
thinning sea ice. A drastic reduction in the equator-to-pole temperature
gradient results, leading to important changes in the general
circulation of the atmosphere. Of course, these model predictions must
be regarded with some skepticism, due in large part to our ignorance of
and inability to model with confidence the Arctic surface energy budget,
the closely related mass budget of the sea ice, and the formation,
maintenance and dissipation of Arctic clouds. Nevertheless, the climate
model results point to a need for more comprehensive observations of key
Arctic climate processes.

Intensified research efforts to investigate the key physical processes
and feedbacks of the Arctic climate system are necessitated by:

∑ questions about possible amplification of global change in the Arctic
and disagreement between models and observations;

∑ questions concerning the stability of the Arctic ice pack;

∑ errors in simulations of the present-day Arctic climate by GCMs and
the disagreements among the models concerning Arctic climate change
predictions; and

∑ the lack of in situ data to validate and improve satellite retrievals
and GCM performance in the Arctic.

Data on the space-time variations of clouds, radiation and the surface
energy balance in the polar regions are very sparse due to a lack of
conventional observations, unfortunately combined with difficulties in
satellite remote sensing.

Remote sensing from space provides some of the temporal and spatial
coverage needed for climate monitoring and, as the time period of
continuous observations expands, should become increasingly valuable for
the detection of climatic trends. However, large discrepancies between
surface- and satellite-derived climatologies exist. The lack of in situ
data is a major obstacle to evaluating and improving satellite
retrievals and GCM parameterizations of Arctic processes.

Detailed process-oriented data sets that document the simultaneous
temporal variations of the coupled atmosphere-sea ice-ocean system on
time scales of hours to a year are needed to achieve a real improvement
in our knowledge of Arctic and global climate. These data sets will be
used to formulate, test and implement improved parameterizations for the
GCMs, and to facilitate the development of a long-term monitoring system
using satellites and buoys to improve the climatology.

In the context of global climate change, we are faced with a need to
document, understand and predict the feedbacks involving clouds,
radiation, and the rest of the Arctic climate system. Among the relevant
processes are changes in cloud fraction and vertical distribution, water
vapor and cloud water content, cloud particle concentration and size,
and cloud phase, as atmospheric temperature and chemical composition
change. Arctic clouds are important for a wide variety of climate
processes, such as:

∑ Arctic and global climate-radiation balance,

∑ interactions with large-scale dynamical systems such as cold-core
anticyclones,

∑ maintenance of the pole-to-equator temperature gradient,

∑ sea ice characteristics such as temperature, albedo, ice volume and
rate of transport to North Atlantic.

Some progress has been made in recent years both observationally and
theoretically with regards to understanding the Arctic climate system.
For example, the Arctic Stratus Experiment was conducted during June
1980 over the Beaufort Sea. The objectives of this experiment were to
concurrently measure cloud microphysical properties with atmospheric
radiative fluxes in the boundary layer stratus clouds and to interpret
the radiative fluxes in the context of the cloud microphysical
properties. In addition to radiation fluxes and cloud microphysical
properties, high-frequency measurements of winds, temperature and
humidity were obtained from the NCAR Electra aircraft. ECMWF analyses
and DMSP visible and infrared satellite images provided the large-scale
context for the measurements. No in situ surface measurements were made.
Using these data, the radiative properties of the clouds were analyzed
and modeled (Herman and Curry, 1984; Curry and Herman, 1985a; Tsay et
al., 1989), the cloud microphysical properties were described (Tsay and
Jayaweera, 1984) and interpreted in the context of turbulence and
radiative processes (Curry 1986), the mean and turbulence structure of
the cloudy atmospheric boundary layer were analyzed (Curry et al. 1988)
and modeled (McInnes and Curry 1994), and the cloud fraction was
interpreted in the context of the large-scale dynamics (Curry and Herman
1985b).

The motivation for a FIRE III expedition, in the mid-1990\'s, to study
Arctic boundary-layer clouds arises from several directions:

∑ GCM assessments. Recent increases in the number and quality of model
simulations of current and doubled CO2 climates highlight both the
importance of Arctic processes and the large gaps in our knowledge about
them.

∑ Access. The end of the Cold War has resulted in a most beneficial
exchange of ideas and data between scientists in the former Soviet Union
and western countries. In particular, areas previously inaccessible to
western scientists have now been opened and new options exist for
logistical support in the Arctic Ocean.

∑ New technology. Newly developed techniques for observing clouds and
radiation have not yet been applied systematically to the Arctic Ocean.
Recent instrumental developments allow ground-based observations of
cloud properties and the vertical structure of the atmosphere that were
previously possible only by using aircraft.

∑ Satellite Sensors. Upcoming launches and continued operation of
satellite-borne active and passive microwave sensors, visible and
infrared imagers, and remote sounders will provide unprecedented
coverage of key variables, making 1995-2005 the ™decade of polar remote
sensing.∫

∑ Computational Capability. Recent and continuing developments in
computer technology make it possible to implement sophisticated
formulations of Arctic air-sea-ice processes in global climate models,
and to perform improved simulations of the role of the Arctic in climate
change scenarios.

∑ Program Coordination. Arctic climate studies appear to be uniquely
positioned to take advantage of opportunities for interagency and
international cooperation. Relevant programs include: NSF Arctic System
Science (ARCSS) Ocean-Atmosphere-Ice Interactions (OAII) program; SHEBA
(the Surface Heat Balance of the Arctic project), which is an
multi-agency U.S. program; the DOE Atmospheric Radiation Measurement
(ARM) program; the NASA Earth Observing System (EOS) initiative and the
NASA Polar Ice and Climate program; the ONR Arctic Program; the Global
Ocean-Atmosphere-Land System (GOALS) program; the Arctic Climate System
Study (ACSYS) of the World Climate Research Programme (WCRP); the WCRP
Global Energy and Water Experiment (GEWEX), the WCRP International
Satellite and Cloud Climatology Program (ISCCP), and the WCRP Climate
Variability and Predictability (CLIVAR) program.

The following section discuss some of the key physics of the Arctic
climate, with emphasis on their relevance to the interests of FIRE.

5.2. Scientific Issues and Objectives

The climatic importance of the Arctic stems largely from the
interactions and couplings among many physical processes that are unique
to the region. The following subsections describe interactions and
processes that are of particular interest to FIRE.

5.2.1 Sea ice

Although the study of sea ice per se is not a key objective of FIRE, the
sea ice is a critically important lower boundary condition that strongly
affects both radiation and turbulent fluxes. In addition, many FIRE
modeling studies will have to include sea ice sub-models. For these
reasons, we begin this Section with a discussion of the key physical
characteristics of and processes associated with sea ice.

Our knowledge of the large-scale features of sea ice has been vastly
increased by microwave remote sensing from satellite (e.g. Cavalieri and
Zwally, 1985; Comiso, 1986), which has now yielded a record of sea ice
extent and concentration over a decade in length. Synthetic Aperture
Radar (SAR) is increasingly being utilized to discern sea ice velocities
and small-scale features of sea ice (e.g. Fily and Rothrock, 1986;
Collins and Emery, 1988). Observations of leads from satellite (e.g.
Barry et al., 1989) and SAR (e.g. Fily and Rothrock, 1990) are giving
increased knowledge of lead fraction, size distribution, and life cycle.
Improved measurements of spectral surface albedos have been reported by
Grenfell and Perovich (1984). Recent in situ observations are reported
by Maykut and Perovich (1987) for MIZEX and Wettlaufer et al. (1990) for
CEAREX. Observations of sea ice thickness are still sparse; it is
expected that declassification of submarine sonar data will provide
valuable new information.

Recent improvements to the understanding of sea ice thermodynamics have
been made by Harvey (1988 a, b), Mellor and Kantha (1989), Harvey (1990)
and Ebert and Curry (1992). Of particular concern has been the
disposition of solar radiation in the sea ice / ocean system. Ebert and
Curry (1993) have incorporated all available observations of surface
albedo into a new spectral surface albedo parameterization that has a
solar zenith angle dependence and a dependence on the ratio of direct to
diffuse shortwave radiation. The penetration of solar radiation into the
sea ice has also been parameterized by Ebert and Curry (1992) to be a
function of the ratio of diffuse to direct solar radiation. A new melt
pond parameterization has been formulated by Ebert and Curry (1992),
allowing a variable pond area and depth and a prescribed fraction of
surface meltwater runoff. At the end of the melt season, freezing occurs
at the top of the ponds, the melted water beneath the surface ice acting
as a latent heat reservoir. The penetration of shortwave radiation into
leads and their effect on lateral and bottom ablation have been observed
by Maykut and Perovich (1987) and Wettlaufer et al. (1990). This effect
has been parameterized by Harvey (1990).

The Arctic atmospheric boundary layer is characterized by extreme
stability, particularly during wintertime. The physical processes
involved in the formation of polar temperature inversions are discussed
by Neff (1980) and Busch et al. (1982). The evolution of the wintertime
boundary layer structure in cold continental Polar air masses has been
modeled by Curry (1983). The Arctic atmospheric boundary layer is
further complicated by the presence of steep topography particularly in
Alaska and Greenland and the resulting katabatic winds. Although a
reasonable understanding of katabatic winds has been obtained as a
result of the observational and theoretical studies conducted in the
Antarctic, gaps in our understanding of the mechanisms of radiative
cooling and entrainment into the katabatic layer still remain.

One of the most intriguing aspects of the Arctic atmospheric boundary
layer is presence of extreme horizontal inhomogeneities associated with
ice margins, leads (quasi-linear breaks in the ice, with widths on the
order of 100 m - 1 km, and lengths up to hundreds of kilometers) and
polynyas (quasi-circular pools of open water, sometimes many kilometers
across, surrounded by ice and / or shoreline). Heat flux from leads and
/ or polynyas have been determined by Andreas (1980), Andreas and Murphy
(1986), denHartog et al. (1983), Smith et al. (1983) and Walter (1989).
Modeling of turbulent fluxes in the marginal ice zone has been conducted
by Mellor and Kantha (1989) and for leads by Lo (1986) and Glendening
and Burk (1992).

Leads represent a major source of non-uniformity in the surface forcing
over the ice in the Arctic. This is in sharp contrast to the more
uniform surface of the ocean and to the more typical forms of surface
inhomogeneity over land (orography, land forms, roughness changes,
etc.). During winter, air-water temperature differences of 20 to 40 C
can result in a combined local (over the lead) sensible and latent heat
transfer to the atmosphere of as much as 1000 W m-2. At Arctic water
temperatures sensible heating dominates latent heating. Such rates of
heat exchange are more commonly associated with strong daytime
convective transfer over land (e.g., deserts) and very powerful cold
continental air outbreaks over the oceans. This heat transfer warms and
moistens the atmosphere and cools the ocean in a highly localized
manner. Whereas only about 1-2% of the surface is occupied by leads in
the winter, it has been hypothesized that leads contribute about 50% of
the surface source of moisture and heat on the polar ice cap in winter.
Thus, the surface heat balance and surface-driving aspects of PBL
dynamics cannot be assessed without consideration of leads. Leads are
the only channel for release to the atmosphere of gases generated in the
ocean by biological processes.

The parameterization of fluxes directly over an open lead has been done
(Andreas and Murphy, 1986), but a number of important aspects of the
lead problem still exist. The Andreas and Murphy model only applies to
the lead just after its formation while it is 100% open water. However,
the great majority of the heat extracted from the lead comes out after
it is partially and totally frozen over. Even leads which have refrozen
with 10 cm of ice (thick enough to walk on) produce heat fluxes in the
tens of W m-2. There are no simple heat flux parameterizations that deal
with the entire life cycle of the lead. At larger scales, we must
consider the accumulated effects of a field of leads in various stages
of their life cycles. Thus, we need a parameterization of the
™effective∫ heat transfer as a function of variables such as lead size
and fractional surface coverage. At very low lead fractions, the leads
probably act independently and linearly but the details are unknown.

By triggering fog and / or clouds, the net radiative balance can be
severely perturbed near the lead; the lead is also a source of buoyancy
which generates turbulence, gravity waves, and mixing. The lead creates
a plume of warmer, moister, more turbulent air that evolves as it is
advected over the ice surface and interacts with the overlying boundary
layer. This plume returns heat to the ice and probably increases
cloudiness and affects the boundary-layer radiative transfer properties.
The relative importance of leads versus advection/entrainment sources of
PBL heat and moisture are unknown.

The effects of blowing snow on the mass and energy balance of the ice
also need further study (Schmidt, 1982).

Climate models need a way of diagnosing mean lead properties. Clearly,
climatological values for seasonal lead fraction cannot be used (even if
they were known) in a model that is portrayed as being usable for
forecasts or assessments of the effects of climate change. In the
winter, leads tend to be caused episodically by powerful storms; in the
summer the ice may be thin and weak enough so that mesoscale variability
in ocean currents can cause leads.

In summary, we have the following critical needs with respect to
understanding the role of sea ice and leads in Arctic climate:

∑ Measurements of lead fraction, ice thickness, and other
statistical-physical properties of the sea ice, and a method to
realistically predict and / or parameterize these quantities in GCMs.

∑ Assessment of the relative importance of leads as a macroscopic (i.e.
large-scale average) source of heat, moisture, and microphysically
relevant biogenic gases, particularly with respect to the formation and
radiative properties of clouds.

∑ A parameterization of lead fluxes based on a modified bulk model with
some effective lead fraction and possibly other lead statistics.

5.2.2 Clouds

A summary of available information on Arctic cloud properties is given
by Curry and Ebert (1992). Our knowledge of Arctic cloud properties is
hampered by difficulties in their observation from both surface and
satellite, and by the fact that there have been few in situ measurements
of Arctic cloud microphysical properties and that what little data we
have is limited mostly to the spring - summer seasons. Significant
advances in the remote sensing of clouds in the polar regions have
recently been made by including information on spatial coherence (e.g.,
Ebert, 1989; Key, 1990) and temporal coherence (Rossow and Lacis, 1991;
Rossow et al., 1989), but climatologies using these new techniques have
yet to be reported.

A principal discrepancy between Arctic satellite cloud climatologies and
the surface cloud climatologies is that the satellite estimates of
wintertime cloud cover are substantially greater than the surface values
(Schweiger and Key, 1993). Studies by Curry (1988), Hoff and Leaitch
(1989), Curry et al. (1990) and Curry and Ebert (1992) give support to
the existence of substantially enhanced cloud cover during winter,
agreeing qualitatively with the interpretation of wintertime Arctic
cloudiness from satellite. During the cold half of the year, when
sunlight is largely absent, lower tropospheric ice crystals are
frequently observed. Recent observations from the Coordinated Eastern
Arctic Experiment (CEAREX) during November 1988 (Overland and Guest,
1991) showed measured ™clear sky∫ radiative fluxes to be 10 - 40 W m-2
greater than expected when compared with modeled clear sky conditions;
it was inferred that the additional downwelling flux was associated with
lower tropospheric ice crystals. These measurements make one suspect
that there may in fact be no such thing as ™clear sky∫ conditions during
the polar night.

In addition to cloud fraction, cloud radiative properties depend on the
amount of condensed water, the size and shape of the cloud particles,
and the phase of the particles (liquid or ice). The microphysical
properties of summertime Arctic clouds were obtained from aircraft
measurements during the June 1980 Arctic Stratus Experiment (Herman and
Curry, 1984; Curry, 1986; Tsay and Jayaweera, 1984). Most of our
understanding of the microphysical properties of the wintertime
low-level ice crystals has been obtained from University of Washington
flights made in the 1960s (Witte, 1968) and the 1980s as a part of the
AGASP program. The microphysical properties of the wintertime
lower-tropospheric ice crystals have been reviewed by Curry et al.
(1990).

Understanding of the formation, maintenance and dissipation of
summertime boundary layer clouds has been obtained from the modeling
study of Herman and Goody (1976), boundary layer aircraft measurements
made during the Arctic Stratus Experiment (Curry et al., 1988), and the
large-scale diagnostic study of Curry and Herman (1985a). The model of
Curry (1983) presents an explanation for the formation and evolution of
low-level ice crystal layers during wintertime. The formation of ice
crystal plumes associated with leads has been examined by Schnell et al.
(1989) and Pinto and Curry (1994).

Curry and Ebert (1992) have integrated all available Arctic cloud
observations into determining the annual cycle of cloud properties.
While many uncertainties remain, this derived annual cycle is a
plausible working hypotheses and provides guidelines for incorporating
Arctic clouds into climate models, leading to the expectation that real
progress can be made on the parameterization of Arctic clouds in climate
models.

5.2.2.1 Cloud Microphysics

Ice cloud microphysics is poorly understood. Both particle size and
particle shape remain uncertain for all ice clouds, including polar ice
clouds. Polar ice clouds include elevated cloud layers as well as
™diamond dust∫ clouds which extend to the surface (Curry et al., 1993 a,
c). The best measurements to date are those from cloud particle
replicators (Curry et al., 1990) which gave an effective particle radius
of about 40 mm. Unfortunately only two measurements were made, so that
additional measurements are required. Ice particle shape (i.e. habit)
plays a dominant role in determining the single scattering phase
functions for ice clouds. These phase functions in turn determine the
cloud albedo for a given cloud optical depth (Platt et al., 1980;
Stephens et al., 1990). This problem is especially severe at the large
solar zenith angles typical of solar illumination in polar regions.
Recently, phase functions computed for hexagonal crystals (Takano and
Liou, 1989) have shown improved realism over those obtained for
spherical particles (Wielicki et al., 1990; Minnis et al., 1990), but so
far they have only been tested for a limited range of solar and viewing
geometries. Further improvements are required and should include both
laboratory and in-situ estimation of scattering phase functions.

There remains a question of the effect of springtime Arctic haze on the
absorption of solar radiation in polar clouds. M. D. King (personal
communication, 1994) has attempted to obtain measurements of Arctic
clouds and haze with his Cloud Absorption Radiometer, but did not
encounter favorable conditions; FIRE III could provide a new opportunity
to obtain such measurements. Resolution of the importance of this effect
requires multispectral and multi-angle observations in the diffusion
regime within the cloud, allowing determination of the single scatter
albedo at both conservative scattering (near 0.65 mm) and absorbing (1.6
and 2.2 mm) atmospheric window wavelengths. Measurements of total cloud
absorption using broadband aircraft fluxes are not likely to have
sufficient accuracy given the large horizontal spatial variability of
the cloud fields.

5.2.2.2 Precipitation

Relatively little is known about precipitation in the Arctic. Land-based
surface observations for the Soviet Arctic are described by Groisman
(1991). Modeling and observations of precipitation over Greenland are
summarized by Bromwich et al. (1992). The role of clear sky ice crystal
precipitation (e.g., Curry et al. 1990) in snow accumulation in the
Arctic is unknown, although it is suspected that it does not make a
large contribution except perhaps over Greenland, where other snow
formation mechanisms are relatively weak.

5.2.2.3 Layered structure

Arctic summertime stratus are often observed to form in multiple layers
in the lowest kilometer of the atmosphere (Herman and Goody, 1976; Curry
et al. 1988). The vertical structure of temperature and moisture is
similarly layered for periods of days. The layered structure is very
important for modeling these clouds and their radiative effects in
climate models. A GCM in which the boundary layer was assumed to be well
mixed produced only 30% as much mean summertime cloudiness as is
observed (Randall et al. 1985). In the winter and spring, there is often
a very strong increase of temperature in the lowest hundred meters. In
this case, the temperature of the cloud bases within these layers can
substantially affect the surface downwelling longwave radiation, and
hence the surface energy balance, and is nearly as important to
understand as the cloud amount.

We have only a primitive theoretical understanding of layering. In
summer, a shallow stably stratified layer with cloud is often observed
beneath an upper cloud-capped mixed layer, with little or no turbulent
mixing between the layers. Although lower-latitude marine stratocumulus
also are observed to exhibit layered structure in association with
diurnal decoupling due to solar absorption, or due to formation of a
cumulus cloud layer beneath a stratocumulus layer, the Arctic cloud
layer is quite different. In the lower-latitude case, the entire
boundary layer is moistened by fluxes from the sea surface, which are
communicated either at night by stratocumulus clouds, or by cumulus
clouds in the two scenarios just described. There is a dynamical link
between all cloud layers and the underlying surface.

In the Arctic, on the other hand, the upper cloud layers appear to
persist without any turbulent mixing of moisture up from the surface.
Three hypotheses have been advanced to explain the layering. All of
these models rely on a unique feature of the Arctic boundary layer,
namely that the air above the boundary layer is usually at least as
moist as the air in the boundary layer, so that entrainment can serve as
a moisture source in place of surface moisture fluxes. Herman and Goody
(1976) proposed a model in which cloud absorption of solar radiation
splits a cloud layer in two by warming the intermediate depths of the
cloud until they evaporate away. Tsay and Jayaweera (1984) proposed that
the upper cloud layer is formed by very weak ascent/entrainment, while
the surface layer is an advective fog. McInnis and Curry (1994), using a
turbulence closure model, suggested that the upper cloud is maintained
by cloud-top radiative cooling, while the lower cloud layer is formed by
condensation brought on by radiative chilling of air at the base of the
upper mixed layer, which is typically warmer than both the underlying
ice surface and the air above.

A variety of layered clouds have been observed and it is not clear from
our limited observations which of these mechanisms is really important.
The models that have been proposed have been heavily simplified,
especially in their treatment of turbulence (except for McInnis©s).
There are no large-eddy simulations of Arctic stratus to date to compare
with the simpler models. The life cycle of layered cloud systems has not
been studied at all for lack of suitable observations.

The radiative cooling and associated turbulent mixing in the upper cloud
layers may have large-scale impacts on the Arctic circulation distinct
from their uncertain direct impacts on the surface radiation budget of
the ice. Without cloud, the summertime Arctic boundary layer would be
very shallow, and much of the lowest kilometer of the atmosphere would
be warmer than with clouds present. This may help maintain the high
pressure and low level divergent flow in the central Arctic, enhancing
the role of the Arctic as a natural refrigerator and potentially
affecting the motion of sea ice.

5.2.3 Radiation

Recent in situ observations of radiation fluxes are reported by Herman
and Curry (1984) and Curry and Herman (1985 b) for the Arctic Stratus
Experiment, Francis et al. (1991) for MIZEX and Overland and Guest
(1991) for CEAREX. Satellite observations of the radiative fluxes at the
top of the atmosphere are reported by Barkstrom et al. (1990). Satellite
retrievals of Arctic surface radiative fluxes, albedos and temperatures
are being investigated by Rossow (personal communication) and Key
(personal communication).

Clouds are the dominant modulators of the Arctic radiation climate.
Features of the derived annual cycle of Arctic cloud optical properties
and cloud radiative effects that must be verified by more complete
observations are as follows: Cloud radiative properties depend on the
amount of condensed water, the size and shape of the cloud particles,
and the phase of the particles (liquid or ice). The radiative properties
of summertime stratus and altostratus clouds have been observed and
modeled by Herman and Curry (1984), Curry and Herman (1985 a, b) and
Tsay et al. (1989). The radiative properties of low-level ice crystal
clouds have been modeled by Curry (1983) and Curry et al. (1990). Curry
and Ebert (1992) derived the annual cycle of Arctic cloud optical
properties that are required to be consistent with both the outgoing
fluxes at the top of the atmosphere, as determined from satellite, and
the available determinations of surface fluxes. Existing data on cloud
fraction and cloud microphysical properties were utilized. Features of
the derived annual cycle of Arctic cloud optical properties and cloud
radiative forcing are summarized as follows:

∑ cloud emissivity is less than unity for all cloud types and during all
seasons;

∑ the net surface radiative flux is negative for more than half of the
year; over the course of the year clouds have a net warming effect on
the surface; and

∑ at the top of the atmosphere, cloud radiative forcing is dominated by
the shortwave flux.

Sensitivity studies were also performed by Curry and Ebert (1992) to
examine areas that represent uncertainties or weaknesses in climate
model parameterizations of cloud-radiation interactions in the polar
regions.

In modeling the radiative interactions occurring between sea ice and the
atmosphere, the complexity of the radiative interactions of clouds with
the highly-reflecting snow/ice surface must be taken into account (Ebert
and Curry, 1992). Surface albedo is not a simple function of surface
type and solar zenith angle, but also a function of cloud optical depth.
Clouds influence the surface albedo by selectively absorbing solar
radiation at wavelengths greater than about 0.7 mm. Because the spectral
reflectivity of snow is greater in the visible region than in the near
infrared (Grenfell and Perovich, 1984), the snow albedo under clouds
exceeds the clear-sky value. Thus it is important to consider the
spectral distribution of the downwelling solar flux. In addition, clouds
alter the distribution of the solar flux between direct and diffuse
components. This can be important for surface types whose reflection
characteristics are not Lambertian. In particular, the clear-sky albedos
of dry snow and open water depend significantly on the solar zenith
angle. The penetration of shortwave radiation into the sea ice depends
on the ratio of diffuse to direct radiation. The importance of solar
radiation penetrating leads in sea ice on lateral ablation of leads and
in warming the ocean mixed layer has been emphasized by Maykut and
Perovich (1987).

5.2.3.1 Non-plane Parallel Cloud Radiative Transfer with Large Solar
Zenith Angles

Recent studies of subtropical marine boundary layer clouds in FIRE 87
and ASTEX indicate that non-plane parallel cloud effects may play a
relatively minor role for these clouds (Wielicki and Parker, 1992;
Cahalan et al., 1994). This appears to be true despite the observed
large horizontal inhomogeneity of these cloud fields. Reasons for this
minor role include the absence of sharply defined cloud edges, typical
cloud thicknesses of 200 meters versus cell diameters of 1-5 km, and the
relatively low optical depth of broken cloud fields (values of 1-3).
Theoretical studies using Monte Carlo calculations show that non-plane
parallel effects are small for optical depths less than about 5-10
(Welch et al. 1980). It is not clear whether this conclusion also holds
for Arctic clouds, and it needs verification. The radiative effects of
the horizontally inhomogeneous summertime stratocumulus clouds over the
horizontally inhomogeneous, melting sea ice surface have hitherto not
been addressed.

A peculiarity of the polar regions is the dominance of large solar
zenith angles for solar illumination, especially in the spring and fall
seasons. Studies are needed to examine the accuracy of current radiative
models for solar zenith angles beyond about 80 degrees. This problem can
seriously affect the determination of both surface and cloud albedo. A
related issue is the increased anisotropy of the scattered radiation
field with increasing solar zenith angle. This anisotropy complicates
the conversion of satellite measured broadband radiance to flux
(Wielicki and Green, 1989) as well as the retrieval of cloud physical
properties from satellite multi-spectral radiances. Aircraft
measurements of surface and cloud anisotropy are required as a function
of solar zenith angle, and should be used to test the accuracy of
current radiative models.

5.2.3.2 Shortwave Flux Issues

Surface albedo is modified by meltpond area and depth, lead area, ice
thickness and age, snow thickness and age, and the effects of cloud on
surface albedo. Changes in direct/diffuse ratio and changes in spectral
distribution of solar illumination associated with changes in cloud
properties have a significant effect on the surface albedo. New methods
(Li and Leighton, 1990) have been developed to directly relate the
satellite observed net shortwave radiation at the top of the atmosphere
to the net shortwave radiation at the surface. A tower measurement of
upward shortwave flux should be included to test this method in the
polar region. A complication will be the characterization of melt pond
and leads within the satellite footprint. For the SCARAB instrument,
this will be a circle about 60 km in diameter.

5.2.3.3 Longwave Flux Issues

The central Arctic spends a greater portion of the year with little or
no solar illumination so that, in contrast to other parts of Earth, the
longwave fluxes play a much more important role in the total energy
balance, particularly at the surface.

Surface emissivity values over ice have been estimated between 0.8 and
1.0; the differences are associated with the effects of grain size.
Also, the stable stratification of the polar atmosphere can cause large
differences in surface skin temperature and air temperature. This effect
must be understood in order to properly determine upward longwave
fluxes.

The Arctic atmospheric longwave opacity is so low that the appearance of
clouds significantly increases the emission of longwave radiation both
downwards to the surface and upwards to space. Arctic clouds may
generally be optically thin enough that their longwave emissivities are
significantly less than unity which will alter their effect on the
radiation balance. Moreover, Arctic stratus often form in the warmest,
most humid layer, which can lie well above the surface, so that the
downward longwave flux in winter could, at times, be larger than the
upward flux from the sea ice.

For these reasons, downward surface longwave flux calculations require
accurate modeling of water vapor absorption at the low mixing ratios
typical of polar conditions. Verification of downward longwave flux
calculations should follow the process used in SPECTRE, i.e. combining
interferometer and broadband measurement of longwave radiation with
radiosonde profiles and Raman lidar water vapor profiles. Several
independent measurements of longwave broadband fluxes are required given
the current uncertainties (10 W m-2) in the absolute calibration of
these devices. Curry (1983) and Ellingson (personal communication)
report a water vapor window in the water vapor rotation band associated
with low atmospheric humidities in the Arctic winter. This window must
be considered when interpreting radiometer measurements and in
constructing spectral intervals for broadband radiative transfer models.
It has important implications for the water vapor feedback in polar
regions.

Most studies of surface fluxes are best carried out by surface-based
observations, through SHEBA (discussed later). FIRE can assist primarily
in obtaining a better understanding of the shortwave downward flux
transmitted through clouds and in providing more accurate surface
instrumentation such as Raman lidar and improved broadband longwave flux
measurement during the FIRE field campaigns. This is especially true in
the case of large solar zenith angles, which have not been examined in
these previous studies. A study of measured cloud anisotropy (Stuhlman,
1986) indicated good agreement with plane-parallel model calculations
for solar zenith angles less than 70 degrees, but poor agreement for
larger solar zenith angles. The disagreements were judged to be caused
by horizontal inhomogeneity in the cloud fields.

5.2.4 Atmospheric chemistry and Arctic clouds

In this section we address the role of aerosols in the context of the
overall Arctic cloud-radiation interactions. Specifically we address the
issue of how the characteristics of cloud condensation nuclei (CCN) and
ice freezing nuclei (IFN) affect the radiative properties of the Arctic
clouds, through the amount and phase of condensed water and the size and
shape of the condensed particles.

The sensitivity of the Arctic radiation balance to changes in cloud
optical properties that could be attributed to aerosols has been
examined theoretically by Curry and Ebert (1990; 1992) and Curry et al.
(1993 a), in terms of the cloud water droplet effective radius (re). The
effective radius is defined to be the average droplet radius weighted by
the droplet cross-sectional area, and is the moment of the dropsize
distribution that is most directly related to the radiation extinction
cross section of the drops. An increasing amount of CCN would act to
reduce the values of re for the liquid water clouds.

The modeled sensitivity of the annual cycle of surface radiation fluxes
over the Arctic Ocean to changes in re shows that the incident surface
shortwave flux decreases with decreasing values of re. As drop sizes
become smaller, cloud reflectivity increases, reducing the incoming
shortwave flux. The impact of changing re is not limited to the
shortwave flux, as decreasing values of re also results in an increase
in downward longwave flux, since the emissivity of Arctic clouds is
significantly less than unity and thus sensitive to drop size (Curry and
Herman, 1985 b). The modeled effect of changing re on the net surface
radiative flux (the sum of the net shortwave and longwave fluxes) over
the Arctic Ocean has been shown to be complex, with a pronounced annual
cycle. During winter the longwave effects dominate in the absence of
solar radiation, while the shortwave effects dominate during summer. At
large values of re, the surface incoming longwave flux will decrease and
the shortwave flux will increase. As re increases, however, the longwave
perturbation becomes increasingly important since the clouds become less
opaque, affecting a larger part of the annual cycle than does the
shortwave perturbation. The shortwave perturbation is dominant at small
values of re, since the summertime clouds have a longwave emissivity of
nearly unity at the smaller values of re, while the longwave emissivity
varies negligibly as re is decreased. Therefore, it was hypothesized by
Curry and Ebert (1990) that annually-averaged net surface radiation flux
would increase for both an increase and decrease in re.

Albrecht (1989) and Twomey (1991) have further suggested that not only
would drop size decrease as a result of increased CCN, but the total
liquid water content of the cloud would also increase due to decreasing
efficiency of the precipitation process. A modification to droplet
particle size associated with altered CCN characteristics could,
therefore, alter the lifetime of the clouds and the overall cloud cover
in the Arctic.

Ice nucleation plays a critical role in determining the amount of
condensed water and the size and shape of the condensed particles. Ice
crystals have been observed at temperatures warmer than about -20 C,
indicating the importance of IFN. The phase of the condensate (liquid or
crystalline) depends on the characteristics of ice freezing nuclei. If
water drops freeze, their optical depth and other single scattering
properties will be altered. Since ice crystals grow much more rapidly
than liquid water drops at a given relative humidity and temperature,
more water will condense if ice nucleation occurs; however, the ice
crystals will also fall out of the atmosphere more rapidly due to their
larger sizes. The temperature at which an IFN nucleates an ice crystal
depends on the composition of the IFN and possibly its previous history
(i.e. whether it has been previously activated). From observations
reported by Curry et al. (1990) during April 1983 and 1986, it seems
that significant ice crystal nucleation routinely occurs at temperatures
as high as -15 to -20 C. Earlier observations by Witte (1968) described
one case with condensate that was predominantly liquid at temperatures
as low as -32 C during December 1967, and Jayaweera and Ohtake (1973)
found very few ice crystals at temperatures above -20 C during September
1971 and April 1972. Clearly, there is no simple relationship between
phase and temperature; the concentration, chemical composition, and life
history of IFN must be accounted for. It has been hypothesized that
anthropogenic aerosol has the potential to significantly impact the
amount of condensed water in the Arctic by modifying the ice nucleation
and thus the phase of condensed water.

An Arctic cloud-radiation-aerosol feedback mechanism has been described
by Curry (1993). A perturbation in the aerosol concentration alters the
cloud optical depth and thus the surface radiation flux and the surface
temperature. This results in a change in sea ice characteristics (i.e.
ice thickness and areal distribution, surface temperature and surface
albedo). These changes in sea ice characteristics, particularly the
surface temperature and fraction of open water, will modify surface
fluxes of radiation and sensible and latent heat, which will modify the
atmospheric temperature, humidity and dynamics. Modifications to the
atmospheric thermodynamic and dynamic structure will modify aerosol and
cloud properties, which will in turn modify the surface radiative
fluxes.

Incorporation of aerosols into a conceptual model of the Arctic cloudy
boundary layer and cloud-radiation interactions requires the following:

∑ measurements that document the impact of aerosol concentration on
cloud particle size distributions and cloud optical properties;

∑ concurrent measurements of atmospheric temperature, phase of
condensate, and concentration and composition of aerosol particles to
assess the impact of aerosols on the phase transition between liquid and
crystalline cloud particles;

∑ improved measurements of atmospheric humidity at cold temperatures to
assess the water vapor feedback;

∑ measurements and models of the radiative properties of cloud/aerosol
mixtures;

∑ measurements and models of the interactions among clouds, aerosols,
radiation, and boundary layer turbulence that influence the life cycle
of low-level boundary layer clouds.

A comprehensive treatment of the effects of atmospheric chemical
processes on the microphysical and optical properties of Arctic clouds
must also consider the role that clouds serve in the atmospheric cycles
of CCN and IFN. Clouds are thought to provide important removal pathways
for these particles through gravitational collection by
collision-coalescence and enhanced Brownian motion (Hoppel et al. 1990;
Hudson and Frisbie, 1991; Hudson 1993 a, b), and chemical reactions in
cloud droplets or on the surface of ice crystals may alter the
nucleating properties of the particles. Understanding the sources,
atmospheric transport and transformation pathways, and removal processes
of the subset of the total aerosol population that acts as CCN and IFN
is thus a necessary component of studies of atmospheric chemistry and
Arctic clouds.

5.2.4.1 Sources and Atmospheric Transformations

Some aspects of the seasonal cycle of aerosol concentrations in the
Arctic are fairly well understood. In particular, much attention has
been focused upon Arctic haze, which results from the winter/early
spring transport of pollutants from North America and Eurasia, and is
identified with the observed March peak in concentration of condensation
nuclei (CN, including both condensation nuclei and ice freezing nuclei).
During the Arctic haze season, the position of the polar front, the
stably stratified air mass, and the high emissions rates of combustion
products in source regions combine to create conditions which are
effective in transporting pollutants poleward, and are ineffective at
removal of such pollutants via mixing processes/surface sinks and/or
precipitation. This explanation of the high winter/spring concentrations
of CN has been verified through tracer studies, which confirm the
presence of metals and other species associated with anthropogenic
pollution (Harriss et al. 1992), and trajectory analyses which show
that, on occasion, direct routes from Europe to the Arctic exist
(Heintzenberg et al., 1986).

Despite the many intensive field programs that have been mounted to
identify the chemical composition and physical and optical
characteristics of the Arctic haze (Barrie, 1986), little work has been
done in relating this aerosol to the microphysical properties of clouds.
During the haze season, the cold temperatures and dry conditions produce
ice clouds, including the phenomenon known as diamond dust. In this
season, the characterization of the subset of the total aerosol
population that are active as IFN is of most relevance. During warming
in late spring, mixed-phase clouds may form; in warmer seasons, then, it
is necessary to also characterize the CCN population. Heintzenberg et
al. (1986), Shaw (1986), and Curry and Ebert (1990) have suggested that
the advective introduction of Arctic pollution aerosol may give rise to
a different population of cloud condensation nuclei (CCN) and thus
modify cloud water nucleation processes in the Arctic.

An annual minimum in CN occurs during summer and late fall. During this
time, transport of aerosol and aerosol precursors (of natural and/or
anthropogenic origin) is the likely dominant source of particulate
matter in regions away from coastal zones. Near coastal regions, and
also in leads that open in the ice during early summer, biological
production of dimethylsulfide (DMS) provides a source of reduced sulfur
to the atmosphere; in leads, the productive season is limited by
available nutrients and hence is short. Organic carbon species are
suspected to contribute significantly to the CCN population in some
regions (Novakov et al., 1993); it may be important to quantify the
contributions of semivolatile organics to the CN and CCN populations in
the Arctic summer, since other sources of particulate matter are so low,
and the cold temperatures may lead to increased partitioning of the
semivolatile species to the particulate phase. The effects of soot on
the snow albedo can be significant (Clarke and Noone, 1985). There have
also been reports of stratospheric intrusions into the Arctic
troposphere; the relative importance of a stratospheric source of
particulate matter, compared with local and long-range transport, is not
known.

The relevant scientific questions to be addressed, with respect to
sources and atmospheric transformations of aerosol, are as follows:

∑ What processes produce CCN and IFN in the Arctic?

∑ What are the relative contributions (throughout the year, and as a
function of altitude) of local production in the Arctic vs. long-range
transport to CCN and IFN, and of the various sources (biological,
anthropogenic, and stratospheric)?

∑ What are the chemical composition and size distributions of CCN and
IFN?

∑ What processes alter the effectiveness of Arctic CCN and IFN?

The approach requires sampling of cloud droplets and ice crystals in
order to allow determination of the chemical and microphysical
properties of the aerosol particles that actually act as CCN and IFN in
Arctic clouds. This approach, together with simultaneous measurements of
size-dependent particle chemical composition and CCN and IFN spectra,
will allow a quantitative connection to be established between activity
spectra and the characteristics of the aerosol particles. Such an
approach is necessary to link atmospheric chemical models with cloud
models for an improved understanding of how these interactions occur and
what controls them.

In order to evaluate relative importance of biological, anthropogenic,
and stratospheric sources of particulate matter, local budgets of
aerosol and aerosol precursor species must be constructed. In the
winter, biological sources are expected to be absent. In the early
summer, during the short biological productivity season, local sources
of DMS may play a significant role. In later summer, transport of DMS
from productive regions near coasts may augment long-range transport
from industrial regions. In all seasons, stratospheric intrusions may
provide periodic injections of sulfate aerosol. Methods for quantifying
each of these contributions must be employed and appropriate
measurements made to determine sources of the observed aerosol.

5.2.4.2 Activation of CCN and IFN

Only a fraction of the total population of aerosol particles are
potential CCN/IFN, and not all potential CCN/IFN actually nucleate
droplets/crystals in ambient clouds. The size and chemical composition
of individual particles determines which ones will activate and grow to
become droplets or crystals. The supersaturation spectrum (IFN activity
spectrum), describes the number concentration of particles that activate
to form droplets (crystals) at a given water vapor supersaturation
(temperature). As described above, a quantitative connection between the
supersaturation (activity) spectra and the characteristics of the
aerosol particles is needed. Similarly, a quantitative connection
between these spectra and the number concentration of cloud
droplets/crystals is needed as another link in the chain connecting the
aerosol particles and the optical properties of the clouds. However,
other factors, such as entrainment and mixing of subsaturated air from
outside the cloud, can affect the number concentration and size
distribution of cloud droplets/crystals.

The key scientific questions concerning the activation of CCN and IFN,
and the formation and growth of cloud droplets and ice crystals, include

∑ What is the effect of the relative abundance of CCN and IFN upon the
phase of the cloud particles?

∑ For liquid water clouds, what is the relationship between the droplet
size distribution and the size and chemical composition of the CCN?

∑ For ice clouds, what is the relationship between the crystal habit and
size distribution and the size and chemical composition of the IFN?

∑ What is the relationship between cloud optical properties and CCN and
IFN abundances?

The approach to the above questions will require measurements of the
size and chemical composition of the CCN and IFN (as in the previous
section) and the microphysical properties of the cloud droplets and ice
crystals, combined with models of the microphysics and dynamics of the
clouds that were sampled. To address the first question, the
measurements need to be performed over a wide range of ambient
temperatures. The second and third questions require evaluation of the
effects of other processes, such as entrainment and mixing, that can
influence the size distribution of the cloud particles. The fourth
question also requires measurements of radiative fluxes within, above,
and below the cloud.

5.2.4.3 Sinks

It is accepted that CCN and IFN have an important impact upon the
formation and properties of clouds; this may be particularly the case in
the Arctic, where, due to the stable conditions, cloud entrainment
effects are of less importance in determining the drop size
distributions in Arctic clouds than are background air chemistry and CCN
characteristics (Curry, 1993). Cloud processes, in turn, will have an
impact on the CCN and IFN populations, by removing number and mass or by
increasing particle sizes by mass addition that occurs during
aqueous-phase gas-to-particle conversion (Hegg et al., 1984; Radke and
Hobbs, 1969). Recent work has demonstrated the importance of cloud
processing in determining observed aerosol concentrations. Baker and
Charlson (1990) employed a simple model to demonstrate the possible
existence of two stable steady states of \[CCN\] in the atmosphere under
certain particle source rate and drizzle sink strength conditions.
Ackerman et al. (1993) present a simulation of the stratus-capped marine
boundary layer (MBL) that shows the MBL structure to weaken and the
cloud to dissipate when the source of fresh particles cannot balance the
sinks due to drizzle removal.

An increased amount of pollution aerosol in the Arctic would increase
the amount of cloud water by decreasing the production of precipitation
in clouds and thus extending the cloud lifetime. A positive feedback
loop between aerosols and clouds is postulated (Curry, 1993), whereby
the larger aerosol concentration results in increased cloud water
content, which increases the in-cloud production of aerosol mass (by
gas-to-particle conversion processes) and decreases the cloud scavenging
of aerosols, resulting in a net increase in cloud condensation nuclei
beyond the original input. Such a mechanism would be most apparent in
the winter/spring months, when the Arctic aerosol is most heavily
influenced by advected pollution. This hypothesis also hinges on a
relative decrease of IFN in polluted air, due to deactivation by sulfate
(Borys, 1983; Borys, 1989).

Persistent stratus clouds and fog and drizzle are observed in the summer
Arctic; summer is also the time of year when total CN concentrations are
quite low, suggesting that the clouds lead to aerosol scavenging (Radke
et al. 1989; Hudson and Frisbie 1991; Ackerman et al. 1993; Hindman et
al. 1992, 1994). Reasons for the low observed CN concentrations may be
the strength of the aerosol removal rates and weak sources of
particulate matter in the region. We must ask, however, how such
persistent cloud decks can occur in the absence of plentiful CN. There
are clearly intriguing possibilities for interesting aerosol / cloud
feedbacks, including those suggested by the papers referenced above.

The relevant scientific questions to be addressed, with respect to sinks
of aerosol, are as follows:

∑ What are the removal mechanisms for aerosol particles in the Arctic?

∑ What is the importance of sedimentation (for diamond dust) and
precipitation (for ice and liquid water clouds) in determining the CCN
and IFN populations?

The experimental approach requires simultaneous measurements of total
aerosol, CCN and IFN above, within, and below cloud to assess the size-
and chemistry-dependent removal rates for these species. Such
measurements will be an integral part of the assessment of the budgets
of aerosol and aerosol precursor species, which are suggested in the
approach to other aspects of the program as well.

5.3. Field measurements

5.3.1 Collaborative experiments

The FIRE III Arctic Stratus Experiment will benefit from strong
interactions with two other field programs planned for the Arctic in the
same time frame. ARM (the Atmospheric Radiation Measurements Program of
the U. S. Department of Energy) designed to make radiation measurements
in the Arctic for up to a decade, and SHEBA, a multi-agency U.S. program
that plans to put a camp on the ice pack for about 15 months. These two
programs are briefly described below.

5.3.1.1 SHEBA

SHEBA (the ™Surface Heat Budget of the Arctic∫ program) will conduct a
one-year field program over the Arctic Ocean pack ice. A unique aspect
of the proposed field program is the concurrent measurement of
characteristics and physical properties of the atmosphere, sea ice and
upper ocean, including the fluxes that occur at the air-ice, ice-ocean,
and air-ocean interfaces. Plans call for integration of the surface and
aircraft measurements with satellite observations and model analyses, on
three different scales:

1\) a scale of about (10 km)2, where we will make in situ and
ground-based remote sensing measurements. This scale corresponds to an
AVHRR footprint.

2\) a scale of about (100 km)2, the scale of GCM grid box, using
aircraft, helicopter and autonomous underwater vehicle. This scale is
similar to the SSM/I footprint and the highest spatial resolution of the
ISCCP cloud and radiation analysis.

3\) the full extent of the Arctic Ocean, including surface buoys,
satellite sensors, and the synoptic meteorological station network.

To make in situ and ground-based remote sensing measurements over the
Arctic Ocean, a camp on floating sea ice is an essential platform. For
reasons of logistics, the southern Beaufort Sea is the most likely site
for the camp. Plans call for making (nearly) continuous measurements
where possible, so that the co-evolution of the coupled atmosphere / sea
ice / ocean system can be documented and understood.

SHEBA has adopted two primary goals:

\(1\) Develop, test and implement models of Arctic air-sea-ice processes
that demonstrably improve GCM simulations of the present day Arctic
climate, including its variability.

\(2\) Improve the interpretation of satellite remote sensing data in the
Arctic so that satellites can assist effectively in the interpretation
of the Arctic climate system and provide reliable data for model input,
model validation and climate monitoring.

To achieve these goals, the following specific issues will be addressed
by SHEBA in collaboration with FIRE III:

Surface energy and mass budgets:

∑ surface fluxes of radiation, sensible and latent heat, and conduction
in the heterogeneous ice cover

∑ top and bottom surface mass balance, including bare ice, snow, melt
ponds, and pressure ridges

∑ internal heating, melting, and absorption and transmission of
shortwave radiation within the ice

∑ evolution of the ice thickness distribution and properties of leads
and floes

∑ impact of clouds on surface temperature, albedo, and fluxes of
radiation, sensible heat, and latent heat

Arctic clouds:

∑ formation, maintenance, and dissipation processes

∑ cloud/atmosphere boundary layer interactions

∑ cloud macrophysical and microphysical properties

∑ cloud microphysical interactions with atmospheric chemistry

∑ cloud radiative properties

∑ response of clouds and atmospheric temperature, humidity, and wind to
changes in surface state and temperature

Upper ocean interactions:

∑ response of upper ocean temperature and salinity to fluxes from sea
ice and leads

∑ horizontal exchange of heat and salt beneath the ice cover

∑ disposition of shortwave radiative energy absorbed by the upper ocean

∑ impact of ocean heat flux on ice mass balance

Coupled sensitivity of atmosphere, ice, and ocean:

∑ mutual adjustments of the upper ocean, ice cover, and atmosphere to
forcing functions and perturbations.

In addition to surface in situ measurements, SHEBA anticipates making
extensive use of passive and active ground-based remote sensing. New
technology, including millimeter (cloud-detecting) radar, lidar,
integrated sounding systems, and Fourier Transform Infrared Radiometers
will provide unique time series data on atmospheric and cloud
properties. One or more research aircraft and a helicopter will be
needed. A tethered balloon has been suggested for making cloud physical
and radiation measurements in boundary layer clouds. If available, a
profiling sonar, mounted on a submarine or autonomous underwater
vehicle, could provide invaluable areal coverage of the ice thickness
distribution and lead characteristics.

The SHEBA field experiment is planned to begin in April 1997 and to
continue through August 1998.

5.3.1.2 ARM

The U. S. Department of Energy\'s Atmospheric Radiation Measurements
Program (ARM) is intended to improve our understanding of processes that
affect atmospheric radiation and the parameterizations of these
processes in climate models. Data will be collected over a period of up
to a decade, at several sites around the world. One of these is the
so-called ™North Slope of Alaska and Adjacent Arctic Ocean∫ (NSA/AAO)
site, which is planned for implementation beginning in 1996 or 1997.
ARM\'s goals and its NSA/AAO siting strategy clearly fit very well with
FIRE III\'s plans to make measurements of Arctic clouds and radiation.
ARM is developing a portable, semi-autonomous measurement system called
an ™ARCS∫ (Atmospheric Radiation and Clouds Station), which will become
available starting in 1995; several units will be manufactured, and
plans call for one to be deployed in the Arctic, at the SHEBA ice camp.
A summary of the observations and possible instruments planned for the
ARCS is given in Table 5.3.1.

Table 5.3.1: ARCS Observations and Possible Instruments.

**Observations Possible Instruments**

[Surface Radiation]{.underline}

Broad-band Solar and IR radiometers

Spectral IR radiometers

Direct Rotating shadow band radiometer

Sun photometer

[Cloud properties]{.underline}

Location, structure, phase LIDAR

Millimeter radar

Sky coverage Whole sky imager

Optical depth, emissivity Rotating shadow band radiometer

Total direct, diffuse radiometer

Sun photometer

Zenith view 10 micron radiometer

Liquid water path Microwave radiometer

[Water vapor]{.underline}

Amount Microwave radiometer

Vertical profiles Rawinsonde

[Aerosols]{.underline}

Optical depth Sun photometer

Rotating shadow band radiometer

Total, diffuse, direct radiometer

Vertical profiles LIDAR

[Boundary layer structure]{.underline}

Temperature, wind, 915 MHz Profiler with RASS

and humidity profiles Rawinsonde

[Surface meteorology]{.underline}

Wind speed and direction, Surface weather station

temperature, pressure, humidity, precipitation rate

5.3.2 When and where?

Clearly FIRE, SHEBA, and ARM can each gain enormously by coordinating
their research plans, without compromising their individual research
goals. This argues strongly for making the FIRE measurements in the
vicinity of the SHEBA ice camp, in the southern Beaufort Sea. Of course,
the camp will be in place for about 15 months, and FIRE cannot possibly
stay in the field for such a long time. This raises the question of
which season or seasons would maximize the likelihood that we will
achieve our scientific goals. Logistical considerations suggest that the
research aircraft would be based in either Barrow or Fairbanks. This
would allow validation flights over the ARM North Slope of Alaska site,
which would provide another useful ™ground truth∫ location for the
satellite remote sensing efforts. Additionally, in late April and early
May, the coastal regions are the most likely place for lead-induced
plumes to develop, which suggests at least some missions away from the
SHEBA ice camp.

Arguably, summer is most important, since the surface characteristics
are sensitive to energy flux perturbations of even a few W m-2. Getting
the summertime clouds wrong in a climate model would lead to major
errors in the Arctic energy budget. Satellite-based remote sensing of
summer cloud properties is very difficult. Perhaps the biggest unknown,
however, is autumn clouds. No Arctic cloud measurements have been made
in autumn. On the other hand, spring is when the most interesting
cloud/chemistry interactions take place, and the wintertime stable ice
crystal clouds have been very poorly observed up to now.

We envision an 8 - 10 week campaign, starting about April 15, 1997. This
is in the seasonal transition period between ice crystal clouds and
water phase clouds, so that both types of clouds may be observed during
the early phase of the experiment. In addition, ™Arctic haze∫ pollution
aerosol is still lingering. By the end of May, the clouds are mostly in
the liquid phase, and DMS production is starting to increase. By
mid-June, the summertime stratus is fully established.

The proposed schedule would allow us to capture the transition between
ice / liquid clouds, as well as the seasonal changes in cloud-chemistry
interactions, thus maximizing the scientific opportunities available to
a single field campaign.

5.3.3 Measurement strategies

The difficult scientific questions raised in Section 5.2 involve the
coupling of ocean transports of heat and ice with atmospheric transports
of heat, water vapor and trace substances. Complicating this coupling
are smaller scale boundary layer dynamical phenomena in both the
atmosphere and ocean that modify the characteristics of clouds and sea
ice and modulate the dominant radiative energy exchanges. To diagnose
the energy fluxes in the Arctic system requires high space and time
resolution measurements of the changing properties of the surface,
atmosphere and ocean; but to determine the impact of these exchanges on
the larger atmospheric and oceanic circulations requires integrating
over basin-wide and annual to interannual scales. No single measurement
system measures all the quantities needed or covers the whole range of
scales that must be observed. Moreover, we must observe a complete
annual cycle to understand how different processes change relative
importance with season.

The kinds of cloud and radiation observations that FIRE III can provide
from aircraft and surface instrumentation contribute key elements to
answering the scientific questions but cannot stand alone. However, a
unique opportunity to increase our understanding of clouds, radiation,
boundary layer dynamics and atmospheric chemistry in the Arctic has
arisen by coordinating the FIRE III experiment with the additional
surface and atmospheric measurements at and near the ARM site and the
SHEBA ice camp and with comprehensive satellite observations before,
during and after the main observing period. The surface set of remote
sensing and in situ instruments can document the surface and atmosphere
at the ice camp location, with limited areal coverage of sea ice
properties and boundary layer attributes. Aircraft campaigns can be used
to provide in situ probes of clouds and aerosols and the vertical
distribution of radiation and to investigate the spatial structure of
particular cloud events. Satellite remote sensing provides the
integration of these smaller scale, but more detailed, surface and
aircraft observations to cover the whole Arctic basin and to compare the
particular year of measurements with other years. Only the surface and
aircraft can access the small boundary layer and cloud process scales
and only the satellite can cover the larger atmospheric circulation
scales.

An additional crucial purpose for coordinated observations from these
different systems is that our ability to measure some attributes of
clouds and radiation is still not perfected. Hence, the instrumentation
on the surface and in the aircraft is selected to provide alternative
measures of some key quantities by these systems and to verify
inferences made from satellite remote sensing. In the next sub-sections
(5.3.4 - 5.3.6), the specific quantities that must be measured and some
instruments that can measure them are outlined.

The satellite observations provide an integration of the variations of
basic atmospheric, cloud and surface parameters over larger space-time
scales; however, the key method for studying the aggregation of the
smaller scale processes to the scales at which they influence the
climate is by a series of model diagnostic studies (Section 5.4). The
strategy is to use different kinds of models representing different
scales of behavior and to acquire comprehensive datasets that can
provide a variety of model testa and constraints. Hence, the
coordination of surface, aircraft and satellite observations is also
designed to span the large range of space and time scales and to provide
a similar richness of detail and completeness of coverage as do models.

The practical aspects of the integration and coordination of these
observations involve using the aircraft and scanning surface
measurements, which can cover larger spatial domains, to link the
surface observations at the ARM and SHEBA sites (point-like but with
longer time records) with the satellite coverage of the whole Arctic
over many years: most satellite instruments available during SHEBA and
FIRE III will have operating for more than five years.

5.3.4 Instruments

In order to accomplish our scientific objectives, as outlined above, it
will be necessary to make a wide variety measurements, and these will be
made in part from the SHEBA ice camp or other surface sites, in part
from aircraft, and in part from satellites. In this subsection, we
outline the measurements needed according to the quantity being
measured. In the following subsections, we discuss aircraft, surface,
and satellite platforms separately. Finally, we discuss the integration
of these measurements into a coherent picture of the physical processes
under study.

We have identified measurements and corresponding instruments that can
satisfy our scientific requirements. In the discussion below, the status
of each is summarized with a code number, defined as follows:

Code: 1 Currently operational system

2Partial development has been achieved

3Full development has been achieved

4Not currently possible

5.3.4.1 Microphysics

Instrumentation that has been used for measuring cloud microphysical
properties in previous FIRE programs have proven to be deficient.
Hot-wire probes used for in situ measurements of cloud liquid water
content and optical (PMS) instruments used to measure drop spectra have
well-documented uncertainties (e.g. Baumgardner et al. 1985; Cooper
1988). Use of cloud microphysical properties derived from these
instruments can result in significant errors in our interpretation of
cloud, radiative, and turbulent processes in boundary layer clouds. The
deficiencies in aircraft measurements of cirrus cloud properties using
PMS probes during FIRE (Heymsfield et al. 1990) were illustrated by
their discrepancies with remote measurements of cirrus cloud
microphysical properties (e.g. Spinhirne and Hart 1990, Wielicki et al.
1990). It appears that PMS probes cannot adequately measure small ice
crystals, which are critical for determination of the radiative
properties of cirrus clouds (e.g. Sassen et al. 1990; Wielicki et al.
1990). In FIRE III we plan to take advantage of recent technological
advances to make substantially improved cloud microphysical
measurements, and to encourage further testing and improvements of these
instruments.

A digital holographic imaging system has been described by Lawson and
Cormack (1993) that reconstructs images of cloud particles from digital
holograms and can measure the size, shape, spacing between, and
concentration of cloud particles, and also the scattering phase
function. This instrument has been tested in the laboratory and also on
aircraft. A new instrument that is called a II-Nephelometer is being
build by Lawson under contract from NASA/LaRC. This instrument will be
of particular utility for aircraft measurements of ice crystal and
mixed-phase clouds. This instrument will fly on board either the NCAR
C-130 or the Canadian Convair 580 aircraft in the Arctic during the
Canadian BASE experiment in Fall 1994.

A cloud droplet spectrometer has been developed by Lawson and Cormack
(1993) that uses a linear photodiode array to ensure the light
forward-scattered from an ensemble of drops. Since this system does not
require optical filters, the raw scatter light intensity measured by the
cloud drop spectrometer gives significantly more accurate measurements
that PMS probes, particularly at liquid water concentrations greater
than 1 g m-3.

Gerber (1992) has described a new instrument, the PVM-100A, that has
been designed to measure cloud liquid water content and integrated
surface area of the droplets. Measurement of both these quantities is of
particular utility for radiative transfer calculations. This instrument
has been adapted for aircraft, and was flown on the University of
Washington C-131A aircraft during ASTEX, during which its performance
was judged to be very good.

∑ Ice water content (IWC) meter2

This is a difficult measurement; in the past it has been estimated based
on particle size spectra measurements discussed later. There are two
candidate instruments to directly measure this quantity: a counterflow
virtual impactor, where ice particles are collected through an inlet
tube, evaporated, and the vapor density of the air is measured; and a
combined dielectric capacitance/evaporator device, in which a dielectric
sensor detects the change in capacitance of a parallel plate capacitor
as a particle passes between the parallel plates.

∑ Ice crystal size spectra n (diameter d) and IWC (d)1, 2

At sizes above about 50 to 1000 micron, Particle Measuring Systems
digital probes can be used. At sizes below the PMS detection thresholds,
we can use video ice particle samplers and replicators, where ice
particles are collected on a liquid coated belt and either photographed
or preserved. Digital holography uses a high powered pulsed laser diode
is used to cast a shadow on a CCD camera. Information contained in the
resulting diffraction patterns is numerically processed to reconstruct
the size and shape of the particles in the sample volume.

∑ Ice crystal habit

Crystal shapes can be identified from the PMS probes above about 150
microns and below these sizes from the video ice particle samplers,
replicators as well as direct collection of particles on oil coated
slides. The digital holographic method holds potential for an electronic
means to decipher the habits of small particles.

∑ Liquid water content (LWC)1, 2

ASTEX highlighted uncertainties in both the liquid water content and
effective radius of water clouds as determined using the FSSP probe.
While droplet sizes were previously measured using FSSP probes during
the summertime Arctic Stratus Experiment (Herman and Curry, 1984), these
measurements must be re-evaluated using improved cloud probes for cloud
particle volume and effective radius. Accurate knowledge of cloud
particle radius is needed to properly model the relationship of
shortwave and longwave cloud optical depths, as well as the relationship
of cloud liquid water to cloud visible optical depth.

5.3.4.2 Chemistry

Chemical species measurements from aircraft should include ozone, CO,
methane, NOx, NOy, SO2, dimethyl sulfide, and collection of aerosols by
filters, preferably size-resolved (e.g., using cascade impactor
sampling), and collection of cloud water for later laboratory analysis
of chemical species (e.g. nitrates, sulfates, and chloride, sodium and
calcium ions). Information on air-mass histories can be obtained by
sampling air in cannisters for later analysis of nonmethane
hydrocarbons, chlorofluorocarbons, and other long-lived trace species.
Similarly, radon collection and analysis can provide estimates of when
an air-mass was last in contact with land. Carbon monoxide is also
useful as a tracer of anthropogenic impact. Fast-response measurements
of ozone, as with a chemiluminescent sensor (e.g. Pearson, 1990), can be
useful as a tracer for estimating entrainment and mixing even in cloudy
regions, since ozone is negligibly soluble in cloudy air, and is
conserved on time scales of days in regions that are not heavily
polluted. The ozone budget in the arctic region is of particular
interest, since in the summer photochemistry could lead to either
production or destruction of ozone, depending on ambient levels of NOx,
while in the winter, there would be no photochemical term.

In addition to total aerosol measurements, the fraction of aerosol
particles which are active as CCN should be determined (Hudson, 1993 a,
b); an instrument that has been developed and successfully flown on
aircraft is the continuous CCN spectrometer of Hudson (1989). Ideally,
the CCN activity spectrum should be linked to size and chemical
composition of the particles; however, such measurements have not yet
been integrated into a single protocol. An effective strategy might be
to coordinate CCN spectrum measurements with other aerosol chemistry
measurements so that the two data sets can be compared at similar time
and spatial scales.

The measurement of IFN is quite difficult, due in part to the
multiplicity of mechanisms which can produce ice nuclei in the
atmosphere (Vali, 1985); relatively few measurements of natural IFN
exist. Some new systems are currently being developed; the method
proposed by Rogers (1988), for example, is sensitive to deposition
(sorption), condensation-freezing and immersion-freezing mechanisms, and
may be appropriate for the conditions encountered in FIRE III.

∑ Cloud condensation nuclei (CCN)1, condensation nuclei (CN)1,
Ice-forming nuclei (IFN)3,4

∑ CCN2 and IFN4 composition and size distribution

∑ Ozone1

5.3.4.3 State and Other Meteorological Parameters

In the Arctic, the magnitudes of turbulence intensity, as well as latent
and sensible heat fluxes, are typically smaller than in the convective
boundary layers of other climate regimes. This puts more stringent
requirements on the accuracies of high-rate air velocity, temperature
and humidity measurements. Furthermore, since the transport is typically
in thin layers, the eddy structures are small. Thus, higher frequency
fluctuations need to be measured. Since most of the turbulence
measurements will be in cloud, it is essential that accurate in-cloud
temperature and humidity measurements be obtained.

A new fast-response airborne thermometer designed to avoid the problems
of sensor-wetting in clouds has been shown during flight tests to be up
ten times faster than sensors currently in use (Lawson and Rodi 1992).
The probe has been flown successfully in field programs on the NCAR King
Air, and recently, on the German DLR Falcon research aircraft. It is
anticipated that the thermometer will provide new insights into the
thermal structure of arctic clouds.

5.3.4.4 Radiometric Measurements

We need better instruments to measure the radiative properties of the
clouds, including the cloud absorption coefficient. Because of the small
net radiation in the Arctic, current short and long wave radiometers are
not adequate. We need in situ measurements of ice particle scattering
phase function, obtained in such a way that the ambient orientation of
the particles is not disturbed. In aircraft measurements of radiative
properties, sampling error is always one of the biggest problems,
however, so that improved instruments do not necessarily reduce the
total error appreciably.

∑ Solar flux radiometers1

Solar fluxes are measured using hemispherical field of view radiometers
mounted in zenith and nadir ports of the aircraft. Spectral coverage
from 0.3 to 2.8 microns.

∑ Infra-red flux radiometers1,2

Infra-red fluxes are measured using hemispherical field of view
radiometers mounted in zenith and nadir ports of the aircraft or
alternatively on a rotating arrangement on the wing of the aircraft
(Valero et al. 1993). Spectral coverage from 3.7 to 50 microns (Ackerman
et al. 1990; Stephens et al. 1993). A significantly more accurate system
that uses liquid nitrogen cooled black body reference, has been
developed in a ground/laboratory version. Adaptation of this new
instrument to aircraft operation is the next logical development.

∑ Total direct diffuse radiometer (TDDR)1

This instrument measures fluxes in seven spectral channels in the solar
region of the spectrum (Valero et al. 1993). Two scanning shadow arms
block different sections of the sky. An inversion process allows the
retrieval of ™sky maps∫ that define the hemispherical radiation field as
a function of wavelength, direction, and power. Also direct and diffuse
fields are measured, optical depths are measured from the direct solar
beam.

∑ Spectral infra-red intensities radiometer1

A narrow field of view (FOV=6 to 60 milliradians) infrared radiometer to
remotely measure cloud-top brightness temperatures and to retrieve cloud
optical depths (King et al., 1992). Bandpasses can be chosen between 4
to 50 microns has been generally used with spectral bandpasses of 3.7,
6.7, and 10.5 microns have been used in the past.

∑ Spectral radiometers (l, q,\...)1

∑ Interferometer (IR)1

∑ Microwave Radiometers1

∑ Nephelometer3

5.3.5 Aircraft measurements

Aircraft in FIRE III will play several important roles:

1\. Provide in situ measurement of cloud microphysical variables (e.g.
phase, size distribution, total water content), cloud thickness, and
radiative properties and fluxes both in and above cloud, the turbulence
and large-scale circulations in the boundary layer, as well as
chemistry.

2\. Measure both horizontal variability and vertical structure.

3\. Characterize surface properties such as surface radiation
temperature and roughness, ice properties, and albedo.

These measurements will be used to validate remote measurements from
satellites and overflying aircraft (e.g. the ER-2 or the German
high-altitude aircraft), to extend to larger spatial scales the
single-point long time series measurements from the SHEBA site, and to
provide in situ measurements for ground-based remote sensing by lidars
and radars.

The aircraft will also be used for studying the impact of leads on the
overall surface energy budget, and on cloud properties and distribution
that arise through lead augmentation of the water content in the
boundary layer and by injection of chemical species which may generate
CCN (e.g. DMS).

These goals can be met by flying horizontal traverses from several tens
to several hundred kilometers across the Arctic ocean, below, within,
between and above the stratus cloud layers. Interspersed among these
horizontal legs, vertical profiles can be flown to document the vertical
structure. The legs below cloud can be used to document the
upward-looking radiation sensors at the SHEBA site, to measure sub-cloud
fluxes and mean quantities, including horizontal advection, and to
investigate the impacts of leads. The in-cloud legs can document the
microphysical structure of the clouds and measure the in-cloud
transports of sensible heat, water vapor and total water. The
above-cloud legs can be used for documenting cloud-top structure (with
lidar) as well as the in-cloud properties (with a suitable mm-wavelength
radar), long and short wave radiation, and effects of gravity waves and
horizontal variability in above-cloud thermodynamic variables.

An important aspect of aircraft measurement in FIRE III is observation
of cloud morphology and depth of the boundary layer. This can be best
accomplished by remote sensing with downward-looking lidar and radar. A
downward-looking lidar can measure cloud-top and height of the boundary
layer, and in the case of thin cloud such as diamond dust ice crystals,
may be useful for obtaining quantitative estimates of their vertical
structure. In addition, lidar can measure the geometrical thickness and
optical depth of aerosol layers. Water phase can be discriminated by
measuring the depolarization ratio of the particles. Some information on
particle size can be obtained by measuring extinction to backscatter
ratios using lidar in the 10 micron region (Platt and Takashima, 1987).

Short-wavelength radar can provide measurements of the thickness and
reflectivity of cloud layers. An example of this is the 3 mm
polarimetric Doppler radar that has been flown on the University of
Wyoming King Air. In addition to cloud reflectivity, this radar can
provide vertical motions in cloud, and may be able to provide
information on ice crystal habits. Such measurements are essential in
understanding both horizontal and vertical distributions of cloud
properties.

A surface contour radar (Parsons and Walsh, 1989) can provide
measurements of surface roughness, which might be useful in measuring
ice surface topology and thus distinguishing among types and ages of
ice, and open water.

Microwave and infrared radiometers may also be useful in measuring ice
type (e.g., age), in distinguishing melt ponds and leads from ice, and
the thickness of thin ice as in recently refrozen leads.

5.3.6 Surface-based measurements

Arctic stratus clouds, because of obvious logistical and environmental
hardships, are arguably the least studied of the radiatively important
cloud types. Modern ground based remote sensing instrumentation,
demonstrated in FIRE II and ASTEX, is now developed to the extent that
important cloud bulk and microphysical properties can be observed, even
in the harsh Arctic environment. The existence of multiple-layered cloud
systems, their vertical distribution and frequency of occurrence, their
diurnal variation, and their horizontal homogeneity all need to be
documented simultaneously with the surface radiation budget. Such
observations of cloud structure can be made with mm-wave radar and with
lidar, as clearly demonstrated in FIRE and ASTEX. Lidar is generally
more sensitive to the smallest particulates than radar but can suffer
greater attenuation than radar in optically thick clouds. Thus radar and
lidar provide complementary measurements of cloud properties.

The radiative importance of ™diamond dust∫ in Arctic stratus can be
assessed by using these active remote sensors along with measurements of
the surface radiation budget. While there are some differences between
the Arctic ™diamond dust∫ and cirrus, such clouds may offer the
opportunity to observe at close range clouds that in many respects are
similar to cirrus clouds. Thus, radar polarization techniques that show
promise in distinguishing plate-like crystals from needle-like crystals
and aggregates (Reinking, et al, 1993; Matrosov and Kropfli, 1993) will
be most effective at the close ranges that are possible in low level
Arctic stratus clouds.

Cloud microphysical properties have been studied in FIRE II and ASTEX
with combinations of ground-based remote sensors. Such studies will also
be useful in these Arctic stratus studies. Doppler radar and IR
radiometer measurements have been used in FIRE II to determine profiles
of ice crystal sizes, concentrations, and, thus, ice mass content. An
alternative method utilizes the radar/lidar backscatter ratio to
estimate similar cloud properties. Such techniques will be effectively
used in Arctic stratus ice clouds.

The scanning capability of some of the presently developed research
radars and lidars may provide an opportunity to map out inhomogeneities
in stratus clouds that are forced by fluxes of heat and moisture from
leads. Such measurements should be possible out to ranges of 10 to 15
km.

The Doppler radar capability that has proved to be so beneficial in
ASTEX will also be exploited in separating various mechanisms involved
in the evolution of Arctic stratus clouds. Of particular importance is
the diurnal variation and the vertical distribution of turbulence in
cloud.

The frequent occurrence of satellite overpasses in the Arctic region
will provide frequent opportunities to use the ground-based remote
sensors to validate some of the satellite-based atmospheric retrieval
techniques and to develop others. Satellite retrievals are especially
uncertain in upper latitudes and FIRE III will provide an excellent
opportunity to improve retrieved products from satellites, especially
those relating to cloud properties.

The Arctic component of FIRE III will be carried out as one or two
process-oriented studies performed in close coordination with SHEBA,
which will have its own extensive set of surface in situ sensors and
surface-based remote sensors. The long-term SHEBA data will provide an
excellent context for FIRE III and a standard set of background
measurements (albeit at one point) for the FIRE III intensive field
phase. SHEBA is still in the planning stages, so the exact suite of
surface-based measurements to be made is uncertain. Table 5.3.2 gives a
listing of some of the surface in situ instruments that have been
suggested for SHEBA. These measurements will provide continuous data on
surface energy fluxes (turbulent, radiative, and the net into the ice)
and background surface meteorology. Table 5.3.3 lists suggested
surface-based profiling remote sensors. These instruments will provide
standard atmospheric wind, temperature, and moisture profiles (from
conventional sondes and remote sensors), plus a variety of remotely
sensed cloud, aerosol, and (perhaps) chemical properties. This basic
suite of sensors will be roughly similar to those used at the
island-based sites in FIRE II - ASTEX.

Table 5.3.2: Suggested surface-based in situ measurements for the SHEBA
icecamp.

**[Instrument Parameter Height]{.underline}**

Sonic Anemometer Stress, Heat Fluxes 2 m

Pyranometer Solar Irradiance up/down 2 m

Pyrgeometer IR Irradiance up/down 2 m

Thermometer Atmospheric Temperature 1,2,4 m

Gradient

Thermometer Ice Temperature Gradient -1,-2,-4 m

Hygrometer Humidity 2 m

Barometer Surface Pressure 2 m

MicroBaro Array Pressure Fluctuations 2 m

Anemometer Windspeed, Direction 1,2,4 m

Chemistry and Aerosol To Be Determined 2 m

Sensors

Table 5.3.3: Suggested surface-based profiling/remote measurements for
the SHEBA icecamp.

**[Instrument]{.underline} [Parameters]{.underline} [Resolution/Max
Altitude]{.underline}**

915 MHz Profiler U,V,W, microturbulence 0.05/2 km 0.4/6 km

2 KHz (Acoustic) RASS Virtual Temperature 0.1/1.5 km

Minisodar U,V,W, microturbulence 0.005/0.1 km

Lidar Aerosol Scat. Coef. 0.01/10 km

Cloud Base Ht./Fraction

35 GHz Doppler Cloud Cloud Scat. Coef. 0.02/10 km

Radar Vertical Velocity

Microwave Radiometer Integrated Humidity - Vapor/Liquid

Fourier Transform High-Resolution - Interferometer: IR Downward IR
Spectrum

Fourier Transform High-Resolution - Interferometer: Solar Downward Solar
Spectrum

One focus of FIRE III and SHEBA is an investigation of the effects of
clouds on the surface energy budget of the Arctic ice pack. The basic
SHEBA instruments will document the energy budget explicitly. The remote
sensors provide information on the cloud properties that result in the
specific impact. The diagnosis of cloud microphysical properties from
the remotely sensed information is, with a few exceptions, indirect.
That is, the fundamental parameters measured directly by a cloud radar
are the backscatter coefficient and the radial velocity. This
information is obtained in an array of height bins with a time
resolution on the order of seconds. Just from this one sensor, a variety
of cloud properties can be determined by simple processing: cloud top
height, cloud base height, and in-cloud velocity variance profiles
(Uttal and Frisch, 1994; Gibson et al., 1993). Using models and / or
assumptions about cloud properties (e.g., adiabatic liquid water
profiles, constant droplet number density as a function of height), such
data can be processed to give information about cloud microphysical
properties such as droplet size (e.g., Frisch et al., 1994). When data
from various systems are combined, we can obtain more and more estimates
of cloud variables. For example, when microwave radiometer values for
integrated liquid water content are used as a constraint, then profiles
of liquid water content within the cloud can be obtained from the cloud
radar backscatter information. Thus, FIRE III (and SHEBA) must include a
carefully chosen set of surface-based remote sensors and must include a
research component of corresponding in situ cloud measurements (either
aircraft or tethered balloons) to develop the various synergistic
algorithms necessary for the experimental objectives.

5.3.7 Satellite measurements

Satellite remote sensing of cloud and atmospheric properties is required
to extend the space and time scales over which atmospheric and surface
characteristics and fluxes are described, assist in the interpretation
of cloud life cycles and sea ice evolution, validate models at larger
scales, and document climate and climate change in the Arctic. As part
of the field campaign, aircraft and surface measurements can be used,
not only to validate the satellite retrievals, but also to provide
inputs to more sophisticated analyses of the satellite data.

Currently available satellite instrumentation that observes the polar
regions includes the meteorological imagers (AVHRR, OLS and SSM/I) and
sounders (HIRS, MSU and SSM/T2) on the NOAA and DSMP satellites and the
ozone (TOMS) and radiation budget (SCARAB) instruments on METEOR. A
variety of atmosphere, cloud and surface characteristics are being
retrieved from these satellite measurements; some are more important
than others and some are more ™retrievable∫ from than others. The more
extreme conditions in the polar regions make these analyses more
difficult and less accurate. Quantities which are currently being
retrieved from satellite measurements are:

5.3.7.1 Atmospheric temperature and humidity, ozone abundance

The TIROS-N Operational Vertical Sounder (TOVS) on-board NOAA
polar-orbiting satellites provides estimates of layer-averaged
temperature and moisture as well as cloud conditions. However, its use
in the polar regions has been problematic because retrieval algorithms
do not take into account some unique features of polar surfaces and the
atmospheric structure. Improvements to the 3I (Improved Initialization
Inversion) method have been made (Francis, 1993), although additional
validation data are needed to more thoroughly assess its accuracy.
Already available are soundings from microwave instruments, SSM/T2 that
will be further advanced in the late 1990s by flight of AMSU and MHS.

5.3.7.2 Cloud amount, top temperature (height), optical thickness,
effective particle size, liquid water path and (liquid) precipitation

The ISCCP cloud climatology (Rossow and Schiffer 1991) is an on-going
analysis of weather satellite radiances to infer cloud amount, top
temperature and optical thickness. Preliminary analyses have been
performed to retrieve cloud particle sizes for liquid water clouds (Han
et al. 1994). Other studies using SSM/I radiances have retrieved column
water paths for liquid clouds (Greenwald et al. 1993); preliminary
estimates of ice water path have been made by combining SSM/I and ISCCP
(Lin and Rossow 1994). These methods are being revised to improve them
over polar regions; however, more detailed validation datasets are
required to determine whether the ISCCP results need to be augmented by
measurements from some of the other instruments discussed below to
produce an acceptable climatology.

Cloud amount has received the greatest attention by the satellite remote
sensing community, although it is radiatively ambiguous when used alone.
Cloud optical thickness is an additionally useful parameter but requires
information about the particle size, composition, and number density.
These parameters are more difficult to obtain, though not impossible if
enough spectral information is available. There remain significant
difficulties to overcome before these methods can be applied to ice
phase clouds and clouds over highly reflective surfaces. Another
possibility is to use the HIRS infrared channels to retrieve cloud
optical thickness and particle sizes for the thinner clouds. Retrieval
of some quantities, such as cloud base location, cannot be determined
directly from satellites.

5.3.7.3 Surface temperature and albedo

Within the Arctic study area over an annual cycle, we will encounter a
changing mixture of open ocean, newly-forming ice, thinner and thicker
multi-year ice with a variety of snow cover and surface roughness.
Because of the large spatial variations at relatively small scales of
the infrared and microwave emissivities of such surfaces, separating the
effects of surface temperature and emissivity variation from atmospheric
cloud and water vapor changes is very difficult. Although no single
sensor can cope with both the surface and atmospheric variations,
collections of combinations of visible, infrared and microwave
observations may allow for improved interpretations. The addition of
SSM/T2 observations of atmospheric temperature and water vapor profiles,
in particular, may allow the combination of HIRS, SSM/I to better
separate clouds and surface properties. Comparisons to higher resolution
surface and aircraft measurements will be crucial to learning how to
interpret the space-based measurements.

5.3.7.4 Shortwave and longwave radiative fluxes at the top of the
atmosphere and surface

Methodologies have been developed for the calculation of surface
radiative fluxes from physical parameters inferred from satellite
measurements, but their accuracy in the polar regions cannot be checked
because surface verification is generally lacking. Some valuable data do
exist from several field experiments, but these do not cover the
complete range of conditions or seasons that occur in the Arctic. A
critical issue for satellite-based surface fluxes is sub-pixel
inhomogeneity, particularly of the surface. For example, over a region
of say 30 km, surface temperature may vary by tens of degrees,
associated with the thermal characteristics of ice with different
thicknesses and open water and micrometeorological processes.
Utilization of the high resolution aircraft measurements of the surface
in conjunction with the coarser resolution satellite measurement will
allow us to begin to address the issue of sub-pixel inhomogeneity.

The accuracy of all of these satellite data analyses are challenged by
the much lower amounts (or lack) of solar illumination and much smaller
temperatures encountered in the Arctic. Moreover, the contrast between
surface and cloud reflectivities and IR emissions is much lower and the
surface small scale variability can be much larger. The accuracy
attainable with current analysis procedures is difficult to evaluate
because there is very little data available from any source against
which to compare the satellite results. The potential of combining
measurements from multiple sensors for obtaining some of this
information in the Arctic has not been explored because there is no way
to check the results.

The last half of the 1990s provides a good opportunity to improve
satellite analyses because new instruments are already or will become
available, including better microwave temperature and humidity sounders
(SSM/T2, AMSU, MHS), a few additional spectral channels on the
meteorological satellite imagers, and newer multi-angle and
multi-spectral instruments (like ATSR on ERS-1 and ERS-2 and POLDER on
ADEOS-1). Even more comprehensive instruments (like MODIS, MISR, AIRS
and EOSP) are planned for the EOS satellites towards the end of the
decade.

The key opportunity is to use the large range of remote sensing
instruments that can be flown on the NASA ER2 to link the large suite of
surface-based remote sensing instruments that can be fielded at the
SHEBA and ARM sites with the whole complement of satellite instruments
that will be observing the polar regions.

The polar regions are in many ways the most difficult to observe using
current satellite systems. This is especially true for the passive
systems, such as AVHRR and HIRS. The largest errors in ISCCP cloud
properties are in the polar regions, where cloud discrimination is most
difficult, and validating observations are scarce. The same is true for
estimates of cloud radiative forcing using the ERBE data. Because of
uncertainties in the discrimination of clear and cloudy ERBE
observations, even the sign of cloud radiative forcing is unknown. The
Arctic FIRE can provide data to be used for testing new cloud retrieval
algorithm in the Arctic. A good validation strategy would involve three
aircraft: the high-altitude ER-2 above cloud, an aircraft within the
cloud, and an aircraft that profiles from near the surface to the cloud
top. The ER-2 would include passive scanning radiometers to simulate the
AVHRR, Landsat, POLDER, MODIS, AIRS, SSM/I, and MIMR observations, as
well as nadir-pointing cloud lidar and cloud radar. The in-cloud
aircraft would measure cloud microphysics and in-cloud radiation. The
third aircraft would document profiles of the temperature, water vapor,
cloud particles, and aerosols from near the surface to a level somewhat
above the cloud top. Both in situ aircraft would fly along the ground
track of the ER-2.

The next 5 years should bring great improvements in our ability to
remotely sense polar clouds and radiation using satellites. The recently
launched ERS-1 ATSR instrument provides new observations at multiple
angles of view in the infrared, as well as observations at 1.6 mm where
clouds are more reflective (especially water clouds) than snow or ice at
the surface. In addition, ISCCP is now using the AVHRR 3.7 micron
channel to enhance the detection of polar clouds. In 1995, the Japanese
ADEOS satellite will include a POLDER multi-angle of view instrument for
solar wavelengths. POLDER also includes polarization measurements. In
1998, the EOS AM platform will include a CERES broadband radiometer (the
ERBE follow-on) as well as MODIS, a greatly improved version of AVHRR
which should greatly increase the ability to detect polar clouds. MODIS
will increase spatial resolution to between 0.25 and 1 km, allowing
improved cloud detection using spatial texture measures (Welch et al.
1991) At the same time MODIS will add spectral bands at 1.6 and 2.2 mm
for cloud particle size and phase discrimination during daylight
conditions, as well as a channel at 8.5 mm for use with 3.7, 11, and 12
mm channels for cloud particle size detection at night. A major
improvement over AVHRR will be on-board calibration of all spectral
bands, including solar wavelengths. The EOS AM platform will also
include ASTER, a Landsat-like instrument which will extend spectral
coverage to include thermal infrared channels at 8.5, 11, and 12 mm
wavelengths. In 2000, the EOS PM platform will be launched, including
CERES, MODIS, MIMR (an advanced SSM/I) and the AIRS infrared
spectrometer for improved temperature and humidity sounding. In 2002,
EOS will launch the GLAS lidar. This nadir pointing lidar will provide
global observations of cloud height, including the polar regions.

5.3.8 Integration of measurements to achieve science objectives

FIRE III provides a unique opportunity to increase our understanding of
clouds, radiation, boundary layer dynamics and atmospheric chemistry in
the Arctic. This unique opportunity arises because of two field programs
in the arctic that will be concurrent with the FIRE III effort, namely
SHEBA and ARM.

FIRE can add to the ARM / SHEBA observational system in three critical
ways. First, aircraft can provide in-situ observations of cloud
microphysics, radiation, and turbulent fluxes. Second, high altitude
aircraft such as the ER-2 can provide both active and passive radiometry
measurements to simulate both current (ERBE,AVHRR,HIRS, SSM/I) and
future (CERES, MODIS, AIRS, MIMR, GLAS lidar, 3 mm radar) satellite
measurement systems. This combination of simultaneous high altitude and
in-situ aircraft cloud observations has proven critical for validation
of satellite derived cloud and radiative properties. Third, FIRE can
provide advanced instrumentation which is too expensive, too manpower
intensive, or is insufficiently developed for long-term use by ARM or
SHEBA. An example is the use of Raman lidar for water vapor profiling in
the FIRE Kansas experiment.

To take full advantage of this opportunity to achieve important climate
objectives in the Arctic, careful integration and coordination of the
measurements made from the different platforms (aircraft, surface,
satellite) is needed. The purpose of this integration and coordination
is:

i\) to provide in situ validation for satellite- and ground-based remote
sensing

ii\) to provide redundancy for key measurements so that the relative
advantages of different platforms and instruments can be exploited;

iii\) to provide an integrated dataset that will provide the required
data for the FIRE III cloud modelling and single-column modelling
efforts, including data for model initialization, boundary conditions,
and evaluation/validation.

Integration and coordination will be a key subject for the FIRE Science
Team to address during the planning period before the field experiment.
Practical aspects include:

i\) timing of aircraft flights to coincide with overpasses of relevant
polar-orbiting satellites;

ii\) focussing aircraft flights on the region of the surface ice camp;

iii\) making measurements on the appropriate time and space scales
required for the satellite remote sensing and atmospheric modelling
objectives.

5.4. Modeling studies

FIRE III will employ a variety of modeling strategies, ranging from
cloud-scale models to global climate models. Models with dynamical
components will require observations of relevant large-scale boundary
conditions such as advective tendencies and vertical motion.

5.4.1 Cloud-scale models

Three-dimensional simulation of the larger scales of turbulence has been
applied to a broad range of meteorological phenomena, perhaps most
successfully in the area of severe convective storms (e.g., Klemp,
1987). It has been a moderately successful approach to analyzing the
evolution and structure of boundary layer stratocumulus in middle
latitude marine environments (e.g., Moeng, 1986). The traditional
mixed-layer modeling approaches have been subjected to validation and
improvement in this way. Comparisons with direct observational data have
been limited, partly because some of the most critical quantities, e.g.
entrainment rate, fluxes near the cloud top, are hard to measure.
Modelers have not yet been clearly successful in simulating the most
important climatological processes, those involving interactions of the
turbulent flow with cloud physics, radiation, and chemistry (Kogan,
1991; Kogan et al. 1994; Stevens et al., 1994). We ask whether this
technique is likely to be useful for low-level Arctic clouds.

Turbulence model simulations fall into the category of ™process studies∫
in the climate change lexicon. In that context their most important role
is regarded as aiding in development and validation of parameterizations
in global climate models. They should be used to test the sensitivity of
cloud evolution and structure to changes in microphysical parameters
which are difficult-to-measure and often ignored, such as cloud
condensation nuclei and their chemical precursors.

Looking first at the summer stratus regime, the process which drives
turbulence in the lower latitude cloud layers, buoyant convection due to
surface heating and/or long-wave radiative cooling, tends to be weaker
or absent in the Arctic summer. This is because of the large static
stability that is typical of the Arctic boundary layer, which is
primarily associated with the relatively cold surface and warm air
advection in the lower atmosphere. Stratus cloud observations (see
Section 5.2.2.3) indicate frequent multiple layers, with the top layer
well-mixed by turbulent convection but decoupled from lower layers and
the surface. A similar process occurs in lower latitude stratocumulus
during the daytime. It is replaced at night by strong cooling, which
reforms a well mixed boundary layer, but in the Arctic the daytime is
months long.

Despite low moisture contents and feeble convection, scavenging of
condensation nuclei occurs in the summer months, as is clear from the
much-reduced aerosol content in summer. Drizzle and snow observed are at
the surface in poorly known amounts. The precipitation-producing
processes, which occur in 10\'s of minutes to an hour or two in lower
latitudes may, because of the colder temperature, lower water content,
and feeble turbulence, require many hours to days in the Arctic cloud
layers.

During the cold half of the year, strong surface-based convection occurs
over leads. Cold air advected over an open lead sets up strong vertical
gradients of both temperature and moisture, creating an environment
extremely favorable for convection and hydrometeor plume development.
Using a very simple mixed-layer model, Serreze et al. (1992) found that
the derived height of buoyant convection tends to be largest under
conditions of low surface wind speed, low surface air temperature, weak
low-level temperature inversion, and large lead width. Glendening and
Burk (1992) have used a large eddy simulation to examine the shallow
convection associated with a 200 m wide lead. Pinto et al. (1994) and
Pinto and Curry (1994) have used a one-dimensional model with
second-order turbulence closure to examine convection from leads. As
pointed out by Alam and Curry (1994), a two-dimensional model is
necessary to reproduce the thermal circulations that result from the
horizontal temperature gradients associated with the lead.

In the transition seasons the cloud processes are complicated by mixed
phase physics, and diurnal convection may be significant during the
spring. Some opportunities for detailed simulation studies may exist,
but require more exploratory observational studies to define the kinds
of structures to be simulated.

The models initially developed for simulation of middle latitude
stratocumulus layers (Moeng, 1986) can be applied over a region of order
10 km square with a resolution of order 10 m, and easily integrated for
several hours. Most current models do not simulate microphysical
processes other than bulk condensation, however, and therefore do not
respond to changes in the aerosol environment. Also, the validity of
their radiation calculations is limited by arbitrary assumptions on
their drop spectra. It is questionable whether they could produce much
of value in the Arctic environment for climatological issues such as
aerosol processing and determination of solar transmission. The models
being developed with more detailed microphysics and radiation feedback
(Kogan, 1991; Kogan et al. 1994; Stevens et al. 1994) appear more
appropriate, but the Arctic environment presents a severe challenge to
them. The requirement for detailed spectra of aerosols and drop (and
perhaps ice particle) sizes increases computational requirements
several-fold, thus limiting the size of the domain, the length of
plausible calculations, or both. It is possible that for fairly
homogeneous situations the horizontal domain of calculations could be
very sharply limited (of order 2-4km) without severe loss of validity.

In addition to LES, discussed above, and the simple process models
discussed below, FIRE III should encourage studies with models of
intermediate complexity, e.g. higher-order closure models with advanced
cloud, radiation, and chemistry parameterizations. Simulations with such
intermediate models are much cheaper than LES, and can be run longer,
allowing studies of interactions between the atmosphere and the ice over
tens of days.

5.4.2 Single-column models

Simplified process models typical of those used as parameterizations in
GCMs can be used to synthesize understanding gained from observations
and more detailed models. They can be combined to form ™single-column
models,∫ which are essentially subsets of climate models, capable of
simulating a wide range of physical processes that occur inside a
™large-scale∫ \[i.e., of order (100 km)2\] grid box, typical of a GCM
grid. Process models developed and successfully tested in this way can
be transferred directly to GCMs, so that this is an efficient way to
facilitate incorporation of new knowledge into global climate models.
Suitable large-scale ™boundary conditions∫ must be prescribed from
observations, however, as discussed later.

A single-column model for the Arctic should include both the atmosphere
(or at least the boundary layer) and the sea ice and upper ocean. This
will allow the interactions among these components of the system to be
simulated and studied with the model. Such a model can be used to
simulate the seasonal cycle of the coupled system. Externally prescribed
advective sources and sinks should be provided for. The model should
include a parameterization of partial cloudiness, and might also include
a simple model of CCN chemistry. It should be capable of being run out
to equilibrium, through many seasonal cycles, on a workstation.
Applications and issues that could be addressed with such models include
the following:

∑ Studies of the sensitivity of the coupled system to external
perturbations, e.g. CCN perturbations, moisture and temperature
advection perturbations.

∑ Simulation of Arctic summer stratus, including formation, dissipation,
convective transports, and optical properties, and also including a
faithful representation of the dependence of cloud amount, cloud depth,
and cloud optical properties on the properties of the lower boundary,
including the fraction of open water, melt-pond coverage, and snow
cover.

∑ Simulation of the formation and dissipation of Arctic winter ™diamond
dust∫ clouds, including their effects on the downward longwave radiation
at the surface.

∑ Simulation of the seasonal transitions, including the coupled
evolution of cloudiness and the ocean / ice surface.

∑ Investigation of the extent to which the cloud amount and optical
properties of the Arctic summer stratus depend on the state of the lower
boundary, e.g. ice cover and thickness, snow-cover and thickness,
melt-pond cover and thickness.

∑ Study of the ways in which Arctic clouds affect the surface energy
budget, both instantaneously in all seasons, and integrated over an
annual cycle.

5.4.3 GCMs

FIRE III\'s expedition to the Arctic should be an occasion for intensive
study of the ability of climate models to simulate the observed seasonal
cycle in the Arctic. Model development activities should also be focused
on the Arctic to take advantage of the field data. Finally, weather
forecasting experiments would be very valuable because they offer the
possibility of detailed verification of particular weather events, e.g.
changes in cloudiness.

5.4.4 Special observations needed to make modeling studies possible

Modeling studies require data for initialization, to provide
observationally specified boundary conditions in some cases, and for
evaluation of the model results. Documentation of the large-scale
atmospheric structure is critically important not only for such modeling
applications, but also for interpretation of the large-scale context and
effects of the smaller-scale process with which a FIRE field program is
most directly concerned.

The data base for producing daily gridded analyses over the Arctic Ocean
of basic atmospheric dynamic and thermodynamic quantities has been
enhanced by the surface pressure and temperature data obtained from
drifting sea ice surface buoys (Thorndike et al., 1983) and
satellite-derived atmospheric temperature retrievals (e.g., Claud et
al., 1991). Improved methods of 4-dimensional data assimilation and
initialization, such as those employed by the European Centre for Medium
Range Weather Forecasting (ECMWF) in their routine initialized analyses,
have provided a plausible dataset for diagnostic and climatological
studies of Arctic circulation features. However, because of numerical
weather prediction model deficiencies in high latitudes, these analyses
must be used with caution, particularly with regards to the moisture
field.

Recent synoptic climatologies for the Arctic have been described by
LeDrew (1989) and Serreze and Barry (1993). Improved understanding of
synoptic-scale meteorology in the Arctic has been accomplished for
Arctic lows (e.g., Kuo and Low-Nam, 1990; Emanuel, 1989; summary by
Kellog and Twitchell, 1986) and for cold-core anticyclones (Curry,
1987).

Large-scale sea ice/atmosphere interactions have been summarized by
Barry (1986). Atmospheric heat budgets for the Arctic have been deduced
by Nakamura and Oort (1988). There has been limited examination of the
high latitude performance of atmospheric general circulation models
(e.g., Herman and Johnson, 1980; Schlesinger, 1986; Crane and Barry,
1988; WCRP, 1991; Walsh and Crane, 1992). A number of sensitivity
studies of atmospheric general circulation models to anomalies in the
total sea ice cover have been conducted (e.g., Herman and Johnson, 1978;
Royer et al. 1990).

The following observations are examples of what will be needed to make
single-column modeling and extended integration with cloud-resolving
models possible:

∑ Large-scale atmospheric vertical motion.

∑ Horizontal advective tendencies of atmospheric temperature and
moisture.

∑ Large-scale atmospheric pressure-gradient force.

Such data can be obtained from the operational weather services, but of
course the Arctic basin is a data void, although it is surrounded by
fairly dense observational networks. Additional observations made from
the ice would be very valuable. Particularly valuable observations would
include those from rawinsondes and wind profilers. The data should be
made available on the GTS, so that the operational forecast centers can
access it for their assimilation cycles. Arrangements should be made
with ECMWF and / or NMC to provide special datasets based on these
assimilations.

5.5. Conclusions

FIRE III can make a major contribution to our understanding of the
Arctic climate system and its role in the global climate. The FIRE
Science Team by itself does not and probably will not include experts on
all aspects of field operations in the Arctic. This additional needed
expertise will come chiefly through FIRE\'s cooperation with SHEBA.

With the additional resources to be provided through SHEBA and ARM, we
have an unprecedented opportunity to stage a multi-agency, multi-year,
multi-strategy attack on the difficult scientific problems that face us
as we attempt to understand and realistically model one of the most
mysterious and quantitatively important climate regimes.

Coordination of the FIRE III program with SHEBA and ARM will be
facilitated by the fact that several members of the FIRE III Science
Team are also on the SHEBA Science Working Group and the ARM Science
Team Executive Committee and also the ARM NSA/AAO Science Steering
Committee.

Integration and coordination of FIRE III field measurements with SHEBA
and ARM will result in considerable enhancement of the dataset that can
be used to achieve the FIRE III science objectives. Integration of the
different components of FIRE III with SHEBA and ARM promises to provide
a dataset whose impact is greater than the sum of its individual parts,
and can make a substantial impact on understanding the Arctic climate
system.

In summary, we distinguish between two types of goals. The scientific
goals of FIRE are to find the answers to certain key scientific
questions, listed below. The programmatic goals are to make the
measurements and conduct the modeling studies that will allow these
scientific questions to be answered. These programmatic goals are listed
separately below.

Scientific Questions

∑ How do leads, melt ponds, and other features of the underlying surface
affect the flow of radiation, sensible heat, moisture, and chemical
species through the air-sea interface?

∑ How does the state of the lower boundary affect the type of cloudiness
found in the Arctic boundary layer?

∑ How do ice crystal clouds in the winter Arctic boundary layer affect
the radiation balance of the surface?

∑ How do the low sun angles characteristic of the Arctic summer affect
the flow of radiation through the clouds and at the distinctly
non-Lambertian surface?

∑ What controls the multi-layered structure of Arctic boundary layer
clouds? Is this an extreme version of solar decoupling, as observed
previously by FIRE in California stratus and in ASTEX? How is moisture
supplied to the upper layers of cloud?

∑ How do Arctic clouds affect the surface energy balance and the
large-scale circulation of the atmosphere? How do these effects vary
with the seasonal cycle? How will they be impacted by anthropogenic
climate change?

∑ What processes produce CCN and IFN in the Arctic? What are the
relative contributions (throughout the year, and as a function of
altitude) of local production in the Arctic vs. long-range transport to
CCN and IFN, and of the various sources (biological, anthropogenic, and
stratospheric)? What are the chemical composition and size distributions
of CCN and IFN? What processes alter the effectiveness of Arctic CCN and
IFN? What is the effect of the relative abundance of CCN and IFN upon
the phase of the cloud particles?

∑ For liquid water clouds, what is the relationship between the droplet
size distribution and the size and chemical composition of the CCN? For
ice clouds, what is the relationship between the crystal habit and size
distribution and the size and chemical composition of the IFN?

∑ What is the relationship between cloud optical properties and CCN and
IFN abundances?

∑ What are the removal mechanisms for aerosol particles in the Arctic?
In particular, how do sedimentation (for diamond dust) and precipitation
(for ice and liquid water clouds) affect the CCN and IFN populations?

Programmatic Objectives

∑ Measurements and modeling studies of the formation, maintenance, and
dissipation of Arctic clouds, and cloud - boundary layer interactions,
cloud macrophysical and microphysical properties, cloud microphysical
interactions with atmospheric chemistry, cloud radiative properties, and
the response of clouds and atmospheric temperature, humidity, and wind
to changes in surface state and temperature.

∑ Measurement of lead fraction, ice thickness, and other
statistical-physical properties of the sea ice, and development of a a
method to realistically predict and / or parameterize these quantities
in GCMs. Assessment of the relative importance of leads as a macroscopic
source of heat, moisture, and microphysically relevant biogenic gases,
particularly with respect to the formation and radiative properties of
clouds. Development of a parameterization of lead fluxes based on a
modified bulk model with some effective lead fraction and possibly other
lead statistics. Studies of the disposition of shortwave radiative
energy absorbed by the upper ocean, and the impact of the radiation and
other energy fluxes on the ice mass balance.

∑ In situ validation for satellite- and ground-based remote sensing,
including measurement of upward shortwave fluxes to test, in the Arctic,
new methods that have been developed to directly relate the satellite
observed net shortwave radiation at the top of the atmosphere to the net
shortwave radiation at the surface.

∑ Measurements that document the impact of aerosol concentration on
cloud particle size distributions and cloud optical properties.
Measurements and modeling studies of the radiative properties of
cloud/aerosol mixtures, including studies of the interactions among
clouds, aerosols, radiation, and boundary layer turbulence and their
combined influence on the life cycles of boundary layer clouds.

∑ Concurrent measurements of atmospheric temperature, phase of
condensate, and concentration and composition of aerosol particles to
assess the impact of aerosols on the phase transition between liquid and
crystalline cloud particles.

∑ Improved measurements of atmospheric humidity at cold temperatures to
assess the water vapor feedback.

∑ Measurements and modeling studies of surface fluxes of radiation,
sensible and latent heat, and conduction in the heterogeneous ice cover,
including the impact of clouds on surface temperature, albedo, and
fluxes of radiation, sensible heat, and latent heat., including studies
of internal heating, melting, and absorption and transmission of
shortwave radiation within the sea ice, including studies of the ways in
which Arctic clouds affect the surface energy budget, both
instantaneously in all seasons, and integrated over an annual cycle.

∑ Modeling studies of the mutual adjustments of the upper ocean, ice
cover, and atmosphere to various forcing functions and perturbations,
including CCN perturbations, moisture and temperature advection
perturbations, the seasonal cycle, and anthropogenic climate change.

∑ Creation of an integrated dataset that will provide the required data
for cloud modelling and single-column modelling efforts, including data
for model initialization, boundary conditions, and
evaluation/validation.

∑ Development and testing of new instruments for key radiative and
microphysical quantities, in order to support development of instruments
that are actually needed to meet key field objectives.

∑ GCM simulations of the Arctic climate, and comparison with
observations. Sensitivity studies to determine how the simulated climate
depends on both model formulation and external physical perturbations
such as increasing carbon dioxide concentrations.

∑ Simulation of Arctic summer stratus, including formation, dissipation,
convective transports, and optical properties, and also including a
faithful representation of the dependence of cloud amount, cloud depth,
and cloud optical properties on the properties of the lower boundary,
including the fraction of open water, melt-pond coverage, and snow
cover. Simulation of the seasonal transitions, including the coupled
seasonal evolution of cloudiness and the ocean / ice surface.
Investigation of the extent to which the cloud amount and optical
properties of the Arctic summer stratus depend on the state of the lower
boundary.

∑ Simulation of the formation and dissipation of Arctic winter ™diamond
dust∫ clouds, including their effects on the downward longwave radiation
at the surface.

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**6. FIRE MANAGEMENT AND SCIENTIFIC ORGANIZATION**

6.1. Management

FIRE has been a multi-agency effort since its inception. The goals of
FIRE are not bounded by a single agency\'s mission; neither is the
talent base required to address the complex problems of cloud-climate
research. Close interagency cooperation in the past has made possible
FIRE\'s advancements in our understanding of these climatically
important cloud systems. It is intention of FIRE\'s participants to
maintain and further refine this spirit of interagency cooperation.

While NASA will continue to serve as the lead agency for FIRE-III, other
federal agencies including National Science Foundation (NSF), Office of
Naval Research (ONR), Department of Energy (DOE), Department of Defense
(DOD), and National Oceanic and Atmospheric Administration (NOAA) will
remain strong participants in FIRE III. The Physical Climate Branch,
NASA Headquarters, will provide overall cognizance of the FIRE project
for those activities associated with processes, especially those with
regional emphasis; the Earth System Modeling and Global Analysis Branch,
NASA Headquarters, will provide cognizance of those activities
associated with models, especially those with global emphasis, and will
represent FIRE to the Working Group on Data Management for WCRP
Radiation Projects. Contact points are located at the following offices:

  -------------------------------- --------------------------------------
  Dr. John T. Suttles              Dr. Jay Fein

  Physical Climate Branch          Division of Atmospheric Sciences

  NASA Headquarters/YSC            National Science Foundation

  Washington, DC 20546             2401 Wilson Boulevard

                                   Arlington, VA 22230

  Dr. Robert A. Schiffer           

  Earth System Modeling and Global Dr. Patrick J. Webber

  Analysis Branch                  Arctic Systems Science Program

  NASA Headquarters/YSM            Office of Polar Programs

  Washington, DC 20546             National Science Foundation

                                   2401 Wilson Boulevard

                                   Arlington, VA 22230

                                   

                                   

                                   
  -------------------------------- --------------------------------------

  -------------------------------- --------------------------------------
  Dr. Robert H. Thomas             Dr. H. Lawrence Clark

  Polar Processes Program          Division of Ocean Sciences

  NASA Headquarters/YSC            National Science Foundation

  Washington, DC 20546             2401 Wilson Boulevard

                                   Arlington, VA 22230

                                   

  Michael R. Riches                Dr. Robert Abbey, Jr.

  Department of Energy             Marine Meteorology Program

  Environmental Sciences Division  Office of Naval Research

  Research ER-74                   Code 322 MM

  Washington, DC 20585             800 N. Quincy Street

                                   Arlington, VA 22217

  Dr. Peter W. Lunn                

  Department of Energy             Dr. Thomas B. Curtin

  Atmospheric and Climate Research Arctic Program

  Division                         Office of Naval Research

  Office of Energy Research        Code 3248 MM

  Research ER-76                   800 N. Quincy Street

  Washington, DC 20874             Arlington, VA 22217

                                   

  Dr. Michael J. Coughlan          Col. Grant C. Aufderhaar

  NOAA/OGP                         Environmental & Life Sciences

  Mail Stop GP                     Room 3D129 The Pentagon

  1100 Wayne Avenue                Office of the Deputy Undersecretary

  Silver Spring, MD 20910          of Defense (R&AT)

                                   Washington, DC 20301

                                   

  Mr. Howard L. Wesoky             Dr. Brian Toon Manager

  AEAP, Manager                    AEAP/SASS

  NASA Headquarters                Project Scientist for Radiative
                                   Processes

  Code RH                          NASA Ames Research Center

  Washington, DC 20546             MS 245-3

                                   Moffett Field, CA 94035

                                   
  -------------------------------- --------------------------------------

6.2. Project Management

The FIRE-III project activities will be managed by the FIRE Project
Office at NASA\'s Langley Research Center. The FIRE project manager will
be responsible for the overall management, coordination, and reporting
of the project activities. These responsibilities will include (a)
interacting with the Earth System Modeling and Global Analysis Branch
and Physical Climate Branch management at NASA Headquarters, and the
other agency representatives; (b) overall cognizance of project
planning, schedules, and field operations; and (c) allocation of
approved funding to support the scientific objectives. The project
manager will be assisted by a project scientist and a project staff,
which will include: an Operations Manager, a Data Manager, a Logistics
Coordinator, and a Project Coordinator.

The FIRE Project Scientist, from NASA Langley, will be responsible for
all scientific aspects of FIRE-III. The project scientist will (a) act
as a scientific advisor to the project manager; (b) represent the
members of the science team in their relationship with the project
manager; (c) maintain an oversight of the scientific integrity of the
project; (d) review and make recommendations of proposed modifications
to selected proposals as warranted; and (e) participate in negotiations
regarding allocations of specialized project resources among approved
investigations.

6.3. FIRE-III Science Team

The FIRE-III Science Team (FST) will be comprised of the principal
investigators of those agency-approved proposals directly related to
FIRE-III research. Appointment to the FST will be based on the
recommendation of the supporting agency. The term of participation on
the team will continue as long as the approved research continues. The
team shall determine its own structure and method for interaction. Ex
officio members may be appointed to the team, as needed, by the project
manager.

The FST will be responsible for implementing the broad scientific
objectives of the project in accordance with the selected investigators.
Additional responsibilities will be to:

> a\. Develop implementation plans for FIRE-III research including:
>
> 1\. Field experiments.
>
> 2\. Data management.
>
> 3\. Research programs.
>
> b\. Recommend and perform coordinated research activities, including
> the interface of modeling and experiments.
>
> c\. Conduct individual investigations in accordance with approved
> proposals.
>
> d\. Hold meetings and workshops , as needed, to plan and assess
> research programs.
>
> e\. Designate the makeup and responsibilities of special working
> groups, as needed, to address special task areas.
>
> f\. Establish a data management and data protocol plan that will
> promote the timely publication and dissemination of scientific
> results.

6.4. Data Management and Protocol

Data management is an ongoing activity, beginning immediately in the
pre-experiment phase and continuing through the end of FIRE-III.
Collaboration and data exchange of data among FIRE investigators will
be, required to produce integrated analyses of multi-platform,
multi-scale, and multi-spectral data sets; these integrated analyses are
central to the accomplishment of the FIRE-III science objectives. In
addition, the data management activities will seek to ensure the
availability of FIRE data and analysis products to the entire science
community. To maximize these data management goals, the FST will develop
a data management and protocol plan consistent with the supporting
agencies\' goals for the sharing of the data, the rapid dissemination of
results, and documentation of measurements obtained.

At a minimum, the data management activities will disperse most of the
data reduction and processing functions to the FIRE investigators
engaged in collecting and analyzing the data, but to hold the resultant
data sets and analysis products centrally for ready access by all FIRE
investigators. The FIRE Central Archive, located at the Langley Research
Center EOSDIS Distributed Data Active Archive (DAAC), and the FIRE
Project Office will provide a centralized source of information and
copies of data which are centrally archived. The FST, composed of the
investigators, will coordinate the decentralized data reduction and
analysis activities. In addition, the FIRE Central Archive will
transfer, from time to time, certified FIRE data to the scientific
community.

At a minimum, the data protocol will provide for submittal of all
reduced measurements as determined by the FST with documentation to the
FIRE Central Archive. Publication of results from analysis of the
respective measurements will be determined by a timely schedule as
agreed to by all investigators. The FIRE Central Archive will serve as a
repository for all measurements and will be released to the public,
following a proprietary period to be determined by the FST and the
program managers of the supporting federal agencies.

6.5. National and International Collaborations

FIRE Phase III is a research project to be conducted by U.S. scientists
to provide a U.S. national contribution to the ISCCP of the World
Climate Research Program. In the sense that the scientific problems
addressed by FIRE-III are truly international, it is in the best
interests of FIRE-III to encourage the free exchange of information with
our national and international colleagues. Although resources do not
permit direct support of foreign participation in FIRE-III, ways will be
sought to allow collaboration, such as full participation and data
sharing as members of the FST. Other forms of collaboration will also be
encouraged. Cooperation and coordination with the research projects of
other countries will be accomplished through the ISCCP Working Group on
Data Management, which is responsible for this function under the Joint
Scientific Committee of WMO and ICSU. Reports of FIRE-III activities
will be made at the annual ISCCP WGDM meetings.

**Acknowledgements**

Cindy Carrick and Melissa Tucker spent many hours assembling and
preparing this manuscript; the drafting panel members are very
appreciative of their efforts, their diligence, their understanding and
their cheerful attitudes in what were sometimes trying circumstances.

**APPENDIX A - ACRONYMS**

  ---------------- ------------------------------------------------------
                   

  2D               2-dimensional

  3-D              three dimensional

  ACSYS            Arctic Climate System Study

  ADEOS            

  AEAP             Atmospheric Effects of Aviation Project

  AGASP            

  AMSU             

  ARCS             Atmospheric Radiation and Clouds Station

  ARCSS            Arctic System Science

  ARM              Atmospheric Radiation Study

  ASTER            Advanced Spaceborne Thermal Emission and Reflection
                   Radiometer

  ASTEX            Atlantic Stratocumulus transition Experiment

  AVHRR            Advanced Very High Resolution Radiometer

  BASE             

  BOMEX            Barbados Ocean Meteorology Experiment

  CCD              coupled charge device

  CCN              Cloud Condensation Nuclei

  CEAREX           Coordinated Eastern Arctic experiment

  CEPEX            Central Equatorial Pacific Experiment

  CERES            Clouds and the Earth\'s Radiant Energy System

  CLIVAR           Climate variability and predictability

  CN               Cloud Nuclei

  CTS              

  DAAC             Distributed Data Active Archive

  DIAL             Differential absorption lidar

  DLR              

  DMS              dimethyl sulfide

  DMSP             Defense Meteorological Satellite Program

  DOD              Department of Defense

  DOE              Department of Energy

  DOE              Department of Energy

  ECMWF            European Centre for Medium Range Forecasting

  EO               Electro-Optic

  EOS              Earth Observing System

  EOSDIS           Earth Observing System Distributed Information System

  EOSP             

  ERBE             Earth Radiative Budget Experiment

  ERS-1            Earth Resources Satellite-1

  ETO              extended-time observations

  FIRE             First ISCCP Regional Experiment

  FOV              Field Of View

  FSSP             Forward Scattering Spectrometer Probe

  FST              FIRE-III Science Team

  GATE             Global Atmosphere Tropical Experiment

  GCM              global climate model

  GEWEX            Global Energy and Water Experiment

  GEWEX            Global energy and Water experiment

  GLAS             

  GOALS            Global Ocean-Atmosphere-Land System

  GOES             Geostationary Operational Environmental Satellite

  HIRS             High Resolution Infrareds Radiation Sounder

  ICSU             

  IFN              Ice Freezing Nuclei

  IFO              intensive field observations

  IR               Infrared

  ISCCP            International Satellite Cloud Climatology Project

  IWC              ice water content

  IWP              ice water path

  JW               Johnson-Williams

  LaRC             Langley Research Center

  LES              large eddy simulation

  LIDAR            Light Detection and Ranging

  LOWTRAN 7        

  LWC              Liquid Water Content

  MCTEX            Marine Continental Thunderstorm Experiment

  METEOR           

  MHS              

  MISR             Multi-Angle Imaging Spectro-Radiometer.

  MIZEX            

  MODIS            Moderate Resolution Imaging Spectrometer

  NCAR             National Center for Atmospheric Research

  NOAA             National Oceanic and Atmospheric Administration

  NSA/AAO          North Slope of Alaska and Adjacent Arctic Ocean

  NSF              National Science Foundation

  OAII             Ocean-Atmosphere-Ice Interactions

  OLS              Optical Line Scanner

  ONR              Office of Naval Research

  PMS              Particle Measurement System

  POLDER           Polarization and Directionality of Earth Reflectances

  PR               Precipitation Radar

  PROBE            Pilot Radiation Observation System

  RASS             Radio Acoustic Sounding System

  ROCEW            Role of Clouds, Energy and Water

  SAR              Synthetic Aperture radar

  SASS             Subsonic Assessment Program

  SCARAB           Scanner for Radiation Balance

  SHEBA            Surface HEat Budget in the Arctic

  SPECTRE          Spectral radiation Experiment

  SSM/I            Special Sensor Microwave/Imager

  TDDR             Total Direct Diffuse Radiometer

  TMI              TRMM Microwave Imager

  TOGA-COARE       Tropical Ocean and Global Atmosphere-Coupled Ocean
                   Atmosphere Regional Experiment

  TOMS             

  TOVS             TIROS Operational Sounder

  TRMM             Tropical Rainfall Measurement Mission

  UAV              unassisted vehicle

  VIRS             Visible and Infrared Scanner

  WCRP             World Climate Research Program

  WGDM             Working Group on Data Management

  WMO              World Meteorological Organization
  ---------------- ------------------------------------------------------

**6. FIRE Management and Scientific Organization**

6.1 *Management*

FIRE has been a multi-agency effort since its inception. The goals of
FIRE are not bounded by a single agency\'s mission; neither is the
talent base required to address the complex problems of cloud-climate
research. Close interagency cooperation in the past has made possible
FIRE\'s advancements in our understanding of these climatically
important cloud systems. It is intention of FIRE\'s participants to
maintain and further refine this spirit of interagency cooperation.

While NASA will continue to serve as the lead agency for FIRE-III, other
federal agencies including National Science Foundation (NSF), Office of
Naval Research (ONR), Department of Energy (DOE), Department of Defense
(DOD), and National Oceanic and Atmospheric Administration (NOAA) will
remain strong participants in FIRE III. The Physical Climate Branch,
NASA Headquarters, will provide overall cognizance of the FIRE project
for those activities associated with processes, especially those with
regional emphasis; the Earth System Modeling and Global Analysis Branch,
NASA Headquarters, will provide cognizance of those activities
associated with models, especially those with global emphasis, and will
represent FIRE to the Working Group on Data Management for WCRP
Radiation Projects. Contact points are located at the following offices:

  -------------------------------- --------------------------------------
  Dr. John T. Suttles              Dr. Jay Fein

  Physical Climate Branch          Division of Atmospheric Sciences

  NASA Headquarters/YSC            National Science Foundation

  Washington, DC 20546             2401 Wilson Boulevard

                                   Arlington, VA 22230

  Dr. Robert A. Schiffer           

  Earth System Modeling and Global Dr. Patrick J. Webber

  Analysis Branch                  Arctic Systems Science Program

  NASA Headquarters/YSM            Office of Polar Programs

  Washington, DC 20546             National Science Foundation

                                   2401 Wilson Boulevard

                                   Arlington, VA 22230
  -------------------------------- --------------------------------------