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5
Climate and Climate Change Research Entering the Twenty-First
Century1
Summary
Climate is variable on time scales of seasons to centuries and
over longer time intervals. Both climate variability and climate
change can have significant societal impact. Climate influences
agricultural yields, water availability and quality, transportation
systems, ecosystems, and human health. Climate variability and
change are a product of external factors such as the Sun, complex
interactions within the Earth system, and anthropogenic effects.
The mission of climate research is to understand the physical,
chemical, and ecological bases of climate in order to characterize
and predict the nature of climate variability from seasonal and
interannual to decadal and longer time scales, and to assess the
role of human activities in affecting climate and of climate in
influencing human activities and environmental resources.
A central goal of climate research is prediction. The objectives
are to understand the mechanisms of natural climate variability on
time scales of seasons to centuries and to assess their
predictability, to predict the future response of the
l Report of
the Climate Research Committee: E.J. Barron (Chair), Pennsylvania
State University; D. Battisti, University of Washington; R.E.
Davis, Scripps Institution of Oceanography; R.E. Dickinson,
University of Arizona; T.R. Karl, National Climatic Data Center;
J.T. Kiehl, National Center for Atmospheric Research; D.G.
Martinson, Lamont-Doherty Earth Observatory of Columbia University;
C.L. Parkinson, NASA Goddard Space Flight Center; S.W. Running,
University of Montana; E.S. Sarachik, University of Washington; S.
Sorooshian, University of Arizona; K.E. Taylor, Lawrence Livermore
National Laboratory; P.J. Webster, University of Colorado.
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climate system to human activities, and to develop improved
capabilities for applying and evaluating these predictions.
The climate research of the past few decades drives the
requirements for future research by focusing our attention on the
remaining uncertainties and on the importance of climatic research
for society:
• Climate variability, such as El Niño, can be
characterized by significant economic and human dislocations.
Modeling studies over the past two decades suggest that aspects of
this climate variability may be predictable. In cases where El
Niño/Southern Oscillation (ENSO) events were predicted in
advance, immediate practical benefits were realized through human
response and adaptation.
• Analyses of historical records have revealed a number of
interesting cases of longer-period fluctuations for North America
and other parts of the world, while model studies have demonstrated
that ocean-atmosphere and land-bio-sphere-atmosphere interactions
are plausible mechanisms to explain decade-to-century variability.
Historical and paleoclimatic data, as well as coupled models,
indicate the potential for significant climate variability on long
time scales. Such changes can be expected to occur in the future,
irrespective of human impacts on climate. Current observational
capabilities and practice are inadequate to characterize many of
the changes in global and regional climate. An enhancement of
current observational capability and improved knowledge of the
coupled Earth system will therefore likely increase our
understanding of climate variability on all time scales and lead to
a greater realization of practical benefits.
• The effort to predict the climate response to increases
in greenhouse gases has both demonstrated the importance of this
problem to society and focused attention on many of the most
important limitations of current climate models. Increased
concentrations of greenhouse gases and changes in land use and land
cover are directly and indirectly tied to human activities. Current
model projections based on increases in greenhouse gases and
aerosols and on land cover change indicate the potential for large,
and rapid, climate change relative to the historical and
paleoclimatic records, with concomitantly large influences on human
activities and ecosystems. Although remarkable progress in
developing these climate models has occurred over the past two
decades, current climate models are characterized by a great number
of uncertainties. Improved predictive capability is likely to have
a positive impact on economic vitality and national security
because of its potential to minimize risk and maximize benefit
associated with the impacts of any climate change.
A comprehensive analysis of the remaining scientific questions
and uncertainties and of the societal drivers for climate research
leads us to four major imperatives for the twenty-first century.
Each imperative is associated with a series of basic
requirements:
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1. We must work to enhance current observational capabilities
and to build a permanent climate observing system.
• Where feasible, adopt consistent data collection and
management rules to ensure the utility of operational and research
system measurements for climate research.
• Develop and adopt interagency plans to ensure the
protection of critical long-term observations, to limit gaps in
continuity due to small budget changes in single agencies, and to
recognize the value of these observations in a balanced, integrated
research program.
• Provide strong U.S. support and participation in the
development of a global climate observing system (GCOS).
• Ensure full and open international exchange of data and
information.
• Maintain major research observation systems, such as the
Tropical Ocean Global Atmosphere (TOGA) Tropical Atmosphere Ocean
(TAO) array, that have demonstrated clear predictive value.
• Focus on key opportunities for reducing major
uncertainties in climate models, including improved observations of
water vapor.
• Ensure full interagency commitment to both the in situ
and the satellite observations necessary to address the major
uncertainties in our understanding of the climate system, including
a commitment to long-term Earth observations of critical variables
such as the major climatic forcing factors.
2. We must extend the instrumented climate record through the
development of integrated historical and proxy data sets.
• Widely sample the alpine glaciers and ice caps before
this important repository of information on natural variability is
lost.
• Continue efforts to collect and analyze data from around
the world from tree rings, lake sediments, corals, and ice cores,
and actively pursue high-resolution records from ocean
sediments.
• Focus research efforts on the development and validation
of proxy indicators.
3. We must continue and expand diagnostic efforts and process
study research to elucidate key climate variability and change
processes.
• Enhance cross-disciplinary communication and
collaboration.
• Develop clearly articulated linkages between strategies
for observation, analysis, model development, and application of
predictions to evaluating consequences of climate change.
• Implement focused research initiatives on processes and
in regions that are identified as important in understanding
variability in the climate system.
• Implement and analyze new observations necessary for
understanding the
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processes that couple the components of the Earth system and
improve our understanding of climate variability on
decade-to-century time scales.
• Develop focused process studies with the objective of
addressing key uncertainties associated with boundary layer
processes and vertical convection; improved linkages coupling the
atmosphere, oceans, and land surface; and more explicit
representation of land surface processes, including vegetation and
soil characteristics.
• Support the development and implementation of a
comprehensive research program to study and advance
seasonal-to-interannual prediction. Such a program is currently the
objectives of GOALS (Global Ocean-Atmosphere-Land System) of the
World Climate Research Programme (WCRP).
• Support the development and implementation of a
comprehensive research program to study the mechanisms of
decadal-to-century variability and its implications for longer
time-scale predictability. Currently, the planning for this element
is incorporated in the Dec-Cen (study of climate variability on
decadal-to-century time scales) and anthropogenic climate change
components of the WCRP.
4. We must construct and evaluate models that are increasingly
comprehensive, incorporating all major components of the climate
system.
• Improve opportunities and enhance efforts at model
observation and model-model comparisons that pay particular
attention to simulating observed changes associated with solar
irradiance, aerosol loadings, and greenhouse gas
concentrations.
• Develop mechanisms that promote formal interaction
between physical scientists and social scientists, by working on
common problems to improve the applications and assessments of
climate change impacts.
• Enhance the computational infrastructure and focused
efforts to develop climate system models that include explicit
representation of the atmosphere, ocean, biosphere, and
cryosphere.
• Focus on key opportunities for reducing major
uncertainties in climate models, including greater understanding of
climate-water vapor feedbacks and improved representation of
atmospheric chemistry and indirect chemistry-climate
interactions.
• Focus effort on improving the credibility and usefulness
of climate model predictions at spatial scales relevant to analysis
of the responses of ecosystems, socioeconomic systems, and human
health to climate change predictions.
• Develop and construct high-resolution, regional climate
models along with empirical methods for producing estimates of
climate change characteristics of immediate relevance to
humans.
These four imperatives offer a general framework, while the
specific objectives and requirements for each characterize more
specific opportunities to promote
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significant advancement in climate and climate change research.
To some, the list of requirements outlined above may appear overly
ambitious and without priority. However, a comprehensive climate
research program that serves societal needs is clearly within our
grasp. In many cases, the programs required to achieve these
objectives are in place. In other cases, changes in requirements
can be implemented with minimum budgetary impact. In still other
cases, objectives can be fulfilled by increased collaboration and
closer interagency planning and linkages. However, even some of the
more logical, minimal-impact issues appear to be problematic. For
example, in terms of the requirement for continuity and quality as
part of the climate observing system, current policies verge on
becoming a national and international embarrassment. Addressing
these issues must be a priority. Finally, with careful planning to
achieve greater efficiencies, the full spectrum of climate
objectives should be realizable. Although each of the listed
requirements has substantial merit, we recognize that improvements
and augmentations of the U.S. climate research programs must still
be paced, based on budgetary and other considerations.
Consequently, the requirements described above are placed in a
prioritized framework in the remainder of this Disciplinary
Assessment. This prioritized framework is based on a relatively
simple perspective. Improvements that have minimal budgetary impact
but substantial merit should be implemented without hesitation.
Requirements with significant programmatic or budgetary
implications should have identifiable levels of priority or clear
trade-offs with current efforts.
Introduction
Three general categories of climate variability and change have
been adopted by the World Climate Research Programme:
seasonal-to-interannual climate variability, decadal-to-centennial
climate variability, and changes in global climate induced by the
aggregate of human activities that change both the concentrations
of greenhouse gases and aerosols in the atmosphere and the pattern
of vegetative land cover. Humans, as individuals and societies, and
ecosystems are affected by and respond to each of these three
categories of variability and change.
Useful predictive skill for seasonal-to-interannual climate
variability has been demonstrated. Moreover, early indications of
human influence on global climate warming are emerging from the
background of natural climate variability. The possibility that
human activities have the potential to modify natural climate
variability and long-term climate trends on a global scale is a
research issue of high priority. Results of such research will have
very high utility for informing the public and decision makers of
appropriate response strategies.
Climate is defined as the long-term statistics that describe the
coupled atmosphere-ocean-land weather system, averaged over an
appropriate time period. For example, the averaged daily mean,
minimum, and maximum temperatures recorded for a given month at a
specified place are some important manifesta-
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tions of climate. Likewise, the daily average hours of sunlight,
cloud cover, rainfall, ground water saturation, snowpack, and
runoff observed for a given month at a specified locality are other
important climate characteristics.
Climate variability refers to fluctuations in climate statistics
with reference to a very long time average. Thus, the average
summer temperature over a region may differ from year to year
(interannual variability) or may manifest a fluctuation that spans
a number of years (decadal variability). Natural climate
variability has been observed on a range of time scales from months
to seasons to centuries and more.
A climate trend refers to a long-term secular change in average
climate statistics or a change in their statistical variation about
the average. A climate trend may be forced by a cause external to
the climate system, such as a change in the solar radiative output,
or by human-induced changes in the atmospheric composition of trace
gases and aerosols or the structure of vegetative land cover. A
climate trend may also be forced by an internal change in the
climate system, which could result, for example, from a change in
ocean circulation patterns.
A climate quantity is predictable when a significant fraction of
its variations can be consistently explained by a physical theory
or mathematical model. Meaningful predictive skill is usually based
on correlation between the predicted time series and the verifying
time series of the quantity. Since climate statistics are strongly
correlated with boundary quantities (e.g., sea surface
temperatures), the boundary quantities may be considered climate
quantities.
Seasonal-to-interannual variability, such as the phases of ENSO,
is associated with widely distributed weather anomalies and
sometimes severe conditions. These anomalies may persist for many
months and can result in significant economic and human
dislocations from Australia through tropical and semitropical South
America to parts of Africa. Historical records and paleoclimatic
data sources indicate the occurrence of significant climate
variability on time scales of decades to centuries. Climate
variability on these time scales has produced marked shifts in
human well-being recorded in history over the past several
centuries and can be expected to result in significant economic and
human dislocations in the future. Current climate model projections
based on anthropogenic increases in greenhouse gases and land cover
changes indicate the potential for large, and rapid, climate change
relative to the historical and paleoclimatic records, with
concomitantly large influences on human activities and
ecosystems.
Climate change can lead to significant changes in energy use,
air pollution, crop yields, water quality and availability, the
frequency and intensity of severe weather events, and the
occurrence and spread of infectious diseases. Improved knowledge of
the climate system offers the potential to enhance our predictive
capability, which could support societal efforts to adjust to,
forestall, or even eliminate some of the negative impacts of
projected climate change. An enhanced capability to predict future
climate will have a positive impact on economic vitality and
national security.
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Progress in understanding the physical, chemical, and ecological
bases of climate during the past few decades is clearly a result of
a wide variety of research efforts. A clear set of scientific
objectives and requirements can be formulated for the coming years.
Nonetheless, significant progress in achieving the mission of
characterizing and predicting seasonal-to-century time-scale
variability in climate, including the role of human activities in
forcing this variability, is likely to take a decade or more. Some
aspects of the problem will continue to be intractable for
considerably longer periods.
The remainder of this Disciplinary Assessment articulates a
mission and identifies the principal issues and related scientific
questions that challenge the climate research community entering
the twenty-first century. Seven scientific and programmatic
objectives intended to guide this community over the next decade
are presented.
Mission Statement
Human endeavors have come to depend on familiar global and
regional environments. In fact, much of the fabric of our society
is tied directly to climate through agriculture, water resources,
and energy utilization. We have long recognized that climate is
variable on time scales of seasons to centuries, and even longer
intervals, and that this variability can have significant societal
impact. El Niño events, the 1930s drought in the United
States, the Sahel droughts, and variations in the monsoons over the
most populous areas of the globe provide examples of the importance
of natural climate variability for human activities and well-being.
The nature of global and regional climates is also subject to
change because of human activities, most notably in response to the
observed changes in atmospheric composition (e.g., greenhouse gases
and aerosols) and land use, characteristic of the last century. The
potential impact of these changes is great and spans such diverse
issues as agricultural yield, water resource availability,
transportation systems, water quality, energy production and
utilization, frequency and magnitude of extreme weather events,
natural ecosystem viability, and even the nature of infectious
diseases and their spread by agents that are influenced by
climate.
The magnitude and timing of human-induced climate change remain
active research topics. Large gaps in our knowledge of interannual
and decade-to-century natural variability hinder our ability to
provide credible predictive skill or to distinguish the role of
human activities from natural variability. Narrowing these
uncertainties and applying our understanding define the mission of
climate and climate change research and education for the
twenty-first century.
The mission of climate research is to
understand the physical, chemical, and ecological bases of climate
in order to characterize and predict the nature of climate
variability from seasonal and interannual to decadal
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and longer time scales, and to assess the
role of human activities in affecting climate and of climate in
influencing human activities and environmental resources.
The scientific uncertainties, coupled with the potential
significance of climate variability and climate change, indicate
the importance of developing a scientific strategy for monitoring
changes to the climate system, addressing key scientific
uncertainties, enhancing our understanding of the impact of human
activities, assessing societal vulnerability to climate change, and
minimizing risk and maximizing benefits to society. Our primary
goal is to enhance our capacity to predict climate variability and
climate change, which implies understanding the impact of human
activities in influencing climate.
Perspectives for the Twenty-First
Century
To determine the imperatives for research in the coming decades,
one must note the results of the past few decades of research,
including both the explicit advances in knowledge and the increased
potential to address the remaining critical uncertainties, and must
recognize the importance of climatic research for society.
Insights of the Twentieth Century
A broad interest in climate variability and climate change was
awakened in the early 1970s and during the 1980s due to a large
number of weather-related disasters in widely scattered parts of
the world and to accumulating evidence that human activities are
altering the concentrations of radiatively important trace gases in
the atmosphere. This awakening resulted in a large dedicated
effort, through both the WCRP and national efforts, such as the
U.S. National Climate Program and the U.S. Global Change Research
Program (USGCRP), to enhance and analyze observations, conduct
process studies, and improve climate models. The principal goal has
been to develop credible methods to predict climate variability and
change. The insights gained from these efforts are diverse and
numerous. The three sections that follow illustrate the state of
the science.
Seasonal-to-Interannual Variability
and the El Niño/Southern Oscillation
ENSO is a major global-scale signal of seasonal-to-interannual
climate variability. ENSO consists of both warm and cold phases,
with the warm El Niño phase attracting most public
attention. The El Niño phenomenon is an anomalous warming of
surface ocean waters in the central to eastern equatorial Pacific
Ocean accompanied by large-scale anomalies in rainfall (Figure
II.5.1). El Niño occurs irregularly with a typical time
period of three to six years. It has been known throughout the
twentieth century, mostly through its detrimental effects
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FigureII.5.1
Schematic of large-scale climate anomalies associated with the warm phase of the Southern Oscillation during Northern
Hemisphere winter. Based on Ropelewski and Halpert (1986, 1987) and Halpert and Ropelewski (1992). Source: NRC,
1994a.
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on the fisheries, agriculture, and water resources of countries
bordering the tropical Pacific, but only in the past 20 years has
major progress been made in understanding the mechanisms that
create ENSO and observing its occurrence and wide-ranging
impacts.
The 1982-1983 warming, the largest of the twentieth century, was
neither predicted in advance nor recognized until nearly at its
peak. The enormous worldwide damage directly attributable to this
warming (floods in Peru, collapse of the Peruvian anchoveta
fishery, devastating drought, and forest fires in Australia and
Borneo) gave impetus to an emphasis on observing the tropical
Pacific in real time and on predicting the phases and intensity of
ENSO.
As a result, the international TOGA program of the WCRP was
developed. The accomplishments of TOGA, including major
contributions by U.S. scientists, are many (NRC, 1996c):
1. The TOGA observing system, consisting of 65 TAO moorings,
expendable bathythermographs (XBTs), drifting buoys, tide gauges,
upper-air integrated sounding systems, and volunteer observing
ships (Figure II.5.2)—all telemetering to the global
telecommunication system (GTS) in real time—allows an
unprecedented look at the state of the atmosphere, sea surface and
subsurface tropical Pacific in real time (McPhaden et al.,
1998).
Figure II.5.2
The TOGA observing system (TAO). SOURCE: NRC, 1996c.
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Figure II.5.3
(A) Observed Sea Surface Temperature Anomalies (SSTA) In Tropical Pacific And (B)
Prediction Made 12 Months In Advance By Cane And Zebiak (1987). Reprinted With
Permission Of The Royal Meteorological Society.
2. A set of theories about ENSO has been developed and the
mechanisms that may be responsible for its irregularity have been
identified (Battisti and Sarachik, 1995; Neelin et al., 1998).
3. Connections between warming in the equatorial Pacific and
climate phenomena in other parts of the world have been
demonstrated, and the dynamical mechanisms responsible for these
connections are beginning to be understood (Lau and Nath, 1994;
Trenberth et al., 1998).
4. Coupled atmosphere-ocean models have been developed that are
capable of simulating the major features of ENSO in the tropical
Pacific (Zebiak and Cane, 1987; Delecluse et al., 1998).
5. Significant skill beyond persistence has been demonstrated in
predicting sea surface temperature anomalies (SSTA) in the eastern
to central tropical Pacific as much as a year in advance (Figure
II.5.3) (Latif et al., 1994, 1998).
6. Prediction systems, consisting of coupled atmosphere-ocean
models, data
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search program to study the mechanisms for decadal-to-centennial
variability and the implications for longer time-scale
predictability. Currently, planning for this element is
incorporated in the Dec-Cen and anthropogenic climate change
components of the WCRP.
Objective 6
Continue to improve the analysis and
predictive skill of the degree to which humans are affecting
climate, including changes in variability and the probability of
extreme events.
Analysis of how humans can potentially affect climate and its
variability is carried out with a hierarchy of global climate
models and observational data sets. Studies with these models
indicate that the nature of global and regional climate is in
danger of changing due to human activities, most notably in
response to increases in greenhouse gases, aerosols, and changes in
land use. However, the nature and timing of this change are
uncertain. The prediction of future climate change is problematic,
in part, because of an inadequate understanding of climate
variability, the difficulty of predicting future greenhouse gas and
aerosol concentrations, and a limited understanding of the behavior
of the coupled climate system. Current climate predictions based on
projected increases in greenhouse gases and aerosols indicate the
potential for large and rapid climate change relative to the
historical record. Improved knowledge of the fully coupled climate
system can lead to an enhanced predictive capability that could
support societal efforts to adjust to, forestall, or even eliminate
some of the negative impacts of projected climate change. This
enhanced ability to predict future climate will have a positive
impact on economic vitality and national security.
The research of the last decade has clearly identified a number
of key factors that require a reduction in uncertainty if progress
is to be made in climate prediction:
First, the current observational system does not measure all of
the key global factors that force climate change. For example,
despite years of debate about the role of solar variations in
explaining observed climate fluctuations, we lack a long-term,
consistent, calibrated measure of solar input to the Earth system.
Similarly, measures of global aerosol concentrations and character
are inadequate to assess its role in climate. Without an enhanced
climate observing system, such debates are likely to continue
without satisfactory resolution.
Second, substantial debate concerning the nature of climate
sensitivity to increases in carbon dioxide stems from uncertainties
in the measurement of water vapor in the upper troposphere and in
the nature of climate-water vapor feedbacks. The nature of this
debate demands improved measurement of water vapor.
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Third, much of the uncertainty involves ocean-atmosphere
coupling, land-vegetation-atmosphere coupling, sea ice modeling,
and cloud-climate interactions. Process studies that combine the
use of fine-scale regional models, field programs, and diagnostic
analysis to bridge the spatial and temporal gaps between
observations and typical scales of climate models offer great
promise of improving model parameterizations. Diagnostic analysis
of paleoclimate and historical data sets can also increase
understanding of processes involved in climate change. These
studies carded out for a number of large-scale conditions will lead
to generalized parameterizations for a range of physical processes
(e.g., clouds, sea ice). Reduced uncertainty in modeling surface
energy budgets through improved cloud parameterizations will
increase the reliability of coupled atmosphere-ocean-land modeling.
Furthermore, increased resolution of ocean models will enhance
understanding of the coupled system. Systematic analysis of these
various climate components should reduce climate drift of the
coupled system.
Fourth, experience with weather forecasting models suggests that
increased spatial resolution results in improved prediction. In
addition, the aspects of climate and climate change prediction of
greatest relevance to humans and to ecosystems are those that
impact water, water resources, weather hazards, agricultural
yields, and human health. Most GCM simulations are at spatial
scales that are too coarse for credible climate impact analysis.
Increased spatial resolution must be matched with better physical
representations.
Fifth, model-data comparison is critical to diagnose and improve
climate model predictions. In many cases, the suite of satellite
and in situ data sets has been underutilized in efforts to validate
climate models. Further, observations from the industrial period
represent too short a time span for satisfactory model validation.
Greater confidence in model predictions will be gained through
efforts to reproduce industrial, preindustrial, and paleoclimatic
data sets.
In addition, WCRP efforts to compare climate models based on
standard sets of climate simulations through the AMIP (Atmospheric
Model Intercomparison Project) process has resulted in increased
scrutiny of model parameterizations. The success of this effort has
resulted in paleoclimatic intercomparison projects, land surface
parameterization comparisons, and intercomparison of limited-area
mesoscale models. Continued effort to intercompare models and their
parameterization will continue to provide substantial benefit.
Finally, increased coordination of climatic research has the
potential to yield significant efficiencies. For decades, we have
developed observational strategies, promoted and completed process
studies and field campaigns, developed a host of atmospheric and
oceanic models, and produced impact analyses of climate change
based on model output. As yet, however, the path from a proposed
new observational strategy or field campaign through to the
development of improved model parameterizations or improved
application is often not articulated clearly. The cost, in human
and financial resources, of major observational
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systems and field campaigns is sufficient justification for
developing clearly articulated strategies for climate research.
The development of more physically based parameterizations for
clouds (including their interaction with radiation), coupled
atmosphere-ocean models that do not rely on flux corrections to
simulate current and historical climates, and multiple examples of
coupled Earth system models that adequately represent the major
components of the Earth system will be evidence of significant
progress in efforts to project future changes in the climate
system, including its response to human activities. The efforts to
develop a more comprehensive observing system and to construct more
comprehensive climate system models should lead to demonstrated
progress in reducing uncertainties in the prediction of
human-induced climate change.
The following requirements are essential to achieve this
objective:
1. Develop an enhanced climate observing system capability, with
dedicated monitoring programs, as described previously.
2. Focus on key opportunities for reducing major uncertainties
in climate models, including improved observations of water vapor
and greater understanding of climate-water vapor feedbacks and
improved representation of atmospheric chemistry and indirect
chemistry-climate interactions.
3. Develop focused process studies with the objective of
addressing key uncertainties associated with boundary layer
processes and vertical convection; improved linkages coupling the
atmosphere, oceans, and land surface; and more explicit
representation of land surface processes, including vegetation and
soil characteristics.
4. Improve the opportunities to develop coupled models, and
enhance efforts at model-observation and model-model comparisons
that give particular attention to simulating the observed changes
due to changes in solar irradiance, aerosol loadings, and
greenhouse gas concentrations.
5. Focus effort on improving the credibility and usefulness of
climate model predictions at spatial scales relevant to analysis of
the responses of ecosystems, socioeconomic systems, and human
health to climate change predictions.
6. Improve the reconstruction, simulation, diagnostic studies,
and analysis of data sets from the industrial, preindustrial, and
paleoclimatic periods in order to increase confidence in model
predictions.
7. Develop clearly articulated linkages between strategies for
observation, analysis, model development, and application of
predictions to evaluating consequences of climate change.
Objective 7
Enhance the linkages between climate model
predictions and aspects of the Earth system of immediate relevance
to humans (e.g., extreme
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