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Page 272 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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Page 273 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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Page 274 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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Page 275 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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Page 276 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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Page 277 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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Page 278 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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Page 279 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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Page 280 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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Page 281 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 timeallows 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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Page 282 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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Page 314 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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Page 315 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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Page 316 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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