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Forum on Global Change Modeling

Part 3.

Opportunities for Reducing Uncertainties

Meeting participants identified a number of areas where sustained or intensified research efforts would bring important gains in understanding and predictive capabilities.

(1) While progress is clear as a result of ongoing research efforts and important steps can be taken over the coming decade that will bring new insights, significant reductions of the uncertainties in projecting changes and trends in the climate will require sustained efforts that are very likely to require a decade or more.

Basis-Progress will require significant effort because the problems are complex, because improvements in model parameterizations will require a sustained and long-term program of research and observations, and because the records of past changes and influences require careful reconstructions to make them more complete and more useful. Although progress may be modest, there are a number of processes and feedbacks on which research must be sustained because of the large leverage to be gained from improved understanding. These processes and feedbacks include (a) cloud- radiation-water vapor interactions, including treatment of solar and infrared radiation in clear and cloudy skies (also including resolution of uncertainties concerning anomalous solar absorption); (b) ocean circulation and overturning; (c) aerosol forcing, requiring information on aerosol character and extent; (d) decadal to centennial variability; (e) land-surface processes, including the climate-induced changes in the structure and functioning of ecological systems with resultant changes in global chemical cycles; (f) short-term variability affecting the frequency and intensity of extreme and high impact events (e.g., monsoons, hurricanes, mesoscale storm systems, etc.); (g) non-linear and threshold effects that create the potential for surprises; and (h) interactions between chemistry and climate change and improved representation of atmospheric chemical interactions within climate models, thereby leading to improved understanding of the causes of trends in CH4, N2O, O3, CFCs, and aerosols.

(2) Improved spatial resolution in atmospheric and oceanic models will improve the representation of the present climate and potential global-scale changes.

Basis-In the atmospheric component of climate models (as in weather forecast models), major storm systems and circulation patterns are significantly better represented in models having resolutions finer than about 2.5 degrees in latitude and longitude (as opposed to the 5- to 7-degree resolution often used in past modeling studies), in part because of improved representation of major orographic features and in part because of improved ability to represent weather systems, the Intertropical Convergence Zone, the Hadley circulation, and other circulation features (figure 9). In the oceanic component of climate models, ocean current patterns are significantly better represented in models having resolutions finer than about 0.5 to 1 degree (as opposed to the 3- to 5-degree resolution in past modeling studies), in large part because important ocean current systems (e.g., the Gulf Stream and Kuriosho), ocean variability (including ENSO events), and the thermohaline circulation and other vertical mixing processes can be better represented. Improved resolution in both atmosphere and ocean components of global climate models has also proven to reduce flux imbalance problems arising in the coupling of these components. With the increasing parallelism of supercomputers and the availability of massively parallel computers, the only impediment to the gain in model accuracy by improving model resolution is the commitment of computational resources. However, a concomitant increase in efforts for process studies and diagnosis and analysis of model results is required.

(3) Climate changes at the surface and as a function of altitude can be better represented by inclusion of significantly more representative parameterizations of the atmospheric boundary layer and of vertical convection processes. Substantially improved observations and improved representations of water vapor in climate models will reduce a major source of uncertainty in model predictions.

Basis-By including more complete representations of the atmospheric boundary layer, weather forecast models have achieved important gains in their representation and prediction of surface conditions, and of water vapor transport to the free troposphere. A 1% change in relative humidity leads to about a 1 W/m2 change in top-of-the-atmosphere fluxes. Observational uncertainty in relative humidity is more than 10% in some regions, which can translate to more than twice the flux change expected from a CO2 doubling. It is difficult to separate possible model error from observational error, especially in relatively dry regions. Important debate continues as to the nature of the positive water vapor feedback associated with global warming. Improved representations of precipitation and of convective transport of water vapor into the upper troposphere will significantly reduce uncertainties about the amplifying feedback due to water vapor and the extent of changes in storm tracks. Such improved representations are being developed and tested, and will be able to be implemented, provided computational time is allocated for testing, and diagnostic and analysis efforts are strengthened. An increased emphasis on observations of water vapor and evaluation and testing of models is crucial to the global warming hypothesis.

(4) Improving the linkages coupling the atmosphere, oceans, and land surface will reduce uncertainties in estimates of the overall climate response by improving the accuracy of the climate simulations, by eliminating the need for ad hoc adjustments to fluxes between components that are used in some models, and by allowing fuller exploration of natural climate variability over all time scales.

Basis-The climate is a result of the complex interactions of the atmosphere, the oceans, and the land surface. The dynamics, thermodynamics, and hydrodynamics (and to an increasing extent the chemical and vegetation dynamics) must all be treated in order to provide a realistic simulation of climate. The focus has initially been on the atmosphere, then increasingly on the ocean; coupling of the atmosphere and oceans has not been completely successful due to limitations in understanding of ocean mixing and air-sea exchange mechanisms, in addition to limitations in model resolution and the full range of processes internal to each domain. Increased attention to improved representation of the coupling is starting to lead to improved representations of temperature and other climatic variables. Corresponding improvements are needed in representations of the land surface and land-atmosphere interactions and fluxes. Because vegetation and chemical composition can affect radiative forcing and water vapor concentrations, these must also be treated in coupled simulations. The emerging results from the World Ocean Circulation Experiment (WOCE), the Global Energy and Water Cycle Experiment (GEWEX), and other field and analysis programs are providing the opportunity for improving the performance of coupled models.

(5) More explicit representation of land-surface processes (figure 10), including vegetation, soil characteristics, and CO2 and O3 effects on stomatal resistance, will reduce uncertainties in estimates of soil moisture, summertime continental drying, and changes of regional climate.

Basis-Explicit treatment of vegetation provides representation of the seasonally varying albedo, the diurnally and seasonally varying pattern of evapotranspiration, and other factors, permitting better representation of the diurnal temperature and humidity. Explicit treatment of soil characteristics permits treatment of runoff and soil moisture, significantly improving representation of the hydrologic cycle. Parameterizations that are significantly better than those that have been used in past studies will be available for use, but still require extensive testing and evaluation before implementation and application in GCMs.

(6) Sub-continental and regional scale features of global climate change can be better represented by an intensified focus on tailoring global predictions to specific regions using both finer scale models and empirical techniques.

Basis-Weather forecasts are successfully tailored to specific regions using both finer scale models and empirical techniques that derive local and regional features from large-scale atmospheric conditions. These techniques, including both regional models and statistical methods, have been demonstrated in studies that predict local conditions given large-scale conditions. Application is starting to be done and awaits only commitment of resources and analytic effort. Results of this type will permit significant testing and improvement of the capabilities for estimating regional vulnerabilities of ecosystems and socio-economic systems to climate change.

(7) Model comparisons against observations and with other models can accelerate the rate of model improvement.

Basis-Important new data sets are being developed that document the climatic changes and fluctuations of the 20th century, including improved estimates of changes in factors (e.g., greenhouse gas concentrations, volcanic aerosols, sulfate aerosols, ozone concentrations, ozone precursors, solar variability, ENSO events, etc.) that are likely the primary causes of these variations. Comparison of results of models making these simulations with each other and with the observational record can identify systematic errors and the strengths and weaknesses of alternative model formulations. Extension of these validation and intercomparison efforts to include atmospheric, oceanic, land surface, atmospheric chemistry, and coupled models is underway; more intensive efforts would likely accelerate progress.

(8) Improved reconstruction, simulation, and analysis of preindustrial and paleoclimatic periods can help assess model projections of climate sensitivity and variability, and lead to enhanced model credibility.

Basis-Successfully demonstrating the capability of models to simulate known paleoclimatic states will increase the confidence in a model's ability to predict future climatic scenarios. Although no past climatic periods are precisely similar to the present, reconstruction and diagnosis of climate changes and states prior to the industrial period provide the natural context to which projected anthropogenic climatic changes can be compared (figure 11). The past 1,000 years provides an opportunity to understand natural climate variability; the transition from the Last Glacial Maximum (18,000 years ago) to the current interglacial provides a period of relatively rapid warming; the last glacial exhibits periods of apparently rapid climatic shifts and changes in ocean circulation (figure 12); periods during the Pliocene to the Cretaceous provide examples of warmer conditions, often with different orography and/or geography. Comparison of changes in climatic forcing with changes in climate across these periods allows estimation of processes and conditions ranging from natural variability to global climate sensitivity and its latitudinal variation. Model simulations of these periods can indicate the influence of factors that cause climatic change and can identify features that current models and understanding are unable to explain, such as changes that may not previously have been seen in the recent climatic record (e.g., relatively rapid and sharp climatic shifts). Several projects are underway to reconstruct the climates of past warm and cold periods and to compare model simulations to these reconstructions, looking at changes in the mean, in rates of change, and in initiation of climatic shifts.

(9) Improving the representation of atmospheric chemistry and of vegetation and soils is needed to improve prediction of radiative feedbacks and to allow calculation of the effects of other types of global environmental change.

Basis-To treat the effects of climate forcing by aerosols (both direct radiative effects and possible indirect effects on cloud radiative properties and atmospheric chemistry) and because of the indirect effects of climate change and non-greenhouse gases on the concentrations of greenhouse gases, especially ozone, it is becoming increasingly important to account for these effects in climate simulations. While this can be done to some extent parametrically, there is an increasing need to explicitly treat these processes in climate simulations. Similarly, changes in the structure and functioning of major ecological systems can affect global biogeochemical cycles, the evapotranspiration and runoff of water, and surface reflectivity and roughness in ways that must also be accounted for in climate simulations if uncertainties are to be reduced. Such changes can be induced by a changing climate or by changes in land use or land-use management. With the development of global chemistry models, land-use models, and vegetation models (and related models of the effects of ocean biogeochemistry on the climate), opportunities are growing for doing so as supercomputer resources and speed increase.

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