response to radiative forcing changes, experiments employing fully coupled land-ocean-atmosphere models to study regional past climate change are just now under way. It is likely that details of stratospheric dynamics and chemistry, ocean circulation, vegetation and soil dynamics, and mechanisms of land-ocean-atmosphere coupling are all important in describing past regional-scale changes in climate. A particular challenge is to quantify the role of radiative forcings (versus other mechanisms) in effecting coherent climate change in widely separated geographical regions, as is evident in paleoclimate proxies on multiple and often abrupt timescales (Rial et al., 2004).

Applications of climate models include developing better understanding of processes and predicting future conditions. Compared to simulating the weather, climate modeling faces the challenges of longer timescales, ranging from years to centuries and longer. Climate modeling also requires the accurate simulation of each important component of the climate system, including the atmosphere, oceans, land surface, and continental ice fields, as well as realistic estimates of external forcings (i.e., solar, volcanoes). Physical, biological, and chemical processes taking place in each of these components interact with each other across the spectrum of space and timescales. In simulating future climate, models must take into account how humans will affect emissions of greenhouse gases and aerosols as well as modify land use and land cover. Because future human activities are inherently uncertain, model projections of future climate are typically computed for multiple scenarios of future emissions.

Historical data have been used extensively to evaluate climate models. The Atmospheric Model Intercomparison Project (AMIP) is an excellent example of model validation (Gates et al., 1998) based on archived atmosphere and sea surface data. Such model evaluations need to be extended to encompass the spectrum of important climate forcing effects on such societally important quantities as water resources, agricultural and natural vegetation growth, and air pollution. Can skillful forecasts of changes in these quantities be made as a function of radiative and other climate forcings? These issues are regional in scale, such that validation of model process simulation and forecast skill must be completed at these subglobal scales.

A particular challenge for global climate models is modeling forced climate change over the last few decades. This is the time period with the greatest change in well-mixed greenhouse gases as well as the most complete observational datasets. Some studies have found discrepancies be-