geographic extent of the domains is much smaller, regional models can solve the equations at higher resolution (currently 30–50 km for most operational regional numerical weather prediction models). These regional models are usually nested in global models (or analyses), and more than one level of nesting can be incorporated. Finer-scale cloud-resolving models (CRMs) can simulate clouds with realistic representations of microphysical processes. A basic research technique in the GCIP coupled modeling effort is to use smaller-scale, high-resolution models and observations to improve the parameterizations of critical processes in larger-scale models. It should be noted, however, that climate simulations are not yet possible with CRMs because of the extensive computational requirements. GCMs and regional models will continue to play a key role in modeling long time scales and providing information about remote variations and their influence on moisture and energy transport into and out of smaller-scale models.


Before GCIP, most of the atmospheric parameterization effort was concerned with atmospheric processes. Of great importance to GCIP, however, is how atmospheric models interact with and represent the land surface. Early GCMs did this by prescribing surface temperature and wetness, and hence the partitioning of incoming radiation. Subsequently, pioneering interactive land surface parameterizations (LSPs) were developed by Manabe (1969), and others soon followed. These LSPs were single bucket-type parameterizations, which ignored important nonlinearities, especially in the dependence of precipitation infiltration-runoff partitioning on soil moisture.

Later LSPs included vegetation effects. The Biosphere-Atmosphere Transfer Scheme (BATS) of Dickinson (1986, 1993), utilized in the early National Center for Atmospheric Research (NCAR) models, is a good example (Figure 2.1). Other models include those of Sellers (1986), Bonan (1996), and Cuenca et al. (1996). Many processes are now included in these LSPs. Just as the early weather models increased their number of levels to deal with the complexity of the atmospheric vertical structure, so too have LSP modelers increased the number of subsurface levels. This increased number of levels now allows a fast upper soil moisture layer, as well as a root zone and subsurface storage region. The vertical distribution of moisture through vegetation as well as ground diffusion are important components of the models. Also important are the vegetation characteristics (e.g., height, density, etc.) which affect variables such as interception, evaporation, radiation, and wind speed.

Although the land surface was previously thought to be important, atmospheric modelers mostly believed that it played only a minor role in climate variability. GCIP has helped to change this perception. The recent improvement in the new European Center for Medium-Range Weather Forecasts (ECMWF) model in depicting the 1993 heavy rainfall over the Mississippi and the attribution

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