Through modeling and international exchange, the Abdus Salam International Centre for Theoretical Physicsis fostering advanced climate research in countries where scientific resources are often scarce. P opulations in economically developing nations (EDNs) depend extensively on climate for their welfare (e.g., agriculture, water resources, power generation, industry) and likewise are vulnerable to variability in the climate system, whether due to anthropogenic forcing or natural processes. Furthermore, changes in atmospheric composition (e.g., greenhouse gases and aerosols) and land cover are likely to significantly alter regional climates (Nakicenovic et al. 2001), thereby affecting local socioeconomic development and livelihoods of EDN populations. Therefore, the evaluation of climate change and variability at seasonal-to-multidecadal time scales is of great benefit to these regions.Climate models, both global and regional, are the primary tools that aid in our understanding of the many processes that govern the climate system. In the past, a lack of computational resources has hindered the use of climate models by EDN scientists. However, in the last decade the computing power of the common desktop personal computer (PC) has dramatically increased •

Abstract.A new large-scale cloud and precipitation scheme, which accounts for the subgrid-scale variability of clouds, is coupled to NCAR's Regional Climate Model (RegCM). This scheme partitions each grid cell into a cloudy and noncloudy fraction related to the average grid cell relative humidity. Precipitation occurs, according to a specified autoconversion rate, when a cloud water threshold is exceeded. The specification of this threshold is based on empirical in-cloud observations of cloud liquid water amounts. Included in the scheme are simple formulations for raindrop accretion and evaporation. The results from RegCM using the new scheme, tested over North America, show significant improvements when compared to the old version. The outgoing longwave radiation, albedo, cloud water path, incident surface shortwave radiation, net surface radiation, and surface temperature fields display reasonable agreement with the observations from satellite and surface station data. Furthermore, the new model is able to better represent extreme precipitation events such as the Midwest flooding observed in the summer of 1993. Overall, RegCM with the new scheme provides for a more accurate representation of atmospheric and surface energy and water balances, including both the mean conditions and the variability at daily to interannual scales. The latter suggests that the new scheme improves the model's sensitivity, which is critical for both climate change and process studies. IntroductionIn many applications of the National Center for Atmospheric Research (NCAR) Regional Climate Model (RegCM), an accurate simulation of the energy and water cycles is crucial [Giorgi and Mearns, 1999]. The presence of clouds and resulting precipitation is the primary control on these cycles. It is therefore important to accurately represent cloud processes in many modeling applications. Clouds, however, are often poorly represented in both regional and global climate models (RCMs and GCMs, respectively) partly because some of the key cloud processes occur at spatial and temporal scales not resolved by current models. This study presents a simple, yet physical, resolvable-scale (nonconvective) moist physics and cloud scheme for the NCAR RegCM that accounts for the subgrid variability of clouds, the accretion of cloud water, and the evaporation of raindrops.The response of the climate system to changes in greenhouse gases, sulfate aerosols, soil moisture, and vegetation is strongly influenced by cloud processes.

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