Evaluation of the Annual Cycle of Precipitation over the United States in GCMs: AMIP Simulations

Abstract

The monthly mean precipitation patterns of the Atmospheric Model Intercomparison Project decadal simulations over the United States and adjoining oceans are intercompared. A simple harmonic analysis of the 12-month seasonal mean precipitation values and a principal component (PC) analysis of the 120 monthly values were carried out. Emphasis is placed on the basic seasonal variation for three subregions: the eastern and central United States and the U.S. west coast. It is vital for GCM simulations to accurately portray the seasonal cycle. The results indicate the following. 1) There are problems for almost all the models in capturing the seasonal variation of the precipitation over the eastern United States. The models typically overemphasize the summer?spring rainfall amounts. The PC analysis indicates that many of the models tend to extend the precipitation regime typical of the central United States too far to the east, resulting in a precipitation maxima occurring in the summer for the eastern region. 2) The seasonal variation of the West Coast is handled with the greatest fidelity. This result cuts across all the models and may be attributable to the fact the SST forcing is specified and common to all the simulations. The common SST forcing is apparently a dominant factor in determining this region?s precipitation climatology. 3) On the space scales of the regions selected, there is little consistent evidence that points to any specific model feature as a predictor of model performance. None of the obvious candidates such as horizontal resolution, convective closure schemes, or land surface schemes are reliable discriminators of a model?s ability to simulate precipitation. 4) For one smaller subregion centered over Arizona, chosen because of the dominance of the semiannual cycle, there is evidence that increased horizontal resolution has an effect. For this intermountain region the higher-resolution models as a whole do better than the low-resolution models. However, even in this case there is enough variation among the individual simulations to obscure the conclusion that increased horizontal resolution is a necessary or sufficient quality to produce a reliable simulation. 5) The models tend to have less interannual variation than the observations with more variance being explained by the leading (annual cycle) PC, whereas the observations have a less peaked spectrum.