COMPARISON OF 2 GENERAL-CIRCULATION MODELS TO DOWNSCALE TEMPERATURE AND PRECIPITATION UNDER CLIMATE-CHANGE

A semiempirical approach for downscaling general circulation model (GC M) based daily atmospheric circulation patterns (CP) and predicting lo cal climatological variables under climate change is developed. Specif ically, the daily 500-hPa surface outputs of the Canadian Climate Cent er (CCC) and Max Planck Institute (MPI) (Germany) GCMs are linked stoc hastically, using a split sampling approach, to local temperature and precipitation in Nebraska. Three series of data are analyzed: historic al data, 1 x CO2 GCM results and 2 x CO2 GCM results. Between these th ree data sets, no significant difference can be detected in either CP typology (constructed by principal component analysis and k means meth od) or stochastic properties of daily time series (Markov matrix). On the other hand, the average geopotential height of the 500-hPa pressur e field exhibits significant change, labeled the Delta CO2 effect, bet ween the 1 x CO2 and 2 x CO2 cases. Accordingly, climate change is ass umed to be represented by the historical average geopotential height a ugmented by the Delta CO2 increment. It is found that both the CCC and MPI GCMs lead to predicting a winter temperature increase of 3 degree s-6 degrees C, a smaller but significant increase in spring and fall t emperatures, and no increase in summer. The probability of precipitati on occurrence is found to remain almost unchanged, as well as the dry period duration. The estimates of local response to climate change dep end upon the location and the GCM used for downscaling the CP. The MPI GCM, which includes an ocean-atmosphere coupling, appears to yield sm aller downscaled changes than the purely atmosphere-based CCC GCM.