Abstract
Statistical downscaling models for precipitation in Scania, southern Sweden, have been developed and applied to calculate the changes in the future Scanian precipitation climate due to projected changes in the atmospheric composition. The models are based on multiple linear regression, linking large-scale predictors at monthly time resolution to regional statistics of daily precipitation on a monthly basis. To account for spatial precipitation variability within the area, the precipitation statistics were derived for different regions in Scania. The final downscaling models, developed for different regions and seasons, use atmospheric circulation, large-scale humidity and precipitation as predictors. Among the precipitation statistics examined, only the models for estimating the mean precipitation and the frequency of wet days were skilful. Based on the Canadian Global Circulation Model 1 (CGCM1), a future scenario of these two statistics was created. The downscaled scenario shows a significant increase of the annual mean precipitation by about 10% and a slight decrease in the frequency of wet days, indicating an increase in the precipitation amounts as well as in the precipitation intensity. The main increase of precipitation amounts and intensity occur during winter, while the summer precipitation amounts decrease slightly. The seasonal changes found in precipitation are likely attributed to changes in the westerly flow of the atmospheric circulation.
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