Based on the BP-CCA method and the results of state-of-the-art climate prediction models, this paper discusses how to establish a statistical downscaling model with high predictive skills for summer precipitation in southwest China, and also investigates the predictability sources of the statistical downscaling mode. The predictive ability of the statistical downscaling model taking tropical sea surface temperature as the predictor is superior to that of 500 hPa geopotential height in Asia and the tropics as the predictor. When taking the tropical sea surface temperature as predictor, the predictive ability of statistical downscaling model is highly influenced by the second EOF mode of the tropical sea surface temperature, which is characterized by positive loading values in the tropical South-East Indian and Western Pacific regions, and negative loading centers in the tropical Middle and East Pacific region. This mode of the tropical sea surface temperature is highly correlated with the convection over Philippine Sea and the western Maritime Continent, which plays an important role in the Southwest China summer precipitation. The ECMWF and NCEP climate prediction model has high predictability of the second EOF mode of the tropical sea surface temperature. This feature helps to enhance the predictability of summer precipitation in Southwest China from the statistical downscaling model that taking the tropical sea surface temperature as the predictor.
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