As one of the means for bridging the gap between low resolution data obtained from weather models and those required in the basin scale,statistical downscaling has become an important field of study,due to its relative simplicity and practicability,along with its many flexible methods.More accurate forecast results can be obtained by the statistical downscaling method of establishing the function between the low-resolution raw model output and high-resolution prediction variables.With the partial correlation-based method,forcing factors are sought for the precipitation over the middle and lower reaches of the Yangtze River Basin in June and July,and a statistical downscaling model is established for the precipitation.The major forcing factors for the precipitation over the region include the 850 hPa geopotential height over the western Pacific(W_PH8) and the sea surface temperature in the Kuroshio extension(K_SST).The W_PH8 may indicate the influence of the western Pacific subtropical high on the rainfall,while the K_SST may reflect the variability of the Kuroshio extension.A regression statistical downscaling model based on W_PH8 and K_SST shows good performance in fitting the variability of early summer rainfall in the middle and lower reaches of the Yangtze River Basin,and the model also shows strong robustness in the independent validation.In the future the statistical downscaling model can be used for downscaling output from seasonal forecast numerical,and improving the middle and lower reaches of the Yangtze River Basin early summer rainfall prediction.