Abstract: The authors constructed ar tificial neural network(ANN) models of short-term climate forecasting to predict summer(June-August) precipitation in Hubei Province.The inputs of the model were the extended empirical orthog onal functions(EEOF) of the 500hP a height field,the sea level pressure field in the Northern Hemisphere and sea surface temperature field over the Pacific before summer flood season(February-April),and the out puts were the empirical orthogonal functions of the summer precipit ation to tals of represent at ivestations.The cross-validation over 41 years has shown that the forecasting skill score of ANN models is 0.246.Though the forecasting skills year by year are still unstable,positive skills existobviously statistically for summer precipitation for ecasting in Hubei Province.