Abstract: With the application of the artificial neural network(ANN) in the field of Atmospheric Science,a "bottle-neck" was found while the artificial neural network model was applied for weather forecast:the fitting precision of training sample could not be definitely determined to make the model showing its best forecasting capability.It was a key problem to be solved on the overfitting and generation capability of the ANN application theory area.Study on this problemis necessary for the further operating application of ANN in the field of Atmospheric Science.A new forecasting model has been proposed for model establishment by means of making a low-dimension ANN learing matrix through principal component analysis(PCA-ANN).The monthly rainf all of June、July and August were forecasted by using PCA-ANN,R-ANN(regression artificial neural network model) and SR(stepwise regression model) respectively.