Based on the basic principle of dynamical analogue prediction, the authors have established the optimal dynamic multi-factor schemes to revise prediction errors. In this paper, the authors studied the correlations between the interactions of prophase key factors and the precipitation of rainy season in China and found the key atmospheric circulation predictor. According to the predictors which are abnormal in prophase, the authors compressed the dimensions of the factors to select the similar years through EOF analysis. Furthermore, a new dynamical analogue prediction scheme is constructed, which is based on the anomalous signals of prophase environment field. Analyses show that there is a good corresponding relationship between precipitation in North China and numbers of atmospheric circulation factors which are abnormal in prophase. The authors developed a comprehensive scheme to revise prediction errors of numerical model combined with the abnormal factors scheme and the optimal dynamic multi-factor scheme. Through the diagnostic analysis, the authors found that the comprehensive scheme has a good adaptability. Results of independent sample return during 2003－2009 show that the anomaly correlation coefficient (ACC) score has increased from 0.38 to 0.61. The similarity revised method has further improved the prediction capacity of numerical model and has a good application prospect for summer precipitation in North China.