Based on the daily 500 hPa geopotential height data between June and August, 2007—2012, the historical reanalysis grid data of NCEP global 2.5°×2.5°and the daily precipitation data of 158 meteorological stations in north of Zhejiang province, the relationships between local precipitation and large-scale precipitation in different atmospheric circulations are studied in this paper.The BP neural network combined with 4 forecasting objects and corresponding predictor variables in different circulations are employed to design 4 downscaling function models to approximate the precipitation data.The 4 models are used to simulate and forecast the daily precipitation data of 158 meteorological stations in north of Zhejiang province, and the results show that the BP neural network model with 2 hidden layers has good simulation accuracy.Through Jenkinson atmospheric circulation to classify the precipitation into SE(SE type), NW(NW type), C(C type) and SW(SW type), NW type and C type generally outperform the SW type and SE type in simulation of the extreme precipitation.Compared with the area of Ningbo and Zhoushan, other areas of north Zhejiang reflect the greater error value from 4 atmospheric circulations.The prediction accuracy of the downscaling model is the best of three types of rainstorm forecast after categorizing rainfall into different levels.