In this study,based on the 1-7 day precipitation forecasts from the ECMWF,JMA,UKMO and NCEP in the TIGGE dataset and the hourly precipitation data merged by China Automatic Weather Station(CAWS) and CMORPH precipitation products as the observation data,the precipitation forecast in China is calibrated by using the frequency matching method(FMM).First,the Kalman filter was used to improve the statistics of the precipitation frequency.China was divided into seven sub-regions for the FMM calibration of the precipitation forecasts in accordance with its different precipitation intensity in various regions.The results show that FMM can significantly reduce the forecast error of precipitation intensity and area.Overall,FMM can improve the forecast skill of precipitation at different thresholds.After calibration,the ETS score of the precipitation forecast is significantly improved,and the false alarm rate of light rain and the missing rate of heavy rain are considerably reduced.In addition,the forecast skill for "rain or no rain" events is significantly improved.In addition,FMM can bring the forecast rainfall area closer to the observed values,particularly reducing the false alarm rate of light rain in a vast area.FMM can only improve the intensity and scope of the precipitation by means of adjusting the amount of rainfall.However,the location and shape of the heavy rainfall area cannot be improved.