The uncertainty of the satellite precipitation products limits their applicability in complex terrain areas. This paper evaluates the applicability of the new rainfall products, GPM （Global Precipitation Measurement） IMERG （Integrated MultisatellitE Retrievals for GPM） and ERA5 precipitation in Yunnan Province area based on the meteorological data. The data of a total of 125 weather stations from April 2014 to June 2018 are used to evaluate and compare the accuracies of GPM IMERG and ERA5. The correlation coefficient (R), root mean square error (RMSE), relative bias (BIAS), Mean Absolute Error (MAE) and the classification statistical analysis indexes (POD, FAR, CIS) are used to assess the applicability of GPM IMERG and ERA5. The result shows that: The two kinds of data have the problems of overestimation of daily precipitation of light rainfall and underestimation of daily precipitation of moderate and above rainfall, and ERA5 data is more prominent in this respect. GPM IMERG data have both higher false and missing alarm rates, while ERA5 data have seriously higher and lower missing rate, especially in light rain days. The areas with more (less) light rain days are in good agreement with the two areas with higher missing (false) rates. In autumn, the precipitation data accuracy of GPM IMERG is the highest in different rain intensity ranges. In winter, there are different performances: underestimation of low rain intensity and overestimation of high rain intensity. For the medium and low rainfall intensity of below 20 mm/d, the errors between the two precipitation data and ground station data are relatively small, and the errors increase with the increasing rain intensity. When the rain intensity is greater than 20 mm/d, the difference between the two data and the station increases more significantly with the increasing rain intensity. With the increase of slope and fluctuation, the accuracy of two kinds of precipitation data presents a trend of deterioration. The evaluation indexes show that GPM IMERG precipitation data have higher accuracy in Yunnan. The research results provide a reference for the application and development of agriculture, water conservancy, hydrology, meteorology and other related disciplines.