ERA5 is the latest generation of ECMWF reanalysis product. Its precipitation data can be used to analyze the spatial and temporal characteristics of precipitation, extracting rainstorm and flood events, driving crop models, hydrological models, and land surface models. Studies on the effects of using reanalysis data to drive various models to simulate climate change are becoming more common in the context of climate change. However, as atmospheric reanalysis data, the data quality of ERA5 precipitation data will be affected by the errors of forecast products, observation data, and assimilation methods. The precision of reanalysis data will influence the uncertainty of related study results. As a result, verifying and evaluating the accuracy of reanalysis data is both necessary and urgent. To investigate the applicability of ERA5 precipitation data in China, daily precipitation data from 728 Chinese sites were used as a reference to examine the accuracy of ERA5 reanalysis precipitation data at various time scales (month, quarter), different climate zones and different elevation gradients using the Pearson correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), probability of detection (POD), false alarm rate, and equitable threat score. Furthermore, the capability of ERA5 to depict heavy rain and drought events was investigated. The results demonstrate that there are spatial and temporal differences in the ability of ERA5 precipitation data to identify daily precipitation events. Among the eight climatic zones, the north temperate zone has the highest accuracy. The r, RMSE, and MAE of ERA5 daily precipitation and station observation are 0.587, 4.040 mm·d^-1, and 1.472 mm·d^-1, respectively, in the north temperate zone. Precipitation data from the ERA5 are less accurate in the summer and autumn than in the winter and spring. The accuracy of ERA5 precipitation data in areas with elevations greater than >500 m is lower than in areas with elevations of less than ≤500 m. When the ERA5 data is used to identify the heavy rain, there is a large deviation from observations of the stations, and the larger the threshold (i.e., the stronger the heave rain), the larger the deviation is. The accuracy of standardized drought index (SPI) of different time scales calculated using ERA5 is different, varies with SPI on a three-month time scale having the highest accuracy. When using ERA5 data to identify drought events, the lower the threshold (that is, the greater the severity of the drought), the greater the error. Generally speaking, the drought capture ability of the north temperate zone, south temperate zone, and north subtropical zone is better. This research broadens the scope of validation of climate data sets and serves as a model for future research. These findings serve as a reference for related studies considering whether to use ERA5 data, as well as a tool for analyzing the uncertainties of related studies.