Precipitation is one of the most important climatic elements. It is one of the main components of the global water cycle which has influences on socioeconomic development, environmental planning, and life on the Earth. Proper knowledge of the spatial and temporal distribution of precipitation cannot be acquired unless there is a good distribution of meteorological stations. Despite the importance of precipitation, rain gauge datasets for hydroclimate applications, due to some limitations, such as the lack of long data records, the distribution and density of meteorological stations, and late updating, particularly in the case of complex terrains like those in Iran, has been a huge challenge both spatially and temporally. Gridded precipitation datasets are good alternatives for the monitoring of precipitation characteristics over regions where gaugebased observations are sparse or nonexistent. In the current study, the tempo-spatial accuracy of the ERA-5 database was evaluated in the estimation of precipitation over Iran during the statistical period of 1998-2019. For this purpose, the precipitation data of ERA-5 base with a spatial resolution of 0.25 degrees of arc was used in comparison with the data of meteorological stations. In order to evaluate the accuracy of the rainfall estimation of ERA-5, diffrent statistical methods including correlation coefficient (R), percentage bias (PBias), root mean square error (RMSE), probability of detection (POD), false alarm ratio (FAR), success threshold index (CSI) and Taylor diagram have been used. The findings showed that the ERA-5 database shows the spatial distribution pattern of precipitation in Iran well. Area-averaged correlation between the ERA-5 database and gaugebased observations is more than 0.9. There is a high agreement between the time series of precipitation values estimated by ERA-5 and the precipitation values observed on meteorological stations in most regions of Iran. The amount of precipitation estimated by the database in the rainy months is more than dry months. This overestimation is high in the high precipitation regions than in other areas of the country (PBias >100%). While in the dry interior regions of the country, the database has underestimated the amount of precipitation (PBias <100%). The RMSE values are more than 100 mm in January, February, March, April and December in the high precipitation regions on the Zagros heights in the west of the country and the southwest of the Caspian Sea. The RMSE value is less than 20 mm in most of the months of the year in the dry regions. The database correctly detects rainy days and dry days in the rainy months of the year over the rainy areas.
   The accuracy of detecting rainy days in the months of January to April, November and December is more than 0.9, and the rate of misdiagnosis of dry days in the mentioned months is less than 0.3. In general, the accuracy of detecting rainy and dry days reaches more than 0.6 in the high precipitation regions of the country.