We integrate various reanalysis, meteorological observation, and satellite precipitation datasets, including CRU (Climate Research Unit), ERA5 (European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version5), MERRA2 (Modern-Eta Retrospective Analysis for Research and Applications version2), CMAP (Climate Prediction Center (CPC) integrated analysis of monthly precipitation), GPCP (Global Precipitation Climatology Project) and GPM (Global Precipitation Measurement), to create a new monthly precipitation product with a spatial resolution of 0.1° × 0.1° (latitude × longitude) during the period from 1980 to 2019 in the arid and semi-arid regions of China (ASRC). The new product was validated with observations at different temporal scales (e.g., monthly to yearly variability and trends). The results show that the new product improves the accuracy of precipitation with the lower bias of 1.0 mm/month and the highest correlation coefficient of 0.998 was achieved with observation. The probability distribution functions (PDF) and standardized precipitation index (SPI) of the integrated precipitation are closer to observation than other reanalysis datasets. The integrated product presents an increasing trend of 0.05 mm/year from 2001 to 2019 and a relative drying pattern during the earlier 20 years as well as a wetting pattern with enhanced water cycle during the last 20 years in the ASRC.