A Gridded Monthly Precipitation Merged Rain Gauge and Satellite Analysis Dataset for the Tian Shan Range between 1981 and 2019

Abstract An accurate and reliable precipitation product on regular grids is essential for understanding trends variability within climate studies, weather forecasting, in hydrology agrometeorology applications. However, the construction of high-resolution spatiotemporal grid products challenging complex terrain with sparse rain gauge networks when only coarse spatial resolutions satellite data are available. The objective this study was to consequently provide a practical method create by merging quantitative observations from stations continuous information satellite-based estimate product. new gridded exhibits monthly temporal resolution 0.01° Tian Shan range, extending back 1981. To overcome limitation low densities distributions meteorological Shan, suitable interpolation Australian National University Spline (ANUSPLIN) used interpolate based situ data. then merged developed U.S. Geological Survey Climate Hazards Group. After evaluation validation using withheld comparison reference datasets, result indicated that considerable promise application terrain. can be widely applied expected construct high multiple sources. Significance Statement purpose dataset observation arid mountain regions. This important because precipitations model output detection mean extremes. Our results present guide frameworks datasets multisource sources regions topography, scarcity, ungauged collection.