Downscaling and Merging of Daily Scale Satellite Precipitation Data in the Three River Headwaters Region Fused with Cloud Attributes and Rain Gauge Data

Complex terrain, the sparse distribution of rain gauges, and poor resolution quality satellite data in remote areas severely restrict development watershed hydrological modeling, meteorology, ecological research. In this study, based on relationship between cloud optical physical properties precipitation, a daily geographically weighted regression (GWR) precipitation downscaling model was constructed for Three Rivers Source region, China, period from 2010 to 2014. The GWR combined three different datasets (CMORPH, IMERG, ERA5) which were downscaled coarse (0.25° 0.1°) fine (1 km). At same time, preliminary results calibrated verified by employing geographic difference analysis (GDA) ratio (GRA) methods with rainfall data. Finally, analytical hierarchy process (AHP) entropy weight method (EW) adopted fuse into merged dataset (MSP), provides higher (CC = 0.790, RMSE 2.189 mm/day, BIAS 0.142 mm). summary, calibration fusion scheme proposed study is suitable obtaining high-resolution region complex climate topography.