%0 Dataset
%T Three-hour precipitation fusion dataset based on random forest model in Muli Kuangqu, Qinghai Province (1990-2020)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/75308376-f417-457b-ace1-0f5a5f043919
%W NCDC
%A quan chen
%A zhang xiao dan
%A zhao tong
%A liu chang
%K Precipitation data fusion;BP-lsm;Random Forest;high-altitude areas
%X In response to the problem of insufficient accuracy of precipitation data due to complex terrain and sparse ground observation stations in Qinghai Province, multi-source data such as GPM, ERA5, and DEM were integrated, based on BP-LSTM and random forest model, a high-precision precipitation dataset with 0.01° spatial resolution and 1h/3h temporal resolution was generated. The verification showed that RMSE was ≤2.5mm, and the precipitation event capture rate was ≥90%, providing data support for regional ecological assessment, hydrological simulation, etc.