高精度高时空分辨率的降水资料能够提高我们对流域尺度水文的理解能力，进而提高陆面过程和状态的模拟能力。然而采用传统的地面观测，遥感产品和区域气候模拟等方法，很难为区域提供高时空分辨率高精度的网格降水资料。本项目拟在区域气候模式--CWRF模式的基础上，同化以FY-系列、TRMM、GPM、AMSR-E和MODIS等多源主被动微波遥感为主的降雨产品和雪深产品，提高区域气候模式的降水（雨雪）模拟精度，并构建高分辨率未来气候变化情景。拟达到以下目标：（1）构建区域气候模式遥感降水资料同化系统框架；（2）充分有效地融合主被动微波遥感降雨与降雪产品，提高区域气候模式降水的模拟精度；（3）建立降水同化产品的评估体系和选择合理的高时空分辨率的降水同化产品评价指标；（4）未来高时空分辨率气候情景的构建，尤其是未来降水要素的构建。

Long term precipitation with high spatio-temporal and precision can improve our understanding on the regional hydrology, thereby increasing the ability of land surface hydrologica precesses and the state of the simulation. Traditional ground-based observations, remote sensing, and regional climate modeling, however, difficult to provide high spatio-temporal precipitation data. So in this project, 4D-Var is proposed to be used to assimilate rainfall rate remote sensing data (the merging data of FY series, TRMM and GPM) and snow depth remote sensing data (the merging data of MODIS and AMSR-E) into Climate extension Weather Research & Forecasting Model (CWRF) to yield high spatial-temporal resolution and accurate precipitation data. To realize the following objectives: ( 1) construction of a regional climate model precipitation remote sensing data assimilation system framework ; ( 2 ) the full and effective integration of active and passive microwave remote sensing of rainfall and snowfall products to improve regional climate model precipitation simulation accuracy ; ( 3 ) the establishment of precipitation product evaluation system; and ( 4 ) the high spatial and temporal resolution of future climate scenarios , especially in building the future of precipitation elements .