Satellite precipitation products play a key role in compensating for the lack of spatial coverage of ground-based observatories,but their low spatial resolution and limited accuracy restrict their direct use in hydrological and climatological studies.Focusing on Inner Mongolia Autonomous Region,this work aims to enhance the value of data application by evalua-ting the Global Precipitation Climate Centre(GPCC)precipitation products at different resolutions and applying spatial downscaling techniques to improve data quality.This work adopted 0.25°resolution GPCC data,which is then fused by multi-source geographic information,constructed multiple linear regression models to implement downscaling,and success-fully increased its resolution to 1 km×1 km,and the models relied on the measured precipitation data for validation.The results show that the R2 values of all models are maintained above 0.881,the root mean square error is lower than 37.348 mm,and the deviation does not exceed 0.041 mm,which proves that the downscaled data are accurate and reliable,and have good geographical adaptability.The research results can provide high-resolution and high-quality satellite precipitation data support for in-depth study of the water cycle process in Inner Mongolia Autonomous Region,guidance of agricultural and animal husbandry production practices,and accurate monitoring of drought conditions.
关键词
全球降水气候中心(GPCC)/降水/多元线性回归模型/空间降尺度
Key words
global precipitation climate centre(GPCC)/precipitation/multiple linear regression model/spa-tial downscaling
维普
万方数据