The research on downscaling methods based on Fengyun meteorological satellite soil moisture data
投稿时间:2019-11-09  修订日期:2021-01-07  download
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盛佳慧 中国科学院上海技术物理研究所上海 200083
中国科学院智能红外感知重点实验室上海 200083
中国科学院大学北京 100049 
饶鹏 中国科学院上海技术物理研究所上海 200083
中国科学院智能红外感知重点实验室上海 200083 
Abstract:In view of the low spatial resolution of passive microwave soil moisture (SM) data, statistical and physical models including random forest (RF), polynomial fitting and DISPATCH are utilized to disaggregate the FY3B microwave SM product from 25 km to 1 km with the synergistic application of Optical/Thermal infrared (TIR) observations and surface elevation parameters. Meanwhile, considering different overpass times of FY3B and other relevant input data source observations, four data combinations are separately used to derive the spatially downscaled SM with above three downscaling method, and the optimized data combination of FY-3B downscaling is proposed by comparison and analysis. Validation is performed from April 1, 2015 to December 31, 2016 with the in-situ measurements of REMEDHUS network and the precipitation time series of ECA&D meteorological site. Experimental results show that RF-based method can achieve the highest comprehensive downscaling accuracy and the best model fitting effect. In addition, the effect of applying FY-3B ascending data to downscale turns out to be better.
keywords:Soil moisture  FY3B/MWRI  MODIS  downscaling  random forest  DISPATCH  polynomial fitting  REMEDHUS
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Copyright:《Journal of Infrared And Millimeter Waves》