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《Remote Sensing Technology and Application》 2017-01
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Intercalibrating FY-3B and FY-3C/MWRI for Synergistic Implementing to Snow Depth Retrieval Algorithm

Wang Gongxue;Jiang Lingmei;Wu Shengli;Liu Xiaojing;Hao Shirui;State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing Science and Engineering,Faculty of Geographical Science,Beijing Normal University;National Satellite Meteorological Center,China Meteorological Administration;  
FY-3C/MWRI has been in operation since 30 July 2015,thus measuring microwave radiation of the Earth's surface jointly with FY-3B/MWRI.To ensure the reliability and consistency of MWRI data and synergistic implementation to snow depth retrieval algorithm,brightness temperatures at all channels from FY-3C/MWRI are calibrated against FY-3B/MWRI based on pseudo-invariant targets,i.e.,the Greenland ice sheet and Amazon rain forest.Then snow depths and snow covered areas over China are estimated by utilizing FY-3B/MWRI operational algorithm from FY-3B,FY-3C,and calibrated FY-3C/MWRI data,of those consistency analyses are conducted separately.And impact of intercalibration on snow depth retrieval is evaluated with in situ observations acquired by meteorological stations during 2013~2014winter.It is indicated that FY-3Band FY-3C/MWRI data performs good consistency,though brightness temperatures from FY-3C/MWRI are little warmer than that from FY-3B/MWRI at most channels.The average relative bias between FY-3Cand FY-3BMWRI are generally ranging from-0.87 to 2.05 Kdepending on channels.In addition,a little high percent(10%~18%)of absolute bias greater than 3Koccurs at 18 H,36V,89 H and 89 Vchannels.Evaluations show that FY-3Band FY-3C/MWRI generate similar snow covered area and snow depth data,and that intercalibration has little impact on snow covered area estimating.FY-3C/MWRI derives snow depth a bit more accurately and MWRI snow depth retrieval is more robust after intercalibration.
【Fund】: 国家重点基础研究计划(2015CB953701 2013CB733406);; 中国科学院战略性先导科技专项"全球水循环观测卫星背景型号研究"(XDA04061200);; 国家自然科学基金项目(41671334)资助
【CateGory Index】: P407.7
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