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作 者:Lian He Senwen Huang Fengming Hui Xiao Cheng
机构地区:[1]School of Geospatial Engineering and Science,Sun Yat-Sen University,and Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China [2]Key Laboratory of Comprehensive Observation of Polar Environment(Sun Yat-Sen University),Ministry of Education,Zhuhai 519082,China
出 处:《Acta Oceanologica Sinica》2024年第3期127-138,共12页海洋学报(英文版)
基 金:The National Natural Science Foundation of China under contract Nos 41830536 and 41925027;the Guangdong Natural Science Foundation under contract No.2023A1515011235;the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.311021008.
摘 要:The aim of this study was to develop an improved thin sea ice thickness(SIT)retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data.This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort,Chukchi,East Siberian,Laptev and Kara seas and utilized the microwave polarization ratio(PR)at incidence angle of 40°.The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact,reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature.The relationship between the SIT and PR was found to be almost stable across the five selected regions.The SIT retrievals were then compared to other two existing algorithms(i.e.,UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen)and validated against independent SIT data obtained from moored upward looking sonars(ULS)and airborne electromagnetic(EM)induction sensors.The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error(RMSE)being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data.The proposed algorithm can be used for thin sea ice thickness(<1.0 m)estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.
关 键 词:Arctic sea ice sea ice thickness remote sensing Soil Moisture Active Passive(SMAP) Soil Moisture Ocean Salinity and Soil(SMOS)
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