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作 者:张大千 张录军[1,2] 储敏 张熠[1] ZHANG Daqian;ZHANG Lujun;CHU Min;ZHANG Yi(School of Atmospheric Sciences,Nanjing University,Nanjing 210023,China;Jiangsu Collaborative Innovation Center for Climate Change,Nanjing 210023,China;National Climate Center,Beijing 100081,China)
机构地区:[1]南京大学大气科学学院,江苏南京210023 [2]江苏省气候变化协同创新中心,江苏南京210023 [3]国家气候中心,北京100081
出 处:《极地研究》2025年第1期55-71,共17页Chinese Journal of Polar Research
基 金:国家自然科学基金(42175172,41975134)资助。
摘 要:本文将中国国家卫星气象中心提供的风云三号系列卫星(FY-3B、FY-3C和FY-3D)中提取的多卫星组合序列海冰密集度(sea ice concentration,SIC)产品(FY-3数据集),美国国家海洋和大气管理局提供的0.25°逐日SIC产品(OISST数据集)及美国国家冰雪数据中心提供的MASAM2和SSMISSIC产品(MASAM2数据集和SSMIS数据集)进行对比分析。结果表明:(1)FY-3数据集、OISST数据集和MASAM2数据集在大西洋扇区的平均均方根误差分别为0.15、0.13和0.13,在太平洋扇区的平均均方根误差分别为0.13、0.11和0.12,主要差异来自FY-3数据集对9月SIC数值的异常高估;(2)FY-3数据集的海冰范围偏差在全时段小于OISST数据集,2016年后小于MASAM2数据集,最小平均绝对百分比偏差为2.5%,在边缘冰区范围方面,FY-3数据集和MASAM2数据集在太平洋扇区存在严重低估(标准化平均偏差为45%);(3)FY-3数据集与OISST数据集的质量相当,与MASAM2数据集相比还有一定差距,尤其在长序列SIC反演产品方面。因此,建议在如何消除多颗卫星间的数据不一致性方面投入更多的开发研究工作。This study compared multisatellite composite sea ice concentration(SIC)data(the FY-3 dataset)retrieved by China’s National Satellite Meteorological Center’s Fengyun-3 series satellites(FY-3B,FY-3C,and FY-3D),with 0.25°daily SIC data(the OISST dataset)provided by the National Oceanic and Atmospheric Administration,and SIC data from MASAM2(the MASAM2 dataset)and SSMIS(the SSMIS dataset)provided by the National Snow and Ice Data Center.Analysis of these datasets revealed the following.(1)The average root mean square error(ERMSE)for the FY-3,OISST,and MASAM2 datasets in the Atlantic sector is 0.15,0.13,and 0.13,respectively;in the Pacific sector,the average ERMSE is 0.13,0.11,and 0.12,respectively.The main difference is overestimation of September SIC in the FY-3 dataset.(2)The deviation in sea ice extent in the FY-3 dataset is lower than that of the OISST dataset throughout the entire period and lower than that of the MASAM2 dataset after 2016,with a minimum mean absolute percentage error of 2.5%.In terms of marginal ice zone extent,the FY-3 and MASAM2 datasets both exhibit substantial underestimation(normalized mean bias:45%)in the Pacific sector.(3)Comprehensive comparison revealed that the quality of the FY-3 dataset is comparable with that of the OISST dataset,but that some discrepancies are evident relative to the MASAM2 dataset,especially for long-term sequence retrieval products.Therefore,it is recommended that research and development efforts be focused on eliminating data inconsistencies among satellite retrievals.
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