A study of multiyear ice concentration retrieval algorithms using AMSR-E data

HAO Guanghua SU Jie

郝光华, 苏洁. 基于AMSR-E数据的多年冰密集度反演算法研究[J]. 海洋学报英文版, 2015, 34(9): 102-109. doi: 10.1007/s13131-015-0656-1
引用本文: 郝光华, 苏洁. 基于AMSR-E数据的多年冰密集度反演算法研究[J]. 海洋学报英文版, 2015, 34(9): 102-109. doi: 10.1007/s13131-015-0656-1
HAO Guanghua, SU Jie. A study of multiyear ice concentration retrieval algorithms using AMSR-E data[J]. Acta Oceanologica Sinica, 2015, 34(9): 102-109. doi: 10.1007/s13131-015-0656-1
Citation: HAO Guanghua, SU Jie. A study of multiyear ice concentration retrieval algorithms using AMSR-E data[J]. Acta Oceanologica Sinica, 2015, 34(9): 102-109. doi: 10.1007/s13131-015-0656-1

基于AMSR-E数据的多年冰密集度反演算法研究

doi: 10.1007/s13131-015-0656-1

A study of multiyear ice concentration retrieval algorithms using AMSR-E data

  • 摘要: 近年来,北极多年冰的面积和范围快速减少,由此产生的气候效应具有重要意义,因而北极多年冰的反演的精度至关重要。本文较系统地总结分析了前人使用微波数据反演多年冰的3种算法,这些算法都能够很好的反演北极总的海冰密集度,但是对于多年冰的反演有较大的差异,相比于Wang和Lomax算法得到的多年冰面积在秋季和冬季过多而且变化明显,NASA TEAM算法得到的多年冰面积要稳定。本文在NASA TEAM算法的基础上改进了多年冰反演算法,同本文定义的参考多年冰面积相比,1-3月平均差异和均方根差异分别为0.65×106km2和0.69×106km2,9-12月平均差异和均方根差异分别为-0.06×106km2和0.14×106km2,同周平均的冰龄数据得到的海冰范围相比较,平均差异和均方根差异分别为0.69×106km2和0.84×106km2,在四种算法中,本文算法的差异最小。
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出版历程
  • 收稿日期:  2014-09-19
  • 修回日期:  2015-03-23

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