极地研究

极地研究 ›› 2019, Vol. 31 ›› Issue (2): 179-190.DOI: 10.13679/j.jdyj.20180035

• 研究论文 • 上一篇    下一篇

基于AMSR-E遥感数据的北极冰间湖面积变化分析

谢小磊1,2,3  魏永亮1,2,3  张瑜1,2,3   

  1. 1. 上海海洋大学海洋科学学院, 上海 201306;
    2. 上海河口海洋测绘工程技术研究中心, 上海 201306;
    3. 上海海洋大学国际海洋研究中心, 上海 201306
  • 收稿日期:2018-06-15 修回日期:2018-09-17 出版日期:2019-06-30 发布日期:2019-06-30
  • 通讯作者: 魏永亮
  • 基金资助:

    国家自然科学基金(41606196, 41706210, 41506211)、国家重点研发计划(2016YFC1400903)、上海市科委地方院校能力建设计划(15320502200)、上海海洋大学博士科研启动基金(A2-0203-00-100344)资助

Analysis of changes in the Arctic polynya based on AMSR-E remote-sensing data

Xie Xiaolei1,2,3, Wei Yongliang1,2,3, Zhang Yu1,2,3   

  • Received:2018-06-15 Revised:2018-09-17 Online:2019-06-30 Published:2019-06-30
  • Contact: Yong-Liang WEI
  • Supported by:

    ;National Key R&D Program of China

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摘要：

利用4种遥感数据: AMSR-E(Advanced Microwave Scanning Radiometer-Earth Observing System) 36 GHz与89 GHz亮温数据反演的海冰厚度以及相应波段的海冰密集度数据, 结合海冰密集度和厚度两种方法提取北极冰间湖面积, 分析东西伯利亚沿岸和阿拉斯加沿岸在2003—2011年期间1—4月冰间湖面积变化, 并比较不同数据和算法之间的差异。结果表明: (1)1—4月份冰间湖面积变化形态相似, 但数值不同, 从长期看, 基于AMSR-E 89 GHz亮温数据反演的海冰厚度数据计算的冰间湖面积呈上升趋势, 变化率为273.33 km2·mon−1, 而AMSR-E 89 GHz和36 GHz波段的海冰密集度及基于AMSR-E 36 GHz亮温数据反演的海冰厚度数据计算的结果呈下降趋势, 分别为−68.91km2·mon−1、−42.74 km2·mon−1和−41.91 km2·mon−1; (2)数据分辨率高能够更精细分辨冰间湖, 得到的面积大, 反之则小; (3)由于基于海冰密集度和基于海冰厚度两种方法对冰间湖的定义不同, 海冰厚度方法计算结果要大于海冰密集度结果; (4)冰间湖面积变化存在地域差别, 白令海峡以西海域冰间湖统计差异较为明显, 而以东海域则较弱。

关键词: 北极冰间湖, 遥感数据, 反演算法, 时间变化, 对比分析

Abstract:

Four types of remote-sensing data, namely: Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) 36 GHz and 89 GHz gridded brightness temperature data and the AMSR-E ice-concentration data retrieved from those bands, combined with two retrieval methods, were used to determine polynyas of the Arctic. Variations in polynyas along the east coast of Siberia and the west coast of Alaska were analyzed using data for January to April during the period 2003–2011. Comparisons were made using the different data and methods. The main results showed that: (1) patterns of variations in the polynyas were similar, but the values differed, as the polynyas derived from the AMSR-E 89 GHz brightness temperature data showed an increasing trend over the long-term, while the results for AMSR-E sea-ice concentration retrieved from the AMSR-E 89 GHz and 36 GHz and the AMSR-E 36 GHz brightness temperature data showed a decreasing trend; (2) high-resolution data could resolve polynyas more precisely, thus obtaining a larger area, and vice versa with low-resolution data; (3) the polynyas retrieved from the ice-thickness approach were larger than that from ice-concentration approach owing to their different delineations of a polynya; and (4) variations in polynya areas revealed differences at a regional level, with more significant differences for areas west of the Bering Strait and weaker difference for areas to the east.

Key words: Arctic polynya, remote sensing data, retrieval methods, temporal variation, comparative analysis