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    基于卫星遥感数据南海南部海洋表面流场反演

    郑贵洲 潘子轩 孟亦菲 王红平

    郑贵洲, 潘子轩, 孟亦菲, 王红平, 2021. 基于卫星遥感数据南海南部海洋表面流场反演. 地球科学, 46(1): 341-349. doi: 10.3799/dqkx.2020.250
    引用本文: 郑贵洲, 潘子轩, 孟亦菲, 王红平, 2021. 基于卫星遥感数据南海南部海洋表面流场反演. 地球科学, 46(1): 341-349. doi: 10.3799/dqkx.2020.250
    Zheng Guizhou, Pan Zixuan, Meng Yifei, Wang Hongping, 2021. Inversion of Sea Surface Flow Field in Southern South China Sea Based on Satellite Remote Sensing Data. Earth Science, 46(1): 341-349. doi: 10.3799/dqkx.2020.250
    Citation: Zheng Guizhou, Pan Zixuan, Meng Yifei, Wang Hongping, 2021. Inversion of Sea Surface Flow Field in Southern South China Sea Based on Satellite Remote Sensing Data. Earth Science, 46(1): 341-349. doi: 10.3799/dqkx.2020.250

    基于卫星遥感数据南海南部海洋表面流场反演

    doi: 10.3799/dqkx.2020.250
    基金项目: 

    海洋地质保障工程(729)子课题 GZH201200508

    天然气水合物资源勘查与试采工程(127工程) GZH201100307

    详细信息
      作者简介:

      郑贵洲(1963-), 男, 教授, 主要从事资源与环境遥感、三维地理信息系统及深度学习与大数据研究.ORCID:0000-0002-2890-6395.E-mail:zhenggz@cug.edu.cn

    • 中图分类号: P237

    Inversion of Sea Surface Flow Field in Southern South China Sea Based on Satellite Remote Sensing Data

    • 摘要: 海表流场可直接影响海表的气候变化,且对于研究海气相互作用、热通量输送等具有重要意义.通过利用Jason-2号与HY-2号卫星高度计数据以及Metop卫星的ASCAT与HY-2号卫星散射计数据反演海表流场.利用距离加权平均法生成分辨率为0.25°×0.25°的网格,通过数据融合分别得到海表高度场与海面风场,在此基础上构建地转流和Ekman流反演数学模型.利用Jason-2与HY-2号卫星高程计数据反演地转流,利用ASCAT与HY-2号卫星散射计数据得出风应力驱动的Ekman流,合并两者得到海表流场.通过对研究海域海表流速的反演结果与OSCAR海流产品的对比分析,发现越靠近赤道的位置,其流速误差较大,最大相对误差达到了0.6 m/s.实验结果表明利用卫星遥感数据反演海洋表层流场能较为准确地表现实际海表流场的基本特征.

       

    • 图  1  研究海域地理位置

      地图取自自然资源部网站《中国地图 1:4 200万32开》,审图号:GS(2016)1545号

      Fig.  1.  Geographical location of the study area

      图  2  HY⁃2+Jason⁃2融合高度场

      Fig.  2.  HY⁃2+Jason⁃2 fusion elevation field

      图  3  HY⁃2+ASCAT融合风场

      Fig.  3.  HY⁃2+ASCAT fusion wind field

      图  4  地转流u分量

      Fig.  4.  u component of geostrophic flow

      图  5  地转流v分量

      Fig.  5.  v component of geostrophic flow

      图  6  Ekman流u分量

      Fig.  6.  u component of Ekman flow

      图  7  Ekman流v分量

      Fig.  7.  v component of Ekman flow

      图  8  经验模型算法海流图

      Fig.  8.  Empirical model algorithm sea flow chart

      图  9  海流u分量

      Fig.  9.  u component of sea flow

      图  10  海流v分量

      Fig.  10.  v component of sea flow

      图  11  u分量纬度平均分布

      Fig.  11.  Latitudinal average distribution of u component

      图  12  v分量纬度平均分布

      Fig.  12.  Latitudinal average distribution of v component

      图  13  经验模型与OSCAR海流u相对误差

      Fig.  13.  u relative error of sea flow between empirical model and OSCAR

      图  14  经验模型与OSCAR海流v相对误差

      Fig.  14.  v relative error of sea flow between empirical model and OSCAR

      表  1  高程计数据融合

      Table  1.   Altimeter data fusion

      Jason⁃2 Value1 Value1 Nan Nan
      HY⁃2 Value2 Nan Value2 Nan
      融合处理 加权平均 Value1 Value2 Nan
      下载: 导出CSV

      表  2  散射计数据融合

      Table  2.   Scatterometer data fusion

      ASCAT Value1 Value1 Nan Nan
      HY⁃2 Value2 Nan Value2 Nan
      融合处理 加权平均 Value1 Value2 Nan
      下载: 导出CSV
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    • 收稿日期:  2020-08-21
    • 刊出日期:  2021-01-15

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