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中法海洋卫星微波散射计风场反演残差特性研究

王冰花 董晓龙 林文明 郎姝燕 朱迪 云日升

王冰花,董晓龙,林文明,等. 中法海洋卫星微波散射计风场反演残差特性研究[J]. 海洋学报,2021,43(11):157–165 doi: 10.12284/hyxb2021164
引用本文: 王冰花,董晓龙,林文明,等. 中法海洋卫星微波散射计风场反演残差特性研究[J]. 海洋学报,2021,43(11):157–165 doi: 10.12284/hyxb2021164
Wang Binghua,Dong Xiaolong,Lin Wenming, et al. On the wind inversion characteristics of China-France Oceanography Satellite microwave scatterometer[J]. Haiyang Xuebao,2021, 43(11):157–165 doi: 10.12284/hyxb2021164
Citation: Wang Binghua,Dong Xiaolong,Lin Wenming, et al. On the wind inversion characteristics of China-France Oceanography Satellite microwave scatterometer[J]. Haiyang Xuebao,2021, 43(11):157–165 doi: 10.12284/hyxb2021164

中法海洋卫星微波散射计风场反演残差特性研究

doi: 10.12284/hyxb2021164
基金项目: “十二五”海洋观测卫星地面系统CFOSAT散射计预处理课题(Y7C01KAJ10)
详细信息
    作者简介:

    王冰花(1996-),女,河南省商丘市人,主要从事CFOSAT风场反演研究。E-mail:wangbinghua18@mails.ucas.ac.cn

    通讯作者:

    董晓龙,研究员,主要从事微波(包括毫米波、亚毫米波)遥感成像与探测的理论与方法及先进微波遥感器系统研究。E-mail:dongxiaolong@mirslab.cn

  • 中图分类号: P425;P732

On the wind inversion characteristics of China-France Oceanography Satellite microwave scatterometer

  • 摘要: 2018年10月发射的中法海洋卫星散射计(CSCAT)是国际上首个扇形波束旋转扫描微波散射计。本文以最大似然估计风场反演算法为基线,详细分析了中法海洋卫星微波散射计海面风场反演代价函数的残差特性,重点研究了新的观测几何对风场反演残差以及风场质量的影响,并建立了风场模糊解的似然概率模型函数。结果表明,CSCAT风场反演的残差特性随风矢量单元在刈幅交轨方向位置的变化而变化,模糊解似然概率模型函数的指数分布在−0.4~−1.8之间。分析结果为CSCAT风场质量控制和二维变分分析去模糊算法的精细化调整提供了重要的参考。
  • 图  1  CSCAT风场反演流程图

    Fig.  1  Wind retrieval flow chart of CSCAT

    图  2  CSCAT观测几何示意图

    Fig.  2  Schematic diagram of observation geometry of CSCAT

    图  3  CSCAT地面风单元划分

    Fig.  3  CSCAT ground wind vector cell meshing

    图  4  MLE风场反演曲线

    Fig.  4  Curve of MLE wind inversion

    图  5  平均MLE随风速和WVC列数的变化(a)及MLE标准差随风速和WVC列数的变化(b)

    Fig.  5  Mean MLE versus wind speed and WVC number (a) and MLE standard deriation versus wind speed and WVC number (b)

    图  6  CSCAT风速、风向相对于ECMWF风速、风向的偏差随平均MLE变化的曲线

    a. 风速偏差;b. 风向偏差;不同线型的曲线表示不同的WVC列数

    Fig.  6  The variation curve of CSCAT wind speed and direction bias relative to ECMWF wind speed and direction with mean MLE

    a. Biases of wind speed; b. biases of wind direction; lines in different styles are for different WVC number

    图  7  CSCAT风速、风向相对于ECMWF风速、风向的标准差随平均MLE变化的曲线

    a. 风速标准差;b. 风向标准差;不同线型的曲线表示不同的WVC列数

    Fig.  7  The variation curve of CSCAT wind speed and direction standard deviation relative to ECMWF wind speed and direction with mean MLE

    a. Standard deviation of wind speed differences; b. standard deviation of wind direction differences; lines in different styles are for different WVC number

    图  8  不同节点下($ {Rn}_{2}-{Rn}_{1} $)值与$ p\left({Rn}_{2}\right)/p\left({Rn}_{1}\right) $ 函数关系的指数拟合($ {Rn}_{1} $=0.1)

    Fig.  8  The exponential fit to ratio $ {Rn}_{2} $ and $ {Rn}_{1} $ as a founction of ($ {Rn}_{2}-{Rn}_{1} $) value for different WVC number($ {Rn}_{1} $=0.1)

    图  9  不同$Rn_1 $取值下$ p\left({Rn}_{2}\right)/p\left({Rn}_{1}\right) $与($ {Rn}_{2}-{Rn}_{1} $)值函数关系的指数拟合(第8列WVC)

    Fig.  9  The exponential fit to ratio of $ {Rn}_{2} $ and $ {Rn}_{1} $ as a founction of ($ {Rn}_{2}-{Rn}_{1} $) value for different $ {Rn}_{1} $ (WVC number 8)

    图  10  $ {Rn}_{1} $分布直方图(节点数为8)

    Fig.  10  The distribution histogram of $ {Rn}_{1} $ (the number of node is 8)

    图  11  概率模型函数的指数及系数随节点的变化

    Fig.  11  The exponents and coefficients of the probabilistic model versus node number

    图  12  改进前概率模型函数反演的CSCAT风场与浮标测量风场

    Fig.  12  CSCAT wind filed and buoy wind filed retrieved by the likelihood probability model before improvement

    图  13  改进的概率模型函数反演的CSCAT风场与浮标测量风场

    Fig.  13  CSCAT wind filed and buoy wind filed retrieved by the improved likelihood probability model

    表  1  预测概率/观测概率的分布对比(刈幅远端)

    Tab.  1  Distribution comparision of predicted probability/observed probability (far swath)

    2个模糊解/%3个模糊解/%4个模糊解/%所有模糊解/%
    风单元个数267 607117 849458 349472 138
    第1模糊解84/8182/7983/8083/80
    第2模糊解16/1913/1610/1314/17
    第3模糊解5/54/43/3
    第4模糊解3/30/0
      注:−代表未获得概率。
    下载: 导出CSV

    表  2  预测概率/观测概率的分布对比(刈幅中间)

    Tab.  2  Distribution comparision of predicted probability/observed probability (sweet swath)

    2个模糊解/%3个模糊解/%4个模糊解/%所有模糊解/%
    风单元个数514 639345 693273 9841 134 316
    第1模糊解90/8878/8280/8384/85
    第2模糊解10/1216/1414/1313/13
    第3模糊解6/44/33/2
    第4模糊解2/10/0
      注:−代表未获得概率。
    下载: 导出CSV

    表  3  预测概率/观测概率的分布对比 (星下点区域)

    Tab.  3  Distribution comparision of predicted probability/observed probability (nadir swath)

    2个模糊解/%3个模糊解/%4个模糊解/%所有模糊解/%
    风单元个数162 112144 37340 206346 691
    第1模糊解78/7856/6648/5665/71
    第2模糊解22/2228/2223/2125/22
    第3模糊解16/1217/139/6
    第4模糊解12/101/1
      注:−代表未获得概率。
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-12-09
  • 修回日期:  2021-04-28
  • 网络出版日期:  2021-08-16
  • 刊出日期:  2021-12-31

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