Acta Optica Sinica, Volume. 42, Issue 18, 1828007(2022)

Models of Sea Surface Wind Speed Retrieval by Spaceborne Lidar Data

Xinyi Zhang1, Dong Wu1,2、*, Zhenwei Yang1, and Yan He3
Author Affiliations
  • 1Department of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, Shandong, China
  • 2Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, Shandong, China
  • 3Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
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    Figures & Tables(4)
    Comparison of CALIOP wind speed inversion values and AMSR-2 wind speed values at different times. (a)(b) October 2017; (c)(d) January 2018; (e)(f) April 2018; (g)(h) July 2018
    Errors between CALIOP wind speed inversion values and AMSR-2 wind speed values in different wind speed intervals. (a) Wind speed less than 3 m·s-1; (b) wind speed greater than 13 m·s-1
    • Table 1. Differences of nighttime sea surface wind speed retrieved by Gaussian model, GC approximation model in cloud-free condition and GC approximation model with transparent cloud layers

      View table

      Table 1. Differences of nighttime sea surface wind speed retrieved by Gaussian model, GC approximation model in cloud-free condition and GC approximation model with transparent cloud layers

      TimeBias /(m·s-1Standard deviation /(m·s-1Correlation coefficient
      GaussGC1GC2GaussGC1GC2GaussGC1GC2
      October 20170.030.100.301.091.291.220.930.920.92
      January 2018-0.210.010.251.171.381.330.910.900.91
      April 2018-0.070.120.231.091.251.200.930.920.92
      July 20180.050.070.251.241.681.390.910.870.90
    • Table 2. Differences of daytime sea surface wind speed retrieved by Gaussian model, GC approximation model in cloud-free condition and GC approximation model with transparent cloud layers

      View table

      Table 2. Differences of daytime sea surface wind speed retrieved by Gaussian model, GC approximation model in cloud-free condition and GC approximation model with transparent cloud layers

      TimeBias /(m·s-1Standard deviation /(m·s-1Correlation coefficient
      GaussGC1GC2GaussGC1GC2GaussGC1GC2
      October 2017-0.19-0.160.331.231.451.410.910.890.90
      January 2018-0.60-0.460.281.281.531.450.890.880.89
      April 2018-0.60-0.450.401.571.831.860.860.850.86
      July 2018-0.41-0.490.351.451.851.690.880.820.87
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    Xinyi Zhang, Dong Wu, Zhenwei Yang, Yan He. Models of Sea Surface Wind Speed Retrieval by Spaceborne Lidar Data[J]. Acta Optica Sinica, 2022, 42(18): 1828007

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jan. 27, 2022

    Accepted: Apr. 21, 2022

    Published Online: Sep. 15, 2022

    The Author Email: Wu Dong (dongwu@ouc.edu.cn)

    DOI:10.3788/AOS202242.1828007

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