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合成孔径雷达反演海面风场变分模型分析

姜祝辉 周晓中 游小宝 易欣 黄为权

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合成孔径雷达反演海面风场变分模型分析

姜祝辉, 周晓中, 游小宝, 易欣, 黄为权

Analysis on the variational model of synthetic aperture radar sea surface wind retrieval

Jiang Zhu-Hui, Zhou Xiao-Zhong, You Xiao-Bao, Yi Xin, Huang Wei-Quan
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  • 为考察合成孔径雷达反演海面风场变分模型精度,开展了误差分析试验.在背景场误差为极大值条件下分析场误差低于背景场误差,且随背景场风向增大呈周期性变化;在背景场误差逐渐变大条件下分析场误差逐渐增大,误差偏离方向与背景场误差偏离方向一致;在特定背景场条件下与直接反演模型相比,低风速时反演误差略高,中高风速时反演误差明显较低. 总体来讲,变分模型误差小于背景场误差,风速反演误差小于1.60 m/s,风向误差小于17.15°.
    Error analysis is carried out to test the variational model of synthetic aperture radar sea surface wind retrieval. On condition that the background error is maximum, the analysis error is lower than the background error, and with the increase of the background wind direction, the analysis error changes periodically; on condition that the background error gradually increase, the analysis error increases gradually and its deviation direction coincides with the background error deviation direction; under the condition of specific background field, the variational model is compared with the direct inversion model: when the background wind speed is low, the variational model error is slightly high, when the background wind speed is high, the variational model error is significantly low. Generally, the variational model wind speed error is less than 1.60 m/s, and the wind direction error is less than 17.15°, which are better than those of the direct inversion model.
    • 基金项目: 高分辨率对地观测系统重大专项青年创新基金(批准号:GFZX04060103-3-12)和国家重点基础研究发展计划(批准号:2010CB951901)资助的课题.
    • Funds: Project supported by the High Resolution Earth Observation System Major Special Project Youth Innovation Foundation of China (Grant No. GFZX04060103-3-12) and the State Key Development Program for Basic Research of China (Grant No. 2010CB951901).
    [1]

    Shimada T, Sawada M, Sha W, Kawamura H 2010 Mon. Wea. Rev. 138 3806

    [2]

    Sheng Z, Fang H 2013 Chin. Phys. B 22 029301

    [3]

    Sheng Z 2013 Chin. Phys. B 22 029302

    [4]

    Weissman D E, King D, Thompson T W 1979 J. Appl. Meteorol. 18 1023

    [5]

    Vachon P W, Dobson F W 1996 Global Atmos. Ocean Syst. 5 177

    [6]

    Koch W 2004 IEEE Trans. Geosci. Remote Sens. 42 702

    [7]

    Jiang Z H, Huang S X, Shi H Q, Zhang W, Wang B 2011 Acta Phys. Sin. 60 108402 (in Chinese) [姜祝辉, 黄思训, 石汉青, 张伟, 王彪 2011 物理学报 60 108402]

    [8]

    Zecchetto S, de Biasio F 2008 IEEE Trans. Geosci. Remote Sens. 46 2983

    [9]

    He Y J, Perrie W, Zou Q P, Vachon P W 2005 IEEE Trans. Geosci. Remote Sens. 43 1453

    [10]

    Portabella M, Stoffelen A, Johannessen J A 2002 J. Geophy. Res. 107 3086

    [11]

    Choisnard J, Laroche S 2008 J. Geophys. Res. 113 C05006

    [12]

    Jiang Z H, Huang S X, He R, Zhou C T 2011 Acta Phys. Sin. 60 068401 (in Chinese) [姜祝辉, 黄思训, 何然, 周晨腾 2011 物理学报 60 068401]

    [13]

    Hersbach H, Stoffelen A, de Haan S 2007 J. Geophys. Res. 112 C03006

    [14]

    Huang S X, Wu R S 2001 Methods of Mathematical Physics in Atmospheric Science (Beijing: China Meteorological Press) p422 (in Chinese) [黄思训, 伍荣生 2001 大气科学中的数学物理问题 (北京: 气象出版社) 第422页]

    [15]

    Li J, Huang S X 2001 Sci. China D 31 70 (in Chinese) [李俊, 黄思训 2001 中国科学 D辑 31 70]

  • [1]

    Shimada T, Sawada M, Sha W, Kawamura H 2010 Mon. Wea. Rev. 138 3806

    [2]

    Sheng Z, Fang H 2013 Chin. Phys. B 22 029301

    [3]

    Sheng Z 2013 Chin. Phys. B 22 029302

    [4]

    Weissman D E, King D, Thompson T W 1979 J. Appl. Meteorol. 18 1023

    [5]

    Vachon P W, Dobson F W 1996 Global Atmos. Ocean Syst. 5 177

    [6]

    Koch W 2004 IEEE Trans. Geosci. Remote Sens. 42 702

    [7]

    Jiang Z H, Huang S X, Shi H Q, Zhang W, Wang B 2011 Acta Phys. Sin. 60 108402 (in Chinese) [姜祝辉, 黄思训, 石汉青, 张伟, 王彪 2011 物理学报 60 108402]

    [8]

    Zecchetto S, de Biasio F 2008 IEEE Trans. Geosci. Remote Sens. 46 2983

    [9]

    He Y J, Perrie W, Zou Q P, Vachon P W 2005 IEEE Trans. Geosci. Remote Sens. 43 1453

    [10]

    Portabella M, Stoffelen A, Johannessen J A 2002 J. Geophy. Res. 107 3086

    [11]

    Choisnard J, Laroche S 2008 J. Geophys. Res. 113 C05006

    [12]

    Jiang Z H, Huang S X, He R, Zhou C T 2011 Acta Phys. Sin. 60 068401 (in Chinese) [姜祝辉, 黄思训, 何然, 周晨腾 2011 物理学报 60 068401]

    [13]

    Hersbach H, Stoffelen A, de Haan S 2007 J. Geophys. Res. 112 C03006

    [14]

    Huang S X, Wu R S 2001 Methods of Mathematical Physics in Atmospheric Science (Beijing: China Meteorological Press) p422 (in Chinese) [黄思训, 伍荣生 2001 大气科学中的数学物理问题 (北京: 气象出版社) 第422页]

    [15]

    Li J, Huang S X 2001 Sci. China D 31 70 (in Chinese) [李俊, 黄思训 2001 中国科学 D辑 31 70]

计量
  • 文章访问数:  1672
  • PDF下载量:  487
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-03-02
  • 修回日期:  2014-03-31
  • 刊出日期:  2014-07-05

合成孔径雷达反演海面风场变分模型分析

  • 1. 北京应用气象研究所, 北京 100029
    基金项目: 

    高分辨率对地观测系统重大专项青年创新基金(批准号:GFZX04060103-3-12)和国家重点基础研究发展计划(批准号:2010CB951901)资助的课题.

摘要: 为考察合成孔径雷达反演海面风场变分模型精度,开展了误差分析试验.在背景场误差为极大值条件下分析场误差低于背景场误差,且随背景场风向增大呈周期性变化;在背景场误差逐渐变大条件下分析场误差逐渐增大,误差偏离方向与背景场误差偏离方向一致;在特定背景场条件下与直接反演模型相比,低风速时反演误差略高,中高风速时反演误差明显较低. 总体来讲,变分模型误差小于背景场误差,风速反演误差小于1.60 m/s,风向误差小于17.15°.

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