留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

多源卫星遥感海面风速误差分析和交叉标定

吕思睿 林文明 邹巨洪 王志雄

吕思睿,林文明,邹巨洪,等. 多源卫星遥感海面风速误差分析和交叉标定[J]. 海洋学报,2023,45(5):118–128 doi: 10.12284/hyxb2023066
引用本文: 吕思睿,林文明,邹巨洪,等. 多源卫星遥感海面风速误差分析和交叉标定[J]. 海洋学报,2023,45(5):118–128 doi: 10.12284/hyxb2023066
Lü Sirui,Lin Wenming,Zou Juhong, et al. Error quantification and cross calibration of sea surface wind speeds from multiple remote sensing satellites[J]. Haiyang Xuebao,2023, 45(5):118–128 doi: 10.12284/hyxb2023066
Citation: Lü Sirui,Lin Wenming,Zou Juhong, et al. Error quantification and cross calibration of sea surface wind speeds from multiple remote sensing satellites[J]. Haiyang Xuebao,2023, 45(5):118–128 doi: 10.12284/hyxb2023066

多源卫星遥感海面风速误差分析和交叉标定

doi: 10.12284/hyxb2023066
基金项目: 国家重点研发计划(2022YFC3104902)。
详细信息
    作者简介:

    吕思睿(1998-),女,云南省丽江市人,研究方向为海洋微波遥感。E-mal: lvfassbender@outlook.com

    通讯作者:

    林文明(1984-),男,福建省仙游县人,教授,研究方向为海洋微波遥感、先进数据处理方法、雷达定标技术以及海面风场遥感及应用。E-mail: wenminglin@nuist.edu.cn

  • 中图分类号: P715.6;P732.1

Error quantification and cross calibration of sea surface wind speeds from multiple remote sensing satellites

  • 摘要: 利用多源卫星散射计和辐射计构建高时间分辨率的海面风遥感数据集是当前海洋遥感研究的热点。本文针对2019年同时期在轨运行的卫星散射计和辐射计,利用浮标数据和欧洲中期天气预报中心(ECMWF)第五代大气再分析数据(ERA5),定量评估了不同传感器获取的海面风速数据的误差特性和标定系数,阐明不同卫星遥感海面风单位误差相对大小,为多源卫星海面风场融合、同化等定量应用提供技术支撑。与常用的中性参考风相比,微波散射计和辐射计反演的风速更适合用等效应力风解释,以便实现卫星遥感数据的优化应用。现有微波散射计和辐射计遥感的海面风速与浮标和ERA5等效应力风在总体上具有良好的一致性,但在高风速条件下(风速大于20 m/s)呈明显的偏差。本文提出的一种用于风速误差横向对比的指示因子,实现了散射计与辐射计风速相对误差估计,为多源数据同化应用中的误差设置提供重要的参考。结果表明:5种散射计风速固有误差介于0.40~0.73之间,5种微波辐射计的风速固有误差介于0.86~1.23。总体而言,在0~20 m/s风速范围内,散射计的风速精度优于辐射计。
  • 图  1  卫星遥感风速与ERA5 u10nu10s的差值平均随纬度的变化

    Fig.  1  Latitude dependence of the difference between satellite wind products and ERA5 wind speed

    图  2  散射计与ERA5 u10s风速对比

    Fig.  2  Scatterometers and ERA5 u10swind speed comparison

    图  3  散射计与浮标 u10s风速对比

    Fig.  3  Scatterometers and buoy u10s wind speed comparison

    图  4  辐射计与ERA5 u10s风速对比

    Fig.  4  Radiometers and ERA5 u10s wind speed comparison

    图  5  辐射计与浮标u10s风速对比

    Fig.  5  Radiometers and buoy u10s wind speed comparison

    表  1  星载散射计发射现状及主要技术参数

    Tab.  1  Present situation and main technical parameters of scatterometers emission

    卫星传感器在轨时间频段刈幅/km标称风速范围/(m·s−1风产品类型
    MetOP-AASCAT-A2006年10月至2021年10月C1 0000~2510 m等效应力风[18]
    MetOP-BASCAT-B2012年9月至今C1 000 0~25 10 m等效应力风[18]
    SCATSAT-1OSCAT-22016年9月至2021年6月Ku1 8003~3010 m等效应力风[19]
    HY-2BHSCAT-B2018年10月至今Ku1 7002~2410 m等效应力风[20]
    CFOSATCSCAT2018年10月至今Ku1 0004~2410 m等效应力风[21]
    下载: 导出CSV

    表  2  星载辐射计发射现状及主要技术参数

    Tab.  2  Present situation and main technical parameters of radiometer emission

    卫星传感器在轨时间空间分辨率/km频率/GHz风产品类型
    CoriolisWindSAT2003年1月8~716.8、10.7、18.7、23.8、37.010 m风速
    GCOM-W1AMSR-22012年5月6~756.925、10.65、18.7、23.8、36.5、8910 m风速
    SSMIS-F16SSMIS2003年10月约5019.35、22.4、37、91.6610 m风速
    SSMIS-F17SSMIS2006年12月约5019.35、22.4、37、91.66
    SSMIS-F18SSMIS2009年10月约5019.35、22.4、37、91.66
    下载: 导出CSV

    表  3  卫星传感器风速的偏差趋势和校准系数

    Tab.  3  Deviation trend and calibration coefficient of satellite sensor wind speed

    传感器类型序号系统偏差趋势偏差校准系数
    散射计1CFOSCAT0.97−0.37
    2HY-2B0.99−0.08
    3ASCAT-A0.95−0.35
    4ASCAT-B0.97−0.20
    5OSCAT-20.97−0.34
    辐射计1SSMIS-160.96−0.64
    2SSMIS-170.94−0.20
    3SSMIS-180.96−0.44
    4AMSR-20.94−0.64
    5WindSAT0.95−0.19
    下载: 导出CSV

    表  4  不同风数据的平均随机误差标准差

    Tab.  4  The average random error standard deviation of different sources

    传感器类型平均随机误差标准差/(m·s−1)
    浮标0.98
    散射计 0.47
    辐射计 0.78
    ERA5 0.76
    下载: 导出CSV

    表  5  卫星遥感海面风速固有误差

    Tab.  5  Satellite remote sensing sea surface wind speed inherent errors

    传感器类型序号系统固有误差
    散射计1HSCAT0.732
    2CSCAT0.712
    3ASCAT-A0.464
    4ASCAT-B0.403
    5OSCAT-20.731
    辐射计1SSMIS-161.225
    2SSMIS-171.216
    3SSMIS-181.107
    4AMSR-20.859
    5WindSAT0.856
    下载: 导出CSV
  • [1] Wang He, Zhu Jianhua, Lin Mingsen, et al. Evaluating Chinese HY-2B HSCAT ocean wind products using buoys and other scatterometers[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(6): 923−927. doi: 10.1109/LGRS.2019.2940384
    [2] Portabella M, Stoffelen A. On scatterometer ocean stress[J]. Journal of Atmospheric and Oceanic Technology, 2009, 26(2): 368−382. doi: 10.1175/2008JTECHO578.1
    [3] Polverari F, Portabella M, Lin Wenming, et al. On high and extreme wind calibration using ASCAT[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 4202210.
    [4] Wright E E, Bourassa M A, Stoffelen A, et al. Characterizing buoy wind speed error in high winds and varying sea state with ASCAT and ERA5[J]. Remote Sensing, 2021, 13(22): 4558. doi: 10.3390/rs13224558
    [5] Zhao Ke, Zhao Chaofang. Evaluation of HY-2A scatterometer ocean surface wind data during 2012−2018[J]. Remote Sensing, 2019, 11(24): 2968. doi: 10.3390/rs11242968
    [6] Li Xiuzhong, Lin Wenming, Liu Baochang, et al. Sea surface wind retrieval using the combined scatterometer and altimeter backscatter measurements of the HY-2B satellite[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5101312.
    [7] Zhao Ke, Zhao Chaofang, Chen Ge. Evaluation of Chinese scatterometer ocean surface wind data: preliminary analysis[J]. Earth and Space Science, 2021, 8(7): e2020EA001482.
    [8] Wang Zhixiong, Zou Juhong, Stoffelen A, et al. Scatterometer sea surface wind product validation for HY-2C[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 6156−6164. doi: 10.1109/JSTARS.2021.3087742
    [9] Kloe J D, Stoffelen A, Verhoef A. Improved use of scatterometer measurements by using stress-equivalent reference winds[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(5): 2340−2347. doi: 10.1109/JSTARS.2017.2685242
    [10] Chen Ge. An intercomparison of TOPEX, NSCAT, and ECMWF wind speeds: illustrating and understanding systematic discrepancies[J]. Monthly Weather Review, 2004, 132(3): 780−792. doi: 10.1175/1520-0493(2004)132<0780:AIOTNA>2.0.CO;2
    [11] Vogelzang J, Stoffelen A, Verhoef A, et al. On the quality of high-resolution scatterometer winds[J]. Journal of Geophysical Research: Oceans, 2011, 116(C10): C10033. doi: 10.1029/2010JC006640
    [12] Mccoll K A, Vogelzang J, Konings A G, et al. Extended triple collocation: estimating errors and correlation coefficients with respect to an unknown target[J]. Geophysical Research Letters, 2014, 41(17): 6229−6236. doi: 10.1002/2014GL061322
    [13] Zwieback S, Scipal K, Dorigo W, et al. Structural and statistical properties of the collocation technique for error characterization[J]. Nonlinear Processes in Geophysics, 2012, 19(1): 69−80. doi: 10.5194/npg-19-69-2012
    [14] Ribal A, Young I R. Global calibration and error estimation of altimeter, scatterometer, and radiometer wind speed using triple collocation[J]. Remote Sensing, 2020, 12(12): 1997. doi: 10.3390/rs12121997
    [15] Vogelzang J, Stoffelen A, Lindsley R D, et al. The ASCAT 6.25-km wind product[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(5): 2321−2331. doi: 10.1109/JSTARS.2016.2623862
    [16] Wentz F J, Ricciardulli L, Rodriguez E, et al. Evaluating and extending the ocean wind climate data record[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(5): 2165−2185. doi: 10.1109/JSTARS.2016.2643641
    [17] Xiang Kunsheng, Yin Xiaobin, Xing Shuguo, et al. Preliminary estimate of CFOSAT satellite products in tropical cyclones[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 4203516.
    [18] OSI SAF/EARS Winds Team. ASCAT wind product user manual: version 1.17[S]. Darmstadt: EUMETSAT, 2021.
    [19] OSI SAF Winds Team. ScatSat-1 wind product user manual: version 1.3[S]. Darmstadt: EUMETSAT, 2018.
    [20] OSI SAF Winds Team. Product User Manual (PUM) for the HY-2 winds: version 1.0[S]. Darmstadt: EUMETSAT, 2021.
    [21] Zhao Xiaokang, Lin Wenming, Portabella M, et al. Effects of rain on CFOSAT scatterometer measurements[J]. Remote Sensing of Environment, 2022, 274: 113015.
    [22] Liu W T, Katsaros K B, Businger J A. Bulk parameterization of air-sea exchanges of heat and water vapor including the molecular constraints at the interface[J]. Journal of the Atmospheric Sciences, 1979, 36(9): 1722−1735. doi: 10.1175/1520-0469(1979)036<1722:BPOASE>2.0.CO;2
    [23] Liu Guoqiang, He Yijun, Zhang Yuanzhi, et al. Estimation of global wind energy input to the surface waves based on the scatterometer[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 9(6): 1017−1020. doi: 10.1109/LGRS.2012.2189194
  • 加载中
图(5) / 表(5)
计量
  • 文章访问数:  359
  • HTML全文浏览量:  140
  • PDF下载量:  67
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-07-29
  • 修回日期:  2022-12-07
  • 网络出版日期:  2022-12-20
  • 刊出日期:  2023-05-01

目录

    /

    返回文章
    返回