Analysis for random error and correlation of HY-2B satellite andmodel wind speed data

Lan Youguo; Lin Mingsen; Zhang Youguang; Yang Dian

doi:10.12284/hyxb2023131

Volume 45 Issue 10

Oct. 2023

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Article Navigation > Haiyang Xuebao > 2023 > 45(10): 183-194

Lan Youguo，Lin Mingsen，Zhang Youguang, et al. Analysis for random error and correlation of HY-2B satellite andmodel wind speed data[J]. Haiyang Xuebao，2023, 45(10)：183–194 doi: 10.12284/hyxb2023131

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Analysis for random error and correlation of HY-2B satellite andmodel wind speed data

doi: 10.12284/hyxb2023131

Lan Youguo^{1, 2
,},
Lin Mingsen^{2
,
,},
Zhang Youguang²,
Yang Dian²

1.
College of Information Science Engineering, Ocean University of China, Qingdao 266100, China
2.
National Satellite Ocean Application Service, Beijing 100081, China

Received Date: 2023-05-06
Rev Recd Date: 2023-06-19

Available Online: 2023-11-16

Publish Date: 2023-10-30

Abstract

Abstract

Random errors between systems are not correlated is a necessary assumption for Triple Collocation (TC) analysis, but this assumption does not always hold in practice. The least squares-based Extended Collocation (EC) method can estimate random error in the presence of error correlation, but it cannot accurately estimate standard deviation (SD) of the random error as error correlation is weak. This paper proposes an error estimation method for the fourth system using three error-independent systems, which can estimate the SD of the system error more accurately in case of weak correlation by considering both error correlation and representative error. The SD of the errors of the scatterometer, radiometer and altimeter are 0.600 m/s, 0.742 m/s and 0.533 m/s respectively, as assumed that random errors of three HY-2B wind speed products are independent. The SD of error of ERA5 reanalysis wind speed is also estimated to be 0.810 m/s, the correlation coefficient of the errors of wind speed between HY-2B scatterometer and the ERA5 is 0.231, the correlation coefficient of the errors of wind speed between HY-2B radiometer and the ERA5 is 0.105. This paper proposes a method to estimate random errors and their correlation with the fourth dataset using three known error independent datasets, which achieves a more precise estimation for the SD of the random error in the case of weak correlation, and it helps to use these data better in assimilation and fusion.
- HY-2B satellite,
- ocean surface wind speed,
- extended triple collocation,
- random error,
- error correlation

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References(21)

References

[1]	Martin S. 海洋遥感导论(修改版)[M]. 蒋兴伟, 译. 北京: 海洋出版社, 2017. Martin S. An Introduction to Ocean Remote Sensing[M]. Jiang Xingwei, trans. Beijing: China Ocean Press, 2017.
[2]	Stoffelen A. Toward the true near-surface wind speed: error modeling and calibration using triple collocation[J]. Journal of Geophysical Research: Oceans, 1998, 103(C4): 7755−7766. doi: 10.1029/97JC03180
[3]	Scipal K, Holmes T, De Jeu R, et al. A possible solution for the problem of estimating the error structure of global soil moisture data sets[J]. Geophysical Research Letters, 2008, 35(24): L24403. doi: 10.1029/2008GL035599
[4]	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
[5]	Vogelzang J, King G P, Stoffelen A. Spatial variances of wind fields and their relation to second-order structure functions and spectra[J]. Journal of Geophysical Research: Oceans, 2015, 120(2): 1048−1064. doi: 10.1002/2014JC010239
[6]	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
[7]	Pierdicca N, Fascetti F, Pulvirenti L, et al. Quadruple collocation analysis for soil moisture product assessment[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(8): 1595−1599. doi: 10.1109/LGRS.2015.2414654
[8]	Pan Ming, Fisher C K, Chaney N W, et al. Triple collocation: beyond three estimates and separation of structural/non-structural errors[J]. Remote Sensing of Environment, 2015, 171: 299−310. doi: 10.1016/j.rse.2015.10.028
[9]	Gruber A, Su C H, Crow W T, et al. Estimating error cross-correlations in soil moisture data sets using extended collocation analysis[J]. Journal of Geophysical Research: Atmospheres, 2016, 121(3): 1208−1219. doi: 10.1002/2015JD024027
[10]	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
[11]	Konings A G, Mccoll K A, Alemohammad S H, et al. Error characterization of similar products: Triple collocation with correlated errors[C]//AGU Fall Meeting Abstracts. Washington: AGU, 2014.
[12]	Lin Wenming, Portabella M, Stoffelen A, et al. ASCAT wind quality under high subcell wind variability conditions[J]. Journal of Geophysical Research: Oceans, 2015, 120(8): 5804−5819. doi: 10.1002/2015JC010861
[13]	Abdalla S, De Chiara G. Estimating random errors of scatterometer, altimeter, and model wind speed data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(5): 2406−2414. doi: 10.1109/JSTARS.2017.2659220
[14]	Vogelzang J, Stoffelen A. Quadruple collocation analysis of in-situ, scatterometer, and NWP winds[R/OL]. (2023−01−18) [2023−02−02]. Oceanography, 2021. https://essopenarchive.org/doi/full/10.1002/essoar.10505872.1.
[15]	Vogelzang J, Stoffelen A. On the accuracy and consistency of quintuple collocation analysis of in situ, scatterometer, and NWP Winds[J]. Remote Sensing, 2022, 14(18): 4552. doi: 10.3390/rs14184552
[16]	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/hyxb2022-0000-00 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/hyxb2022-0000-00
[17]	林明森, 何贤强, 贾永君, 等. 中国海洋卫星遥感技术进展[J]. 海洋学报, 2019, 41(10): 99−112, doi: 10.3969/j.issn.0253-4193.2019.10.006 Lin Mingsen, He Xianqiang, Jia Yongjun, et al. Advances in marine satellite remote sensing technology in China[J]. Haiyang Xuebao, 2019, 41(10): 99−112. doi: 10.3969/j.issn.0253-4193.2019.10.006
[18]	Gourrion J, Vandemark D, Bailey S, et al. A two-parameter wind speed algorithm for Ku-band altimeters[J]. Journal of Atmospheric and Oceanic Technology, 2002, 19(12): 2030−2048. doi: 10.1175/1520-0426(2002)019<2030:ATPWSA>2.0.CO;2
[19]	Molina M O, Gutiérrez C, Sánchez E. Comparison of ERA5 surface wind speed climatologies over Europe with observations from the HadISD dataset[J]. International Journal of Climatology, 2021, 41(10): 4864−4878. doi: 10.1002/joc.7103
[20]	Efron B, Tibshirani R J. An Introduction to the Bootstrap[M]. New York: Chapman and Hall/CRC, 1994.
[21]	Caires S, Sterl A. Validation of ocean wind and wave data using triple collocation[J]. Journal of Geophysical Research: Oceans, 2003, 108(C3): 3098. doi: 10.1029/2002jc001491