Retrieval of ocean wave spectra from Sentinel-1 SAR data and comparison with the CFOSAT/SWIM data in the Arctic ocean
- Vol. 27, Issue 4, Pages: 881-890(2023)
Published: 07 April 2023
DOI: 10.11834/jrs.20211210
扫 描 看 全 文
浏览全部资源
扫码关注微信
Published: 07 April 2023 ,
扫 描 看 全 文
黄冰清,李晓明,蔡琼琼.2023.北极海域SAR海浪方向谱反演及其与中法海洋卫星CFOSAT/SWIM数据的比较.遥感学报,27(4): 881-890
Huang B Q,Li X M,Cai Q Q. 2023. Retrieval of ocean wave spectra from Sentinel-1 SAR data and comparison with the CFOSAT/SWIM data in the Arctic ocean. National Remote Sensing Bulletin, 27(4):881-890
北极海域的海浪与海冰相互作用是目前北极海冰变化研究的一个前沿问题。但观测数据的缺失,限制了对于该问题的深入研究。星载合成孔径雷达SAR(Synthetic Aperture Radar)具有独特的海面二维成像能力,是极地边缘区海浪—海冰相互作用研究重要的遥感手段。本文基于哨兵1号干涉宽幅模式IW(Interferometric Wide Swath)数据,利用SAR海浪非线性反演方法在格陵兰海及挪威海开展了海浪方向谱的反演实验,进而使用中法海洋卫星CFOSAT搭载的SWIM波谱仪的海浪谱数据和星下点有效波高数据对SAR反演结果进行了验证。结果表明,无论是海浪方向谱的结构、能量分布特征还是海浪方向谱的积分参数,SAR的反演结果都与SWIM的测量结果具有良好的一致性。其中,SAR海浪方向谱和SWIM斜率谱积分计算的有效波高的偏差和均方根误差为0.11 m和0.71 m,平均波周期的偏差和均方根误差分别为-0.52 s和0.62 s,谱峰传播方向与波长的偏差分别为-7.74 °和-0.56 m, 均方根误差分别为15.75°和52.73 m。SAR反演的有效波高与SWIM星下点测量的有效波高之间偏差为0.03 m,均方根误差为0.48 m,二者相关系数为0.95。本研究验证了利用SAR海浪非线性反演方法进行北极海域海浪方向谱及海浪参数反演的可行性,为后续的海浪向冰传播衰减过程研究奠定了数据基础和方法基础。
The interaction between ocean waves and sea ice in the Arctic ocean has received significant attention. However
the study on this issue is significantly limited due to the lack of observation data. Synthetic Aperture Radar (SAR) plays an important role in the research of ocean wave and sea-ice interaction because of its unique capability of imaging sea surface in two dimensions. Sentinel-1 (S1)
which consists of Sentinel-1A (S1A) and Sentine-1B (S1B)
can cover the entire Arctic Area within 2 days. The Interferometric Wide Swath (IW) mode
one of the main imaging modes of S1 in the Arctic
has been providing SAR images with a high resolution of 10 m. The ocean wave spectra are derived using the S1 IW data. The spectra are likely to provide vital observation for studying the interaction between sea-ice and waves as they present the distribution of wave energy and their variations in different frequencies and directions. Meanwhile
the retrieved ocean wave spectra are an excellent validation data source for SWIM
which is onboard the China-France Oceanography Satellite and provides measurements of ocean wave spectra in the global ocean.In this study
we use the sub-images from the S1 IW image with a size of 1024 pixels × 1024 pixels (10.24 km × 10.24 km) to retrieve ocean wave spectra by using a nonlinear retrieval method (i.e.
MPI scheme). The retrieved ocean wave spectra and wave parameters are compared with SWIM measurements acquired at an incidence angle of 10°
and the Significant Wave Height (SWH) is measured at nadir. The SWIM spectrum covers a large area by approximately 70 km × 90 km. To make a comparison
all the SAR sub-image spectra within a SWIM beam coverage are averaged to calculate a new observed SAR spectrum
which is inputted into the MPI inversion scheme. Then
the retrieved SAR ocean wave spectrum is compared with the SWIM spectrum. The footprint size of the SWIM nadir beam is 18 km
which is comparable to the S1 sub-image size. Accordingly
a SAR sub-image is extracted at SWIM nadir
and the corresponding ocean wave spectrum is retrieved. The SWH is calculated by integrating the retrieved wave spectra to compare with the SWIM nadir measurements of SWH. The experiment was carried out using the data acquired in September 2020 in the Greenland Sea and Norwegian Sea
where the ocean waves generated in the North Atlantic and propagating vast distances to the ice-covered area in the Arctic ocean can be frequently observed.
Fifty-four ocean wave spectra were retrieved from 25 IW data and are compared with the SWIM slope spectra. The comparison shows that the SAR-retrieved spectra are consistent with SWIM spectra in terms of structure and energy distribution. Good agreements are also found between the integral parameters of the SAR ocean wave spectra and SWIM slope spectra. The comparison yields a bias and an RMSE of 0.11 and 0.71 m for SWH and a bias and an RMSE of -0.52 s and 0.62 s for mean wave period. The comparison of the dominant wave parameters yield a bias of -7.74° and an RMSE of 15.75° for the dominant wave direction and a bias of -0.56 m and an RMSE of 52.73 m for the dominant wavelength. Furthermore
5075 data pairs of S1-retrieved SWH and SWIM nadir SWH were collocated and compared. The comparison result yields a bias of 0.03 m
an RMSE of 0.48 m
and a correlation of 0.95.
The comparison between the S1 retrieved results and the SWIM measurements suggests that ocean wave information can be effectively retrieved from S1 IW data by using the MPI method in the Arctic ocean. Although the MPI method relies on prior information
it is still an effective method for obtaining ocean wave spectra in high resolution. The spectra retrieved from S1 are likely to show the energy attenuation of ocean waves in different frequencies and directions when propagating toward an ice-covered area. This finding will be of great support for the further study on the interaction between sea ice and ocean waves.
遥感北极海浪SARCFOSAT
remote sensingArcticocean waveSARCFOSAT
Alpers W and Rufenach C L. 1979. The effect of orbital motions on synthetic aperture radar imagery of ocean waves. IEEE Transactions on Antennas and Propagation, 27(5): 685-690 [DOI: 10.1109/TAP.1979.1142163http://dx.doi.org/10.1109/TAP.1979.1142163]
Brooker G. 1995. UWA processing algorithm specification Version 2.0. [2021-04-16]. https://earth.esa.int/eogateway/documents/20142/37627/UWA%20Processing%20Algorithm%20Specification/aa6d1https://earth.esa.int/eogateway/documents/20142/37627/UWA%20Processing%20Algorithm%20Specification/aa6d1b71-a540-cc8c-06bf-897042938c8b
Earle M D, Steele K E and Wang D W C. 1999. Use of advanced directional wave spectra analysis methods. Ocean Engineering, 26(12): 1421-1434 [DOI: 10.1016/S0029-8018(99)00010-4http://dx.doi.org/10.1016/S0029-8018(99)00010-4]
Engen G and Johnsen H. 1995. SAR-ocean wave inversion using image cross spectra. IEEE Transactions on Geoscience and Remote Sensing, 33(4): 1047-1056 [DOI: 10.1109/36.406690http://dx.doi.org/10.1109/36.406690]
ESA. 2013. Sentinel-1 SAR User Guide. [2021-04-16]. https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sarhttps://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar
Hasselmann S, Brüning C, Hasselmann K and Heimbach P. 1996. An improved algorithm for the retrieval of ocean wave spectra from synthetic aperture radar image spectra. Journal of Geophysical Research: Oceans, 101(C7): 16615-16629 [DOI: 10.1029/96jc00798http://dx.doi.org/10.1029/96jc00798]
Hasselmann K and Hasselmann S. 1991. On the nonlinear mapping of an ocean wave spectrum into a synthetic aperture radar image spectrum and its inversion. Journal of Geophysical Research: Oceans, 96(C6): 10713-10729 [DOI: 10.1029/91JC00302http://dx.doi.org/10.1029/91JC00302]
Hasselmann K, Raney R K, Plant W J, Alpers W, Shuchman R A, Lyzenga D R, Rufenach C L and Tucker M J. 1985. Theory of synthetic aperture radar ocean imaging: A MARSEN view. Journal of Geophysical Research: Oceans, 90(C3): 4659-4686 [DOI: 10.1029/JC090iC03p04659http://dx.doi.org/10.1029/JC090iC03p04659]
Hauser D, Tourain C, Hermozo L, Alraddawi D, Tran N T, Aouf L, Chapron B, Dalphinet A, Delaye L, Dalila M, Dormy E, Gouillon F, Gressani V, Grouazel A, Guitton G, Husson R, Mironov A, Mouche A, Ollivier A, Oruba L, Piras F, Suquet R R, Schippers P and Tison C. 2021. New observations from the SWIM radar on-board CFOSAT: Instrument validation and ocean wave measurement assessment. IEEE Transactions on Geoscience and Remote Sensing, 59(1): 5-26 [DOI: 10.1109/TGRS.2020.2994372http://dx.doi.org/10.1109/TGRS.2020.2994372]
He Y J. 1999. A parametric method of retrieving ocean wave spectra from synthetic aperture radar images. Chinese Science Bulletin, 44(13): 1218-1224
何宜军. 1994. 合成孔径雷达提取海浪方向谱的参数化方法. 科学通报, 44(4): 428-433 [DOI: 10.3321/j.issn:0023-074X.1999.04.022http://dx.doi.org/10.3321/j.issn:0023-074X.1999.04.022]
Heimbach P, Hasselmann S, Brüning C and Hasselmann K. 1996. Application of wave spectral retrievals from ERS-1 wave mode data for improved wind and wave field analyses//Proceedings of the Second ERS Applications Workshop. Noordwijk: ESA: 303-308.
Huang B Q, Zeng K and He M X. 2017. On the effects of the region for obtaining first guess spectra on the directional ocean wave spectra retrieved by SAR with MPI algorithm. Periodical of Ocean University of China, 47(S1): 129-135
黄冰清, 曾侃, 贺明霞. 2017. 第一猜测谱运行范围对MPI方法SAR海浪方向谱反演结果的影响. 中国海洋大学学报, 47(S1): 129-135 [DOI: 10.16441/j.cnki.hdxb.20170229http://dx.doi.org/10.16441/j.cnki.hdxb.20170229]
Kohout A L, Williams M J M, Dean S M and Meylan M H. 2014. Storm-induced sea-ice breakup and the implications for ice extent. Nature, 509(7502): 604-607 [DOI: 10.1038/nature13262http://dx.doi.org/10.1038/nature13262]
Li X M and Huang B Q. 2020. A global sea state dataset from spaceborne synthetic aperture radar wave mode data. Scientific Data, 7(1): 261 [DOI: 10.1038/s41597-020-00601-3http://dx.doi.org/10.1038/s41597-020-00601-3]
Li X M, Lehner S and Bruns T. 2011. Ocean wave integral parameter measurements using Envisat ASAR wave mode data. IEEE Transactions on Geoscience and Remote Sensing, 49(1): 155-174 [DOI: 10.1109/TGRS.2010.2052364http://dx.doi.org/10.1109/TGRS.2010.2052364]
Li X M, Koenig T, Schulz-Stellenfleth J and Lehner S. 2010. Validation and intercomparison of ocean wave spectra inversion schemes using ASAR wave mode data. International Journal of Remote Sensing, 31(17-18): 4969-4993 [DOI: 10.1080/01431161.2010.485222http://dx.doi.org/10.1080/01431161.2010.485222]
Liu Q X, Babanin A V, Zieger S, Young I R and Guan C L. 2016. Wind and wave climate in the Arctic Ocean as observed by altimeters. Journal of Climate, 29(22): 7957-7975 [DOI: 10.1175/JCLI-D-16-0219.1http://dx.doi.org/10.1175/JCLI-D-16-0219.1].
Liu X Y, Yang Q, Zong Y F, Zhang X N, Zeng K and Wu C X. 2017. Research on the wave characteristics of China’s seas based on SAR directional ocean wave spectra. Journal of Ocean Technology, 36(5): 81-87
刘晓燕, 杨倩, 宗芳伊, 张晓楠, 曾侃, 吴承璇. 2017. 基于SAR海浪方向谱的中国海海浪特性研究. 海洋技术学报, 36(5): 81-87 [DOI: 10.3969/j.issn.1003-2029.2017.05.013http://dx.doi.org/10.3969/j.issn.1003-2029.2017.05.013]
Mastenbroek C and De Valk C F. 2000. A semiparametric algorithm to retrieve ocean wave spectra from synthetic aperture radar. Journal of Geophysical Research: Oceans, 105(C2): 3497-3516 [DOI: 10.1029/1999JC900282http://dx.doi.org/10.1029/1999JC900282]
Schulz-Stellenfleth J and Lehner S. 2004. Measurement of 2-D sea surface elevation fields using complex Synthetic Aperture radar data. IEEE Transactions on Geoscience and Remote Sensing, 42(6): 1149-1160 [DOI: 10.1109/tgrs.2004.826811http://dx.doi.org/10.1109/tgrs.2004.826811]
Schulz-Stellenfleth J, König T and Lehner S. 2007. An empirical approach for the retrieval of integral ocean wave parameters from synthetic aperture radar data. Journal of Geophysical Research: Oceans, 112(C3): C03019 [DOI: 10.1109/IGARSS.2006.484http://dx.doi.org/10.1109/IGARSS.2006.484]
Serreze M C and Francis J A. 2006. The arctic amplification debate. Climatic Change, 76(3): 241-264 [DOI: 10.1007/s10584-005-9017-yhttp://dx.doi.org/10.1007/s10584-005-9017-y]
Shao W Z, Ding Y Y, Li J C, Gou S P, Nunziata F, Yuan X Z and Zhao L B. 2019. Wave retrieval under typhoon conditions using a machine learning method applied to Gaofen-3 SAR imagery. Canadian Journal of Remote Sensing, 45(6): 723-732 [DOI: 10.1080/07038992.2019.1683444http://dx.doi.org/10.1080/07038992.2019.1683444]
Stopa J E and Mouche A. 2017. Significant wave heights from Sentinel‐1 SAR: Validation and applications. Journal of Geophysical Research: Oceans, 122(3): 1827-1848 [DOI: 10.1002/2016JC012364http://dx.doi.org/10.1002/2016JC012364]
Sun J. 2005. The Retrieval of Ocean Wave Information from SAR Images. Qingdao: Ocean University of China
孙健. 2005. SAR影像的海浪信息反演. 青岛: 中国海洋大学
Thomson J and Rogers W E. 2014. Swell and sea in the emerging Arctic Ocean. Geophysical Research Letters, 41(9): 3136-3140 [DOI: 10.1002/2014GL059983http://dx.doi.org/10.1002/2014GL059983]
Tison C and Hauser D. 2018. SWIM products users guide. [2021-04-16]. https://www.aviso.altimetry.fr/fileadmin/documents/data/tools/SWIM_simplified_handbook.pdfhttps://www.aviso.altimetry.fr/fileadmin/documents/data/tools/SWIM_simplified_handbook.pdf
Tolman H L. 1997. User manual and system documentation of WAVEWATCH-III version 1.15. [2021-04-16]. https://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtmlhttps://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml
Tolman H L. 1999. User manual and system documentation of WAVEWATCH-III version 1.18. [2021-04-16]. https://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtmlhttps://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml
Tolman H L. 2009. User manual and system documentation of WAVEWATCH III version 3.14. [2021-04-16]. https://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtmlhttps://polar.ncep.noaa.gov/waves/wavewatch/wavewatch.shtml
Wang H, Yang J S, Huang W G and Wang J. 2008. Analysis on intrinsic error of ENVISAT ASAR level 2 algorithm. Acta Oceanologica Sinica, 30(3): 72-76
王贺, 杨劲松, 黄韦艮, 王隽. 2008. 对ENVISAT ASAR level 2算法固有误差的分析. 海洋学报 30(3): 72-76 [DOI: 10.3321/j.issn:0253-4193.2008.03.009http://dx.doi.org/10.3321/j.issn:0253-4193.2008.03.009]
Wang L B and Feng Q. 2004. Directional ocean wave spectrum from SAR image using Hasselmann’s method. Chinese Journal of Radio Science, 19(1): 67-71
王来部, 冯倩. 2004. Hasselmann方法从SAR图像反演海浪方向谱及其印证研究. 电波科学学报, 19(1): 67-71 [DOI: 10.3969/j.issn.1005-0388.2004.01.015http://dx.doi.org/10.3969/j.issn.1005-0388.2004.01.015]
Wu K, Li X M and Huang B Q. 2021. Retrieval of ocean wave heights from spaceborne SAR in the arctic ocean with a neural network. Journal of Geophysical Research: Oceans, 126(3): e2020JC016946 [DOI: 10.1029/2020JC016946http://dx.doi.org/10.1029/2020JC016946]
Zhao J P, Shi J X, Wang Z M, Li Z J and Huang F. 2015. Arctic amplification produced by sea ice retreat and its global climate effects. Advances in Earth Science, 30(9): 985-995
赵进平, 史久新, 王召民, 李志军, 黄菲. 2015. 北极海冰减退引起的北极放大机理与全球气候效应. 地球科学进展, 30(9): 985-995 [DOI: 10.11867/j.issn.1001-8166.2015.09.0985http://dx.doi.org/10.11867/j.issn.1001-8166.2015.09.0985]
相关作者
相关机构