Journal of East China Normal University(Natural Science) >

2022 , Vol. 2022 >Issue 3: 125 - 136

DOI: https://doi.org/10.3969/j.issn.1000-5641.2022.03.013

Estuary and Coastal Research

Inversion methods for typhoon wind fields using Sentinel-1

  • Peng YU ,
  • Xiaojing ZHONG ,
  • Xupu GENG
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  • 1. College of Computer and Information Engineering, Xiamen University of Technology, Xiamen Fujian　361024, China
    2. College of Harbour and Coastal Engineering, Jimei University, Xiamen Fujian　361021, China
    3. State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen Fujian　361102, China

Received date: 2021-06-16

  Accepted date: 2021-10-25

  Online published: 2022-05-19

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Abstract

Under high-speed wind conditions, cross-polarization synthetic aperture radar (SAR) is not affected by signal saturation. Hence, SAR can be used to observe expansive, high-speed wind fields under all-weather, day- and night-time conditions and offers great potential for monitoring typhoons. Sentinel-1, which was launched by the European Space Agency (ESA), is one of the few available SAR satellites in orbit at present that can provide cross-polarization data. Based on Sentinel-1 cross-polarization data, seven different cross-polarization models, including the C-band cross polarization ocean model (C-2PO), C-band cross-polarization coupled-parameters ocean model (C-3PO), and quad-polarization stripmap cross-polarization model (QPS-CP), developed from 2011 to 2021 were used to estimate the typhoon wind fields of Higos and Molave. A denoising method was applied to remove the noise from extra wide (EW) mode SAR images. The results show that the denoising method can effectively reduce the noise and improve the retrieved wind fields. The C-3PO model performs well in monitoring high-speed winds, but does not obtain reliable results for low- to moderate-speed winds compared with the Sentinel-1 Level-2 Ocean (OCN) product. By merging results from the cross-polarization model and the OCN wind product, the combined wind field can effectively reproduce the inner high-speed winds and outer relative low-speed winds. This study is of significant value for forecasting, data assimilation, and research of typhoon disasters.

Key words： Sentinel-1; typhoon; SAR; cross-polarization

Cite this article

Peng YU , Xiaojing ZHONG , Xupu GENG . Inversion methods for typhoon wind fields using Sentinel-1[J]. Journal of East China Normal University(Natural Science), 2022 , 2022(3) : 125 -136 . DOI: 10.3969/j.issn.1000-5641.2022.03.013

References

1 端义宏, 陈联寿, 许映龙, 等. 我国台风监测预报预警体系的现状及建议. 中国工程科学, 2012, 14 (9): 4- 9.
2 尤再进. 中国海岸带淹没和侵蚀重大灾害及减灾策略. 中国科学院院刊, 2016, 31 (10): 1190- 1196.
3 STOFFELEN A, ANDERSON D. Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4. Journal of Geophysical Research: Oceans, 1997, 102 (C3): 5767- 5780.
4 QUILFEN Y, CHAPRON B, ELFOUHAILY T, et al. Observation of tropical cyclones by high-resolution scatterometry. Journal of Geophysical Research:Oceans, 1998, 103 (C4): 7767- 7786.
5 HERSBACH H. Comparison of c-band scatterometer CMOD5. N equivalent neutral winds with ECMWF. Journal of Atmospheric and Oceanic Technology, 2010, 27 (4): 721- 736.
6 STOFFELEN A, VERSPEEK J A, VOGELZANG J, et al. The CMOD7 geophysical model function for ASCAT and ERS wind retrievals. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10 (5): 2123- 2134.
7 DONNELLY W J, CARSWELL J R, MCINTOSH R E, et al. Revised ocean backscatter models at C and Ku band under high-wind conditions. Journal of Geophysical Research: Oceans, 1999, 104 (C5): 11485- 11497.
8 DONELAN M A, HAUS B K, REUL N, et al. On the limiting aerodynamic roughness of the ocean in very strong winds. Geophysical Research Letters, 2004, 31 (18): 1- 5.
9 SHEN H, HE Y, PERRIE W. Speed ambiguity in hurricane wind retrieval from SAR imagery. International Journal of Remote Sensing, 2009, 30 (11): 2827- 2836.
10 李晓峰, 张彪, 杨晓峰. 星载合成孔径雷达遥感海洋风场波浪场. 雷达学报, 2020, 9 (3): 425- 443.
11 KOCH W. Directional analysis of SAR images aiming at wind direction. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42 (4): 702- 710.
12 KUDRYAVTSEV V, JOHANNESSEN J. On effect of wave breaking on short wind waves. Geophysical Research Letters, 2004, 31, L20310.
13 HWANG P A, ZHANG B, PERRIE W. Depolarized radar return for breaking wave measurement and hurricane wind retrieval. Geophysical Research Letters, 2010, 37, L01604.
14 FOIS F, HOOGEBOOM P, LE CHEVALIER F, et al. Future ocean scatterometry: On the use of cross-polar scattering to observe very high winds. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53 (9): 5009- 5020.
15 MOUCHE A, CHAPRON B. Global C-band envisat, RADARSAT-2 and Sentinel-1 SAR measurements in copolarization and cross-polarization. Journal of Geophysical Research:Oceans, 2015, 120 (11): 7195- 7207.
16 VACHON P W, WOLFE J. C-band cross-polarization wind speed retrieval. IEEE Geoscience and Remote Sensing Letters, 2011, 8 (3): 456- 459.
17 ZHANG B, PERRIE W. Cross-polarized synthetic aperture radar: A new potential measurement technique for hurricanes. Bulletin of the American Meteorological Society, 2012, 93 (4): 531- 541.
18 ZHANG B, PERRIE W, ZHANG J A, et al. High-resolution hurricane vector winds from C-band Dual-polarization SAR observations. Journal of Atmospheric and Oceanic Technology, 2014, 31 (2): 272- 286.
19 VAN ZADELHOFF G J, STOFFELEN A, VACHON P W, et al. Retrieving hurricane wind speeds using cross-polarization C-band measurements. Atmospheric Measurement Techniques, 2014, 7 (2): 437- 449.
20 ZHANG G, LI X, PERRIE W, et al. A hurricane wind speed retrieval model for C-band RADARSAT-2 Cross-polarization ScanSAR images. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55 (8): 4766- 4774.
21 ZHANG T, LI X, FENG Q, et al. Retrieval of sea surface wind speeds from Gaofen-3 full polarimetric data. Remote Sensing, 2019, 11 (7): 813.
22 FANG H, PERRIE W, FAN G, et al. High-resolution sea surface wind speeds of Super Typhoon Lekima (2019) retrieved by Gaofen-3 SAR [J]. Frontiers of Earth Science, 2021. DOI: 10.1007/s11707-021-0887-8.
23 王旻燕, 姚爽, 姜立鹏, 等. 我国全球大气再分析(CRA-40)卫星遥感资料的收集和预处理. 气象科技进展, 2018, 8 (1): 158- 163.
24 王隽, 杨劲松, 黄韦艮, 等. 多视处理对SAR船只探测的影响. 遥感学报, 2008, 12 (3): 399- 404.
25 PARK J, WON J, KOROSOV A A, et al. Textural noise correction for Sentinel-1 TOPSAR Cross-polarization channel images. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57 (6): 4040- 4049.
26 YU P, JOHANNESSEN J A, YAN X, et al. A study of the intensity of tropical cyclone Idai using Dual-polarization Sentinel-1 data. Remote Sensing, 2019, 11 (23): 2837.
27 SUN Y, LI X. Denoising Sentinel-1 extra-wide mode cross-polarization images over sea ice. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59 (3): 2116- 2131.
28 MOUCHE A A, CHAPRON B, ZHANG B, et al. Combined co- and cross-polarized SAR measurements under extreme wind conditions. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55 (12): 6746- 6755.
29 JIANG Z, LI Y, YU F, et al. A damped Newton variational inversion method for SAR wind retrieval. Journal of Geophysical Research: Atmospheres, 2017, 122 (2): 823- 845.
30 PORTABELLA M, STOFFELEN A, JOHANNESSEN J A. Toward an optimal inversion method for synthetic aperture radar wind retrieval. Journal of Geophysical Research: Oceans, 2002, 107, 3086C8.
31 CHRISTIANSEN M B, KOCH W, HORSTMANN J, et al. Wind resource assessment from C-band SAR. Remote Sensing of Environment, 2006, 105 (1): 68- 81.
32 戚纤云, 周云轩, 田波, 等. 基于Sentinel-1A的长江口近岸风矢量场反演研究. 华东师范大学学报(自然科学版), 2017, (6): 126- 135.
33 TOURNADRE J, QUILFEN Y. Impact of rain cell on scatterometer data: 1. Theory and modeling. Journal of Geophysical Research: Oceans, 2003, 108 (C7): 1- 18.
34 ALPERS W, ZHANG B, MOUCHE A, et al. Rain footprints on C-band synthetic aperture radar images of the ocean-revisited. Remote Sensing of Environment, 2016, 187, 169- 185.
35 ZHANG G, LI X, PERRIE W, et al. Rain effects on the hurricane observations over the ocean by C-band Synthetic Aperture Radar. Journal of Geophysical Research:Oceans, 2016, 121 (1): 14- 26.
36 XUE S, GENG X, MENG L, et al. HISEA-1: The first C-band SAR miniaturized satellite for ocean and coastal observation. Remote Sensing, 2021, 13 (11): 2076.
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