Inversion methods for typhoon wind fields using Sentinel-1

doi:10.3969/j.issn.1000-5641.2022.03.013

Abstract

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

CLC Number:

TP79

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.

Figures/Tables 10

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影像序号	成像时间	卫星	极化方式	成像模式	空间分辨率	幅宽/km
1	2020-08-18 18:25	哨兵1号A	VV, VH	IW	20 m × 22 m	250
2	2020-08-18 18:26	哨兵1号A	VV, VH	IW	20 m × 22 m	250
3	2020-10-27 18:39	哨兵1号A	VV, VH	EW	93 m × 87 m	410
4	2020-10-27 18:40	哨兵1号A	VV, VH	EW	93 m × 87 m	410

模型	台风名称	最大风速/(m·s^–1)	平均误差/(m·s^–1)	模型	台风名称	最大风速/(m·s^–1)	平均误差/(m·s^–1)
ECMWF	海高斯	18.3	10.5	C2014Z	海高斯	27.9	5.2
ECMWF	莫拉菲	35.8	10.5	C2014Z	莫拉菲	36.7	5.2
S1	海高斯	25.5	3.5	C-3PO	海高斯	29.2	3.6
S1	莫拉菲	42.5	3.5	C-3PO	莫拉菲	38.7	3.6
C2011	海高斯	27.9	8.7	C2019	海高斯	27.4	9.3
C2011	莫拉菲	29.8	8.7	C2019	莫拉菲	29.0	9.3
C2012	海高斯	28.6	5.5	C2021	海高斯	31.6	4.1
C2012	莫拉菲	30.5	5.5	C2021	莫拉菲	38.4	4.1
C2014V	海高斯	37.6	6.7	CRA	海高斯	30.0	0.0
C2014V	莫拉菲	50.7	6.7	CRA	莫拉菲	45.0	0.0

序号	模型名称	评估点个数	平均绝对误差/(m·s^–1)	均方根误差/(m·s^–1)	与风场产品相关系数
1	C2011	120708	0.33	2.75	0.33
2	C2012	118611	0.70	2.85	0.30
3	C2014Z	121968	4.22	5.99	0.35
4	C2014V	112013	4.21	7.21	0.21
5	C-3PO	121682	4.44	5.99	0.41
6	C2019	118937	1.24	2.84	0.31
7	C2021	80602	2.02	3.79	0.11

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