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Novel Approach to Wind Retrieval from Sentinel-1 SAR in Tropical Cyclones.

Authors :
Zhao, Xianbin
Shao, Weizeng
Hao, Mengyu
Jiang, Xingwei
Source :
Canadian Journal of Remote Sensing. Feb2023, Vol. 49 Issue 1, p1-13. 13p.
Publication Year :
2023

Abstract

The strong winds in tropical cyclones (TCs) are commonly retrieved from cross-polarized SAR images using a geophysical model function (GMF). However, the accuracy of wind retrieval in cross-polarization is significantly reduced at the edges of sub-swaths. In this study, a novel approach to TC wind retrieval from VV polarized SAR images is proposed based on using the azimuthal cutoff wavelength to represent the effect of velocity bunching. A total of 12 dual-polarized (VV and VH) Sentinel-1 (S-1) images acquired in the interferometric wide (IW) mode were used, five of which were collocated with measurements taken by the Stepped-Frequency Microwave Radiometer (SFMR) on board an NOAA aircraft. The SAR-based azimuthal cutoff wavelengths were found to be linearly related to the SFMR wind speeds. Based on this finding, an empirical GMF for TC wind speed retrieval from VV S-1 images was constructed. The inversion results from seven images using this approach were validated against the wind products from the Advanced Scatterometer and the European Center for Medium-Range Weather Forecasts. The RMSE of the wind speed was 2.15 m s−1 and the correlation coefficient (COR) was 0.83 at wind speeds of less than 25 m s−1, while the RMSE was 2.66 m s−1 and the COR was 0.97 when compared with wind retrieval using the VH-polarized GMF S1IW.NR at wind speeds greater than 25 m s−1. The proposed algorithm performs well and has two advantages: (1) it is not subject to the saturation problem of the VV backscattering signal and (2) the discontinuity of the retrieval results obtained using VH GMF at the edges of sub-swaths is improved. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07038992
Volume :
49
Issue :
1
Database :
Academic Search Index
Journal :
Canadian Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
174277092
Full Text :
https://doi.org/10.1080/07038992.2023.2254839