{"title":"Wind field reconstruction based on dual-polarized synthetic aperture radar during a tropical cyclone","authors":"Zhengzhong Lai, Mengyu Hao, Weizeng Shao, Wei Shen, Yuyi Hu, Xingwei Jiang","doi":"10.1080/22797254.2023.2273867","DOIUrl":null,"url":null,"abstract":"A wind field reconstruction method for dual-polarized (vertical-vertical [VV] and vertical-horizontal [VH]) Sentinel-1 (S-1) synthetic aperture radar (SAR) images collected during tropical cyclones (TCs) that does not require external information is proposed. Forty S-1 images acquired in interferometric-wide (IW) and extra-wide (EW) modes during the Satellite Hurricane Observation Campaign in 2015–2022 were collected. Stepped-frequency microwave radiometer (SFMR) observations made onboard the National Oceanic and Atmospheric Administration’s hurricane aircraft are available for 13 images. The geophysical model functions, namely VV-polarized C-SARMOD and cross-polarized S-1 IW/EW mode wind speed retrieval model after noise removal (S1IW.NR/S1EW.NR), were employed to invert the wind fields from the collected images. TC wind fields were reconstructed based on SAR-derived winds, enhancing TC intensity representation in the VV-polarized SAR retrievals and minimizing the error of the VH-polarized SAR retrievals at the sub-swath edge. The wind speeds retrieved from the SAR IW image were validated against the remote-sensing products from the soil moisture active passive (SMAP) radiometer, yielding a root mean squared error (RMSE) of approximately 4.3 m s−1, which is slightly smaller than the RMSE (4.4 m s−1) for the operational CyclObs wind product provided by the French Research Institute for Exploitation of the Sea (IFREMER). However, the CyclObs wind product has better performance than the approach proposed in this paper for the S-1 EW mode. Moreover, the RMSE of the wind speed between SAR-derived wind speed obtained using the proposed approach and the CyclObs wind product is within 3 m s−1 in all flow directions clockwise relative to north centered on the TC’s eye. This study provides an alternative method for TC wind retrieval from dual-polarized S-1 images without suffering saturation problem and external information; however, the pattern of the wind field around the TC’s eye needs to be further improved, especially at the head and back of the TC’s eye.","PeriodicalId":49077,"journal":{"name":"European Journal of Remote Sensing","volume":"123 3-4","pages":"0"},"PeriodicalIF":3.7000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/22797254.2023.2273867","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
A wind field reconstruction method for dual-polarized (vertical-vertical [VV] and vertical-horizontal [VH]) Sentinel-1 (S-1) synthetic aperture radar (SAR) images collected during tropical cyclones (TCs) that does not require external information is proposed. Forty S-1 images acquired in interferometric-wide (IW) and extra-wide (EW) modes during the Satellite Hurricane Observation Campaign in 2015–2022 were collected. Stepped-frequency microwave radiometer (SFMR) observations made onboard the National Oceanic and Atmospheric Administration’s hurricane aircraft are available for 13 images. The geophysical model functions, namely VV-polarized C-SARMOD and cross-polarized S-1 IW/EW mode wind speed retrieval model after noise removal (S1IW.NR/S1EW.NR), were employed to invert the wind fields from the collected images. TC wind fields were reconstructed based on SAR-derived winds, enhancing TC intensity representation in the VV-polarized SAR retrievals and minimizing the error of the VH-polarized SAR retrievals at the sub-swath edge. The wind speeds retrieved from the SAR IW image were validated against the remote-sensing products from the soil moisture active passive (SMAP) radiometer, yielding a root mean squared error (RMSE) of approximately 4.3 m s−1, which is slightly smaller than the RMSE (4.4 m s−1) for the operational CyclObs wind product provided by the French Research Institute for Exploitation of the Sea (IFREMER). However, the CyclObs wind product has better performance than the approach proposed in this paper for the S-1 EW mode. Moreover, the RMSE of the wind speed between SAR-derived wind speed obtained using the proposed approach and the CyclObs wind product is within 3 m s−1 in all flow directions clockwise relative to north centered on the TC’s eye. This study provides an alternative method for TC wind retrieval from dual-polarized S-1 images without suffering saturation problem and external information; however, the pattern of the wind field around the TC’s eye needs to be further improved, especially at the head and back of the TC’s eye.
提出了一种不需要外界信息的Sentinel-1 (S-1)合成孔径雷达(SAR)双极化(垂直-垂直[VV]和垂直-水平[VH])图像风场重建方法。收集了2015-2022年卫星飓风观测运动期间以干涉宽(IW)和超宽(EW)模式获取的40幅S-1图像。步进频率微波辐射计(SFMR)在国家海洋和大气管理局的飓风飞机上观测到13幅图像。利用vv极化C-SARMOD和交叉极化S-1 IW/EW模式去噪后风速反演模型(S1IW.NR/S1EW.NR)对采集图像进行风场反演。基于SAR衍生风重建TC风场,增强了vh极化SAR检索中TC强度的表征,减小了vh极化SAR检索在子带边缘的误差。从SAR IW图像中获取的风速与土壤湿度主被动(SMAP)辐射计的遥感产品进行了验证,得到的均方根误差(RMSE)约为4.3 m s - 1,略小于法国海洋开发研究所(IFREMER)提供的操作CyclObs风产品的RMSE (4.4 m s - 1)。然而,在S-1 EW模式下,CyclObs风产品的性能优于本文提出的方法。此外,在以风眼为中心的顺时针方向上,利用该方法获得的sar反演风速与CyclObs风产品的均方根误差(RMSE)在3 m s−1以内。该研究提供了一种从双偏振S-1图像中提取TC风的替代方法,不受饱和问题和外部信息的影响;然而,风眼周围的风场格局需要进一步改善,特别是在风眼的头部和后部。
期刊介绍:
European Journal of Remote Sensing publishes research papers and review articles related to the use of remote sensing technologies. The Journal welcomes submissions on all applications related to the use of active or passive remote sensing to terrestrial, oceanic, and atmospheric environments. The most common thematic areas covered by the Journal include:
-land use/land cover
-geology, earth and geoscience
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-geography and landscape
-ecology and environmental science
-support to land management
-hydrology and water resources
-atmosphere and meteorology
-oceanography
-new sensor systems, missions and software/algorithms
-pre processing/calibration
-classifications
-time series/change analysis
-data integration/merging/fusion
-image processing and analysis
-modelling
European Journal of Remote Sensing is a fully open access journal. This means all submitted articles will, if accepted, be available for anyone to read anywhere, at any time, immediately on publication. There are no charges for submission to this journal.