On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR

The accurate retrieval of sea-surface wind field data is crucial for weather forecasting and climate modeling. Despite this, the complexity of sea surface conditions poses significant challenges for satellite-based synthetic aperture radar (SAR) wind retrieval techniques. This study introduces a Bay...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 17; s. 10367 - 10379
Hlavní autori:	Zhu, Yuting, Grieco, Giuseppe, Lin, Jiarong, Portabella, Marcos, Wang, Xiaoqing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Algorithms Azimuth Azimuth cutoff Bayesian analysis Bayesian inversion algorithm Climate models Cost function Cut off wavelength Fields (mathematics) Information retrieval Oceanography Parameter sensitivity Probability theory Radar measurements Radar polarimetry Remote sensing SAR (radar) Scatterometers Sea measurements Sea state Sea states Sea surface Surface wind Synthetic aperture radar Vectors Wavelength Weather forecasting Wind direction Wind fields Wind forecasting Wind measurement wind retrieval Wind speed
ISSN:	1939-1404, 2151-1535
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Abstract	The accurate retrieval of sea-surface wind field data is crucial for weather forecasting and climate modeling. Despite this, the complexity of sea surface conditions poses significant challenges for satellite-based synthetic aperture radar (SAR) wind retrieval techniques. This study introduces a Bayesian inversion algorithm that incorporates azimuth cutoff wavelength information-a parameter previously underutilized and highly sensitive to varying wind conditions. We aimed to enhance the accuracy of SAR-derived wind estimations to enable more reliable interpretations of marine atmospheric dynamics. The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. The proposed method was comprehensively validated using Sentinel-1 and Gaofen-3 SAR datasets against buoy measurements and wind estimations from scatterometers. The results demonstrated that the proposed method significantly improved the accuracy of wind speed estimations, especially under low-wind conditions and different sea-state conditions, without substantially increasing the computational burden. Although the wind direction retrieval displayed limited enhancement, the improved accuracy in wind speed estimations provides considerable benefits for operational meteorological applications. These findings suggest that the integration of azimuth cutoff information could be a critical step toward obtaining more accurate and reliable wind field retrievals from SAR data, thereby advancing the field of remote sensing and oceanography.
AbstractList	The accurate retrieval of sea-surface wind field data is crucial for weather forecasting and climate modeling. Despite this, the complexity of sea surface conditions poses significant challenges for satellite-based synthetic aperture radar (SAR) wind retrieval techniques. This study introduces a Bayesian inversion algorithm that incorporates azimuth cutoff wavelength information-a parameter previously underutilized and highly sensitive to varying wind conditions. We aimed to enhance the accuracy of SAR-derived wind estimations to enable more reliable interpretations of marine atmospheric dynamics. The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. The proposed method was comprehensively validated using Sentinel-1 and Gaofen-3 SAR datasets against buoy measurements and wind estimations from scatterometers. The results demonstrated that the proposed method significantly improved the accuracy of wind speed estimations, especially under low-wind conditions and different sea-state conditions, without substantially increasing the computational burden. Although the wind direction retrieval displayed limited enhancement, the improved accuracy in wind speed estimations provides considerable benefits for operational meteorological applications. These findings suggest that the integration of azimuth cutoff information could be a critical step toward obtaining more accurate and reliable wind field retrievals from SAR data, thereby advancing the field of remote sensing and oceanography.
Author	Zhu, Yuting Portabella, Marcos Lin, Jiarong Grieco, Giuseppe Wang, Xiaoqing
Author_xml	– sequence: 1 givenname: Yuting orcidid: 0000-0001-5039-9601 surname: Zhu fullname: Zhu, Yuting email: zhuyt63@mail2.sysu.edu.cn organization: School of Electronic and Communication Engineering, Sun Yat-Sen University, Shenzhen, China – sequence: 2 givenname: Giuseppe orcidid: 0000-0002-1255-599X surname: Grieco fullname: Grieco, Giuseppe email: giuseppe.grieco@cnr.it organization: Istituto di Scienze Marine-Consiglio Nazionale delle Ricerche (CNR-ISMAR), Calata Porta di Massa, Napoli, Italy – sequence: 3 givenname: Jiarong orcidid: 0009-0008-2894-507X surname: Lin fullname: Lin, Jiarong email: linjr9@mail2.sysu.edu.cn organization: School of Electronic and Communication Engineering, Sun Yat-Sen University, Shenzhen, China – sequence: 4 givenname: Marcos orcidid: 0000-0002-9972-9090 surname: Portabella fullname: Portabella, Marcos email: portabella@icm.csic.es organization: Barcelona Expert Center, Institute of Marine Sciences (ICM-CSIC), Barcelona, Spain – sequence: 5 givenname: Xiaoqing orcidid: 0000-0002-7818-0449 surname: Wang fullname: Wang, Xiaoqing email: wangxq58@mail.sysu.edu.cn organization: School of Electronic and Communication Engineering, Sun Yat-Sen University, Shenzhen, China
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SubjectTerms	Accuracy Algorithms Azimuth Azimuth cutoff Bayesian analysis Bayesian inversion algorithm Climate models Cost function Cut off wavelength Fields (mathematics) Information retrieval Oceanography Parameter sensitivity Probability theory Radar measurements Radar polarimetry Remote sensing SAR (radar) Scatterometers Sea measurements Sea state Sea states Sea surface Surface wind Synthetic aperture radar Vectors Wavelength Weather forecasting Wind direction Wind fields Wind forecasting Wind measurement wind retrieval Wind speed
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Title	On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR
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