Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30371
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dc.contributor.authorZhu, Shuaien_UK
dc.contributor.authorShao, Weizengen_UK
dc.contributor.authorMarino, Armandoen_UK
dc.contributor.authorSun, Jianen_UK
dc.contributor.authorYuan, Xinzheen_UK
dc.date.accessioned2019-10-30T01:02:25Z-
dc.date.available2019-10-30T01:02:25Z-
dc.date.issued2020-02en_UK
dc.identifier.urihttp://hdl.handle.net/1893/30371-
dc.description.abstractSynthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution. The geophysical model function (GMF), which is widely employed for wind speed retrieval from SAR data, describes the relationship between the SAR normalized radar cross-section (NRCS) at the copolarization channel (vertical-vertical and horizontal-horizontal) and a wind vector. SAR-measured NRCS at cross-polarization channels (horizontal-vertical and vertical-horizontal) correlates with wind speed. In this study, a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function. GF-3 SAR can acquire data in a quad-polarization strip mode, which includes cross-polarization channels. The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts. In particular, the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS. The accuracy of SAR-derived wind speed is around 2.10 m s-1 root mean square error, which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration. The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms. This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.en_UK
dc.language.isoenen_UK
dc.publisherBMCen_UK
dc.relationZhu S, Shao W, Marino A, Sun J & Yuan X (2020) Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data. Journal of Ocean University of China, 19 (1), pp. 23-35. https://doi.org/10.1007/s11802-020-4215-9en_UK
dc.rightsThis item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. This is a post-peer-review, pre-copyedit version of an article published in Journal of Ocean University of China. The final authenticated version is available online at: https://doi.org/10.1007/s11802-020-4215-9en_UK
dc.rights.urihttps://storre.stir.ac.uk/STORREEndUserLicence.pdfen_UK
dc.subjectwinden_UK
dc.subjectGaofen-3 synthetic aperture radaren_UK
dc.subjectcross-polarizationen_UK
dc.titleSemi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Dataen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2020-10-01en_UK
dc.rights.embargoreason[Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data_Ocean.pdf] Publisher requires embargo of 12 months after formal publication.en_UK
dc.identifier.doi10.1007/s11802-020-4215-9en_UK
dc.citation.jtitleJournal of Ocean University of China (English Edition)en_UK
dc.citation.issn1993-5021en_UK
dc.citation.issn1672-5182en_UK
dc.citation.volume19en_UK
dc.citation.issue1en_UK
dc.citation.spage23en_UK
dc.citation.epage35en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderEuropean Space Agencyen_UK
dc.author.emailarmando.marino@stir.ac.uken_UK
dc.citation.date30/09/2019en_UK
dc.contributor.affiliationZhejiang Ocean Universityen_UK
dc.contributor.affiliationZhejiang Ocean Universityen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationOcean University of Chinaen_UK
dc.contributor.affiliationNational Satellite Ocean Application Service (NSOAS)en_UK
dc.identifier.isiWOS:000489498100001en_UK
dc.identifier.scopusid2-s2.0-85073933777en_UK
dc.identifier.wtid1470581en_UK
dc.contributor.orcid0000-0002-4531-3102en_UK
dc.date.accepted2019-07-01en_UK
dc.date.filedepositdate2019-10-29en_UK
Appears in Collections:Biological and Environmental Sciences Journal Articles

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