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dc.date.accessioned2024-03-19T16:48:20Z
dc.date.available2024-03-19T16:48:20Z
dc.date.created2023-08-20T03:01:26Z
dc.date.issued2023
dc.identifier.citationHøeg, Per Carlström, Anders . Sea Surface Roughness Determination from Grazing Angle GPS Ocean Observations and Scatterometry Simulations. Remote Sensing. 2023, 15(15)
dc.identifier.urihttp://hdl.handle.net/10852/109863
dc.description.abstractMeasurements of grazing angle GNSS-R ocean reflections combined with meteorological troposphere data are used for retrieval of ocean wave heights and surface roughness parameters. The observational results are compared to multiphase screen simulations for the same atmosphere conditions. The retrieved data from observations and simulations give equal results within the error bounds of the methods. The obtained ocean mean wave-heights are almost proportional to the square of the wind speed when applying a first-order approximation model to the high-wave-number part of the measured GNSS-R power spectra. The spectral variances from the measurements link directly to the ocean surface roughness, which is also verified by the performed multiple phase-screen wave propagation simulations. Thus, grazing angle GNSS-R techniques are an efficient method for determining the ocean state and the conditions in the boundary layer of the troposphere.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSea Surface Roughness Determination from Grazing Angle GPS Ocean Observations and Scatterometry Simulations
dc.title.alternativeENEngelskEnglishSea Surface Roughness Determination from Grazing Angle GPS Ocean Observations and Scatterometry Simulations
dc.typeJournal article
dc.creator.authorHøeg, Per
dc.creator.authorCarlström, Anders
cristin.unitcode185,15,4,70
cristin.unitnamePlasma- og romfysikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin2168152
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote Sensing&rft.volume=15&rft.spage=&rft.date=2023
dc.identifier.jtitleRemote Sensing
dc.identifier.volume15
dc.identifier.issue15
dc.identifier.doihttps://doi.org/10.3390/rs15153794
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2072-4292
dc.type.versionPublishedVersion
cristin.articleid3794


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