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A Physically Based Two-Scale Ocean Surface Emissivity Model Tuned to WindSat and SSM/I Polarimetric Brightness Temperatures

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dc.contributor.authorLee, Sang-Moo-
dc.contributor.authorGasiewski, Albin J.-
dc.date.accessioned2024-05-07T02:04:00Z-
dc.date.available2024-05-07T02:04:00Z-
dc.date.created2023-05-08-
dc.date.issued2021-12-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, Vol.60, p. 4205523-
dc.identifier.issn0196-2892-
dc.identifier.urihttps://hdl.handle.net/10371/201041-
dc.description.abstractA two-scale ocean surface emissivity model tuned to WindSat and Special Sensor Microwave/Imager (SSM/I) polarimetric brightness temperatures for general passive microwave applications is detailed. The model provides a full Stokes vector emissivity calculation at arbitrary microwave frequencies and observation angles for wind speeds of up to 15 m/s. During model development, it was found that the untuned two-scale model generally produced plausible azimuthal behavior in the ocean surface emissivity vector; however, large discrepancies between the untuned model and WindSat and SSM/I observations were observed, in particular for the zeroth-azimuthal-harmonic coefficients. These discrepancies can be ascribed to inaccuracies in contemporary ocean foam coverage and emissivity models. Accordingly, foam influences were treated using machine-tunable correction parameters incorporated as a means of improving and extending the physically based two-scale model. In addition, a hydrodynamic modulation function and the lower cutoff wavenumber for small-scale perturbation integration were treated as empirically tunable. Model tuning was performed by minimizing the metric over all available wind bins, channel frequencies, polarizations, and azimuthal harmonics. The result is an approximately eightfold reduction infrom its initial untuned model value, indicating that machine tuning can considerably reduce model errors inherent in the two-scale model to levels acceptable for oceanic passive microwave remote sensing applications. The tuned model is independently validated against NASA Global Precipitation Measurement Microwave Instrument (GMI) measurements. The tuned model and GMI observed emissivities, when scaled to the surface temperature, are in agreement to within & x00B1;0.3 K root-mean-square (rms) error, thus suggesting good applicability of the model over a wide range of microwave frequencies and wind speeds.-
dc.language영어-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.titleA Physically Based Two-Scale Ocean Surface Emissivity Model Tuned to WindSat and SSM/I Polarimetric Brightness Temperatures-
dc.typeArticle-
dc.identifier.doi10.1109/TGRS.2021.3133852-
dc.citation.journaltitleIEEE Transactions on Geoscience and Remote Sensing-
dc.identifier.wosid000766298800019-
dc.identifier.scopusid2-s2.0-85121359499-
dc.citation.startpage4205523-
dc.citation.volume60-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorLee, Sang-Moo-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusWHITECAP COVERAGE-
dc.subject.keywordPlusDIELECTRIC-CONSTANT-
dc.subject.keywordPlusWAVE SPECTRA-
dc.subject.keywordPlusSEA FOAM-
dc.subject.keywordPlusMICROWAVE-
dc.subject.keywordPlusWATER-
dc.subject.keywordPlusSLOPE-
dc.subject.keywordPlusLONG-
dc.subject.keywordAuthorSea surface-
dc.subject.keywordAuthorOcean temperature-
dc.subject.keywordAuthorSurface waves-
dc.subject.keywordAuthorSurface roughness-
dc.subject.keywordAuthorRough surfaces-
dc.subject.keywordAuthorSurface treatment-
dc.subject.keywordAuthorAtmospheric modeling-
dc.subject.keywordAuthorEmissivity-
dc.subject.keywordAuthormicrowave-
dc.subject.keywordAuthorocean-
dc.subject.keywordAuthorocean foam-
dc.subject.keywordAuthorpassive microwave remote sensing-
dc.subject.keywordAuthorroughness-
dc.subject.keywordAuthortwo-scale approximation-
dc.subject.keywordAuthorwind speed-
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Data Assimilation for Numerical Weather Prediction, Radiative Transfer Modeling, Satellite Remote Sensing

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