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

Authors :
Lee, Sang-Moo
Gasiewski, Albin J.
Source :
IEEE Transactions on Geoscience & Remote Sensing; Mar2022, Vol. 60, p1-23, 23p
Publication Year :
2022

Abstract

A 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 $\chi ^{2}$ metric over all available wind bins, channel frequencies, polarizations, and azimuthal harmonics. The result is an approximately eightfold reduction in $\chi ^{2}$ from 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 ±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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
60
Database :
Complementary Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
156372188
Full Text :
https://doi.org/10.1109/TGRS.2021.3133852