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On the MCF Model for Predicting Radar Ocean Backscatter | IEEE Journals & Magazine | IEEE Xplore

On the MCF Model for Predicting Radar Ocean Backscatter


Abstract:

This article employs the modulated correlation function (MCF) model to describe the ocean surface in radar backscattering. Surface correlation functions derived from wind...Show More

Abstract:

This article employs the modulated correlation function (MCF) model to describe the ocean surface in radar backscattering. Surface correlation functions derived from wind wave spectra: Apel, Elfouhaily, Kudryavtsev, and Hwang models are examined. The spectral properties of the above spectra are also analyzed, including the height, slope, and saturation spectra. The results suggest that the MCF model is applicable in depicting spatial correlation of ocean surface. At the same time, the spectrum of MCF may not be proper in describing the energy cascade of ocean waves. The comparisons of backscatter are made among the MCF model and wind wave spectra, with regard to dependences of radar frequency at L-, C-, X-, and Ku-bands, wind vector, and incidence angle. The results indicate that the MCF model yields the overall minimum errors in radar backscatter against geophysical model functions (GMFs). We validate the model with the airborne and spaceborne radar measurements and show that the MCF model gives good agreement at the C-band but only moderate at the Ku-band. Meanwhile, the backscatters calculated based on different wind wave spectra can significantly deviate from each other, related to the magnitudes of the short-wave spectrum. Besides, the breaking wave effect on radar backscatter is also discussed.
Article Sequence Number: 2002715
Date of Publication: 26 February 2024

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