Registro completo |
Provedor de dados: |
ArchiMer
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País: |
France
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Título: |
Low-Frequency Sea Surface Radar Doppler Echo
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Autores: |
Yurovsky, Yury Yu.
Kudryavtsev, Vladimir N.
Grodsky, Semyon A.
Chapron, Bertrand
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Data: |
2018-06
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Ano: |
2018
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Palavras-chave: |
Radar
Ocean
Backscatter
Doppler shift
Wave groups
Non-linearity
Modulation
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Resumo: |
The sea surface normalized radar backscatter cross-section (NRCS) and Doppler velocity (DV) exhibit energy at low frequencies (LF) below the surface wave peak. These NRCS and DV variations are coherent and thus may produce a bias in the DV averaged over large footprints, which is important for interpretation of Doppler scatterometer measurements. To understand the origin of LF variations, the platform-borne Ka-band radar measurements with well-pronounced LF variations at frequencies below wave peak (0.19 Hz) are analyzed. These data show that the LF NRCS is coherent with wind speed at 21 m height while the LF DV is not. The NRCS-wind correlation is significant only at frequencies below 0.01 Hz indicating either differences between near-surface wind (affecting radar signal) and 21-m height wind (actually measured) or contributions of other mechanisms of LF radar signal variations. It is shown that non-linearity in NRCS-wave slope Modulation Transfer Function (MTF) and inherent averaging within radar footprint account for NRCS and DV LF variance, with the exception of VV NRCS for which almost half of the LF variance is unexplainable by these mechanisms and perhaps attributable to wind fluctuations. Although the distribution of radar DV is quasi-Gaussian, suggesting virtually little impact of non-linearity, the LF DV variations arise due to footprint averaging of correlated local DV and non-linear NRCS. Numerical simulations demonstrate that MTF non-linearity weakly affects traditional linear MTF estimate (less than 10% for typical MTF magnitudes less than 20). Thus the linear MTF is a good approximation to evaluate the DV averaged over large footprints typical of satellite observations
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Tipo: |
Text
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Idioma: |
Inglês
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Identificador: |
http://archimer.ifremer.fr/doc/00445/55646/57298.pdf
DOI:10.3390/rs10060870
http://archimer.ifremer.fr/doc/00445/55646/
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Editor: |
Mdpi
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Formato: |
application/pdf
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Fonte: |
Remote Sensing (2072-4292) (Mdpi), 2018-06 , Vol. 10 , N. 6 , P. 870 (16p.)
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Direitos: |
2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
info:eu-repo/semantics/openAccess
restricted use
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