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A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface

Sea surface emissivity (SSE) is a key variable in the estimation of sea surface temperature and the sea surface radiation budget. A physical base SSE model with adequate accuracy and acceptable computational efficiency is highly desired. This paper develops a Monte Carlo ray-tracing model to compute...

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Autores principales: Cheng, Jie, Cheng, Xiaolong, Meng, Xiangchen, Zhou, Guanhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539143/
https://www.ncbi.nlm.nih.gov/pubmed/31083293
http://dx.doi.org/10.3390/s19092166
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author Cheng, Jie
Cheng, Xiaolong
Meng, Xiangchen
Zhou, Guanhua
author_facet Cheng, Jie
Cheng, Xiaolong
Meng, Xiangchen
Zhou, Guanhua
author_sort Cheng, Jie
collection PubMed
description Sea surface emissivity (SSE) is a key variable in the estimation of sea surface temperature and the sea surface radiation budget. A physical base SSE model with adequate accuracy and acceptable computational efficiency is highly desired. This paper develops a Monte Carlo ray-tracing model to compute the SSE of a wind-roughened sea surface. The adoption of a two-dimensional continuous surface model and averaging the two polarization components in advance before ray-tracing gives the model acceptable computational efficiency. The developed model can output the contributions of direct emission and the reflected component to the effective emissivity. The contribution of the reflected component to the effective emissivity reaches 0.035 at an 80° emission angle for a wind speed larger than 10 m/s. The emissivity spectra and channel emissivities collected from two field campaigns and one set of outdoor measurements are used to validate the developed model. Statistical results indicate that the absolute value of bias or difference is less than 0.5% when the view angle is less than 65°, which means the retrieval accuracy of sea surface temperature (SST) is guaranteed from the view of SSE. When the view angle increases, the accuracy of the developed model degraded, especially at the view angle of 85°. Without considering this view angle, the absolute value of bias or difference is less than 0.016, and the root mean square difference (RMSD) is less than 0.018.
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spelling pubmed-65391432019-06-04 A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface Cheng, Jie Cheng, Xiaolong Meng, Xiangchen Zhou, Guanhua Sensors (Basel) Article Sea surface emissivity (SSE) is a key variable in the estimation of sea surface temperature and the sea surface radiation budget. A physical base SSE model with adequate accuracy and acceptable computational efficiency is highly desired. This paper develops a Monte Carlo ray-tracing model to compute the SSE of a wind-roughened sea surface. The adoption of a two-dimensional continuous surface model and averaging the two polarization components in advance before ray-tracing gives the model acceptable computational efficiency. The developed model can output the contributions of direct emission and the reflected component to the effective emissivity. The contribution of the reflected component to the effective emissivity reaches 0.035 at an 80° emission angle for a wind speed larger than 10 m/s. The emissivity spectra and channel emissivities collected from two field campaigns and one set of outdoor measurements are used to validate the developed model. Statistical results indicate that the absolute value of bias or difference is less than 0.5% when the view angle is less than 65°, which means the retrieval accuracy of sea surface temperature (SST) is guaranteed from the view of SSE. When the view angle increases, the accuracy of the developed model degraded, especially at the view angle of 85°. Without considering this view angle, the absolute value of bias or difference is less than 0.016, and the root mean square difference (RMSD) is less than 0.018. MDPI 2019-05-10 /pmc/articles/PMC6539143/ /pubmed/31083293 http://dx.doi.org/10.3390/s19092166 Text en © 2019 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/).
spellingShingle Article
Cheng, Jie
Cheng, Xiaolong
Meng, Xiangchen
Zhou, Guanhua
A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title_full A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title_fullStr A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title_full_unstemmed A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title_short A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface
title_sort monte carlo emissivity model for wind-roughened sea surface
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539143/
https://www.ncbi.nlm.nih.gov/pubmed/31083293
http://dx.doi.org/10.3390/s19092166
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