Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis
A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) fields over the North Atlantic Ocean and the Mediter...
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ftmdpi:oai:mdpi.com:/2072-4292/10/3/485/ 2023-08-20T04:08:27+02:00 Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis Estrella Olmedo Isabelle Taupier-Letage Antonio Turiel Aida Alvera-Azcárate agris 2018-03-20 application/pdf https://doi.org/10.3390/rs10030485 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs10030485 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 3; Pages: 485 sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment Text 2018 ftmdpi https://doi.org/10.3390/rs10030485 2023-07-31T21:26:21Z A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) fields over the North Atlantic Ocean and the Mediterranean Sea. The debiased non-Bayesian retrieval mitigates the systematic errors produced by the contamination of the land over the sea. In addition, this retrieval improves the coverage by means of multiyear statistical filtering criteria. This methodology allows obtaining SMOS SSS fields in the Mediterranean Sea. However, the resulting SSS suffers from a seasonal (and other time-dependent) bias. This time-dependent bias has been characterized by means of specific Empirical Orthogonal Functions (EOFs). Finally, high resolution Sea Surface Temperature (OSTIA SST) maps have been used for improving the spatial and temporal resolution of the SMOS SSS maps. The presented methodology practically reduces the error of the SMOS SSS in the Mediterranean Sea by half. As a result, the SSS dynamics described by the new SMOS maps in the Algerian Basin and the Balearic Front agrees with the one described by in situ SSS, and the mesoscale structures described by SMOS in the Alboran Sea and in the Gulf of Lion coincide with the ones described by the high resolution remotely-sensed SST images (AVHRR). Text North Atlantic MDPI Open Access Publishing Remote Sensing 10 3 485 |
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Open Polar |
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MDPI Open Access Publishing |
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English |
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sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment |
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sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment Estrella Olmedo Isabelle Taupier-Letage Antonio Turiel Aida Alvera-Azcárate Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
topic_facet |
sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment |
description |
A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) fields over the North Atlantic Ocean and the Mediterranean Sea. The debiased non-Bayesian retrieval mitigates the systematic errors produced by the contamination of the land over the sea. In addition, this retrieval improves the coverage by means of multiyear statistical filtering criteria. This methodology allows obtaining SMOS SSS fields in the Mediterranean Sea. However, the resulting SSS suffers from a seasonal (and other time-dependent) bias. This time-dependent bias has been characterized by means of specific Empirical Orthogonal Functions (EOFs). Finally, high resolution Sea Surface Temperature (OSTIA SST) maps have been used for improving the spatial and temporal resolution of the SMOS SSS maps. The presented methodology practically reduces the error of the SMOS SSS in the Mediterranean Sea by half. As a result, the SSS dynamics described by the new SMOS maps in the Algerian Basin and the Balearic Front agrees with the one described by in situ SSS, and the mesoscale structures described by SMOS in the Alboran Sea and in the Gulf of Lion coincide with the ones described by the high resolution remotely-sensed SST images (AVHRR). |
format |
Text |
author |
Estrella Olmedo Isabelle Taupier-Letage Antonio Turiel Aida Alvera-Azcárate |
author_facet |
Estrella Olmedo Isabelle Taupier-Letage Antonio Turiel Aida Alvera-Azcárate |
author_sort |
Estrella Olmedo |
title |
Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
title_short |
Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
title_full |
Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
title_fullStr |
Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
title_full_unstemmed |
Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
title_sort |
improving smos sea surface salinity in the western mediterranean sea through multivariate and multifractal analysis |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10030485 |
op_coverage |
agris |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing; Volume 10; Issue 3; Pages: 485 |
op_relation |
Ocean Remote Sensing https://dx.doi.org/10.3390/rs10030485 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10030485 |
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Remote Sensing |
container_volume |
10 |
container_issue |
3 |
container_start_page |
485 |
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1774720709930516480 |