Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis
International audience 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 Atlanti...
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Online Access: | https://hal.science/hal-01780372 https://hal.science/hal-01780372/document https://hal.science/hal-01780372/file/remotesensing-10-00485-1.pdf https://doi.org/10.3390/rs10030485 |
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ftunivtoulon:oai:HAL:hal-01780372v1 2024-05-12T08:08:08+00:00 Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis Olmedo, Estrella Taupier-Letage, Isabelle Turiel, Antonio Alvera-Azcarate, Aida Institute of Marine Sciences / Institut de Ciències del Mar Barcelona (ICM) Consejo Superior de Investigaciones Cientificas España = Spanish National Research Council Spain (CSIC) Institut méditerranéen d'océanologie (MIO) Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS) Université de Liège 2018-03 https://hal.science/hal-01780372 https://hal.science/hal-01780372/document https://hal.science/hal-01780372/file/remotesensing-10-00485-1.pdf https://doi.org/10.3390/rs10030485 en eng HAL CCSD MDPI info:eu-repo/semantics/altIdentifier/doi/10.3390/rs10030485 hal-01780372 https://hal.science/hal-01780372 https://hal.science/hal-01780372/document https://hal.science/hal-01780372/file/remotesensing-10-00485-1.pdf doi:10.3390/rs10030485 info:eu-repo/semantics/OpenAccess ISSN: 2072-4292 Remote Sensing https://hal.science/hal-01780372 Remote Sensing, 2018, 10 (3), ⟨10.3390/rs10030485⟩ Mediterranean sea Remote sensing Sea surface salinity Quality assessment Alboran sea Smos Data processing [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDE.MCG]Environmental Sciences/Global Changes info:eu-repo/semantics/article Journal articles 2018 ftunivtoulon https://doi.org/10.3390/rs10030485 2024-04-18T00:22:26Z International audience 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). Article in Journal/Newspaper North Atlantic Université de Toulon: HAL Remote Sensing 10 3 485 |
institution |
Open Polar |
collection |
Université de Toulon: HAL |
op_collection_id |
ftunivtoulon |
language |
English |
topic |
Mediterranean sea Remote sensing Sea surface salinity Quality assessment Alboran sea Smos Data processing [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDE.MCG]Environmental Sciences/Global Changes |
spellingShingle |
Mediterranean sea Remote sensing Sea surface salinity Quality assessment Alboran sea Smos Data processing [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDE.MCG]Environmental Sciences/Global Changes Olmedo, Estrella Taupier-Letage, Isabelle Turiel, Antonio Alvera-Azcarate, Aida Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis |
topic_facet |
Mediterranean sea Remote sensing Sea surface salinity Quality assessment Alboran sea Smos Data processing [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDE.MCG]Environmental Sciences/Global Changes |
description |
International audience 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). |
author2 |
Institute of Marine Sciences / Institut de Ciències del Mar Barcelona (ICM) Consejo Superior de Investigaciones Cientificas España = Spanish National Research Council Spain (CSIC) Institut méditerranéen d'océanologie (MIO) Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS) Université de Liège |
format |
Article in Journal/Newspaper |
author |
Olmedo, Estrella Taupier-Letage, Isabelle Turiel, Antonio Alvera-Azcarate, Aida |
author_facet |
Olmedo, Estrella Taupier-Letage, Isabelle Turiel, Antonio Alvera-Azcarate, Aida |
author_sort |
Olmedo, Estrella |
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 |
HAL CCSD |
publishDate |
2018 |
url |
https://hal.science/hal-01780372 https://hal.science/hal-01780372/document https://hal.science/hal-01780372/file/remotesensing-10-00485-1.pdf https://doi.org/10.3390/rs10030485 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 2072-4292 Remote Sensing https://hal.science/hal-01780372 Remote Sensing, 2018, 10 (3), ⟨10.3390/rs10030485⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.3390/rs10030485 hal-01780372 https://hal.science/hal-01780372 https://hal.science/hal-01780372/document https://hal.science/hal-01780372/file/remotesensing-10-00485-1.pdf doi:10.3390/rs10030485 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.3390/rs10030485 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
3 |
container_start_page |
485 |
_version_ |
1798851039499124736 |