Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis
peer reviewed 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 a...
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Online Access: | https://orbi.uliege.be/handle/2268/221425 https://orbi.uliege.be/bitstream/2268/221425/1/olmedo2018.pdf https://doi.org/10.3390/rs10030485 |
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ftorbi:oai:orbi.ulg.ac.be:2268/221425 2024-10-20T14:10:39+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 FOCUS - Freshwater and OCeanic science Unit of reSearch - ULiège 2018-03 https://orbi.uliege.be/handle/2268/221425 https://orbi.uliege.be/bitstream/2268/221425/1/olmedo2018.pdf https://doi.org/10.3390/rs10030485 en eng MDPI http://www.mdpi.com/2072-4292/10/3/485/html urn:issn:2072-4292 https://orbi.uliege.be/handle/2268/221425 info:hdl:2268/221425 https://orbi.uliege.be/bitstream/2268/221425/1/olmedo2018.pdf doi:10.3390/rs10030485 open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess Remote Sensing, 10 (3), 485 (2018-03) sea surface salinity remote sensing Mediterranean Sea SMOS alboran sea data processing quality assessment Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique journal article http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/article peer reviewed 2018 ftorbi https://doi.org/10.3390/rs10030485 2024-09-27T07:01:35Z peer reviewed 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). Improving sea surface salinity estimates through multivariate and multisensor analyses Article in Journal/Newspaper North Atlantic University of Liège: ORBi (Open Repository and Bibliography) Remote Sensing 10 3 485 |
institution |
Open Polar |
collection |
University of Liège: ORBi (Open Repository and Bibliography) |
op_collection_id |
ftorbi |
language |
English |
topic |
sea surface salinity remote sensing Mediterranean Sea SMOS alboran sea data processing quality assessment Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique |
spellingShingle |
sea surface salinity remote sensing Mediterranean Sea SMOS alboran sea data processing quality assessment Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique 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 |
sea surface salinity remote sensing Mediterranean Sea SMOS alboran sea data processing quality assessment Physical chemical mathematical & earth Sciences Earth sciences & physical geography Physique chimie mathématiques & sciences de la terre Sciences de la terre & géographie physique |
description |
peer reviewed 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). Improving sea surface salinity estimates through multivariate and multisensor analyses |
author2 |
FOCUS - Freshwater and OCeanic science Unit of reSearch - ULiège |
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 |
MDPI |
publishDate |
2018 |
url |
https://orbi.uliege.be/handle/2268/221425 https://orbi.uliege.be/bitstream/2268/221425/1/olmedo2018.pdf https://doi.org/10.3390/rs10030485 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing, 10 (3), 485 (2018-03) |
op_relation |
http://www.mdpi.com/2072-4292/10/3/485/html urn:issn:2072-4292 https://orbi.uliege.be/handle/2268/221425 info:hdl:2268/221425 https://orbi.uliege.be/bitstream/2268/221425/1/olmedo2018.pdf doi:10.3390/rs10030485 |
op_rights |
open access http://purl.org/coar/access_right/c_abf2 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_ |
1813450625734672384 |