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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ftdoajarticles:oai:doaj.org/article:c48af59cc64b4259bd3f37c18a7b240f 2023-05-15T17:34:29+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 2018-03-01T00:00:00Z https://doi.org/10.3390/rs10030485 https://doaj.org/article/c48af59cc64b4259bd3f37c18a7b240f EN eng MDPI AG http://www.mdpi.com/2072-4292/10/3/485 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10030485 https://doaj.org/article/c48af59cc64b4259bd3f37c18a7b240f Remote Sensing, Vol 10, Iss 3, p 485 (2018) sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment Science Q article 2018 ftdoajarticles https://doi.org/10.3390/rs10030485 2022-12-31T16:27:50Z 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 Directory of Open Access Journals: DOAJ Articles Remote Sensing 10 3 485 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment Science Q |
spellingShingle |
sea surface salinity remote sensing mediterranean sea smos alboran sea data processing quality assessment Science Q 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 Science Q |
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 |
Article in Journal/Newspaper |
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 |
MDPI AG |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10030485 https://doaj.org/article/c48af59cc64b4259bd3f37c18a7b240f |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Remote Sensing, Vol 10, Iss 3, p 485 (2018) |
op_relation |
http://www.mdpi.com/2072-4292/10/3/485 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10030485 https://doaj.org/article/c48af59cc64b4259bd3f37c18a7b240f |
op_doi |
https://doi.org/10.3390/rs10030485 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
3 |
container_start_page |
485 |
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1766133346837987328 |