Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions

This paper aims to present and assess the quality of seven years (2011&#8315;2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans (<inline-formula> <math display="inline"> &l...

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Main Authors: Estrella Olmedo, Carolina Gabarró, Verónica González-Gambau, Justino Martínez, Joaquim Ballabrera-Poy, Antonio Turiel, Marcos Portabella, Severine Fournier, Tong Lee
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/10/11/1772
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author Estrella Olmedo
Carolina Gabarró
Verónica González-Gambau
Justino Martínez
Joaquim Ballabrera-Poy
Antonio Turiel
Marcos Portabella
Severine Fournier
Tong Lee
author_facet Estrella Olmedo
Carolina Gabarró
Verónica González-Gambau
Justino Martínez
Joaquim Ballabrera-Poy
Antonio Turiel
Marcos Portabella
Severine Fournier
Tong Lee
author_sort Estrella Olmedo
collection DOAJ
description This paper aims to present and assess the quality of seven years (2011&#8315;2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans (<inline-formula> <math display="inline"> <semantics> <msup> <mn>50</mn> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>N&#8315;<inline-formula> <math display="inline"> <semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.
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spelling doaj.art-26a6e3f51d1846e6a5337d502378d35e2022-12-22T01:41:24ZengMDPI AGRemote Sensing2072-42922018-11-011011177210.3390/rs10111772rs10111772Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic RegionsEstrella Olmedo0Carolina Gabarró1Verónica González-Gambau2Justino Martínez3Joaquim Ballabrera-Poy4Antonio Turiel5Marcos Portabella6Severine Fournier7Tong Lee8Department of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainDepartment of Physical Oceanography, Institute of Marine Sciences, CSIC &amp; Barcelona Expert Center, Pg. Marítim 37–49, E-08003 Barcelona, SpainJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USAJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USAThis paper aims to present and assess the quality of seven years (2011&#8315;2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans (<inline-formula> <math display="inline"> <semantics> <msup> <mn>50</mn> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>N&#8315;<inline-formula> <math display="inline"> <semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.https://www.mdpi.com/2072-4292/10/11/1772sea surface salinityremote sensingArctic oceanSMOSArctic riversdata processingquality assessment
spellingShingle Estrella Olmedo
Carolina Gabarró
Verónica González-Gambau
Justino Martínez
Joaquim Ballabrera-Poy
Antonio Turiel
Marcos Portabella
Severine Fournier
Tong Lee
Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
Remote Sensing
sea surface salinity
remote sensing
Arctic ocean
SMOS
Arctic rivers
data processing
quality assessment
title Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
title_full Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
title_fullStr Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
title_full_unstemmed Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
title_short Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions
title_sort seven years of smos sea surface salinity at high latitudes variability in arctic and sub arctic regions
topic sea surface salinity
remote sensing
Arctic ocean
SMOS
Arctic rivers
data processing
quality assessment
url https://www.mdpi.com/2072-4292/10/11/1772
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