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 (2011–2017) 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 ( <math display="inline"> <semantics> <msup> <...
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ftcsic:oai:digital.csic.es:10261/172560 2023-05-15T14:48:19+02:00 Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions Olmedo, Estrella Gabarró, Carolina González-Gambau, Verónica Martínez, Justino Ballabrera-Poy, Joaquim Turiel, Antonio Portabella, Marcos Fournier, Severine Lee, Tong 2018-11-08 http://hdl.handle.net/10261/172560 https://doi.org/10.3390/rs10111772 unknown Multidisciplinary Digital Publishing Institute doi:10.3390/rs10111772 Remote Sensing 10 (11): 1772 (2018) http://hdl.handle.net/10261/172560 2018 ftcsic https://doi.org/10.3390/rs10111772 2018-11-28T00:19:12Z This paper aims to present and assess the quality of seven years (2011–2017) 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 ( <math display="inline"> <semantics> <msup> <mn>50</mn> <mo>∘</mo> </msup> </semantics> </math> N– <math display="inline"> <semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics> </math> 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. Other/Unknown Material Arctic Arctic Ocean Digital.CSIC (Spanish National Research Council) Arctic Arctic Ocean Remote Sensing 10 11 1772 |
institution |
Open Polar |
collection |
Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
unknown |
description |
This paper aims to present and assess the quality of seven years (2011–2017) 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 ( <math display="inline"> <semantics> <msup> <mn>50</mn> <mo>∘</mo> </msup> </semantics> </math> N– <math display="inline"> <semantics> <msup> <mn>90</mn> <mo>∘</mo> </msup> </semantics> </math> 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. |
author |
Olmedo, Estrella Gabarró, Carolina González-Gambau, Verónica Martínez, Justino Ballabrera-Poy, Joaquim Turiel, Antonio Portabella, Marcos Fournier, Severine Lee, Tong |
spellingShingle |
Olmedo, Estrella Gabarró, Carolina González-Gambau, Verónica Martínez, Justino Ballabrera-Poy, Joaquim Turiel, Antonio Portabella, Marcos Fournier, Severine Lee, Tong Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions |
author_facet |
Olmedo, Estrella Gabarró, Carolina González-Gambau, Verónica Martínez, Justino Ballabrera-Poy, Joaquim Turiel, Antonio Portabella, Marcos Fournier, Severine Lee, Tong |
author_sort |
Olmedo, Estrella |
title |
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_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_sort |
seven years of smos sea surface salinity at high latitudes: variability in arctic and sub-arctic regions |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
http://hdl.handle.net/10261/172560 https://doi.org/10.3390/rs10111772 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean |
genre_facet |
Arctic Arctic Ocean |
op_relation |
doi:10.3390/rs10111772 Remote Sensing 10 (11): 1772 (2018) http://hdl.handle.net/10261/172560 |
op_doi |
https://doi.org/10.3390/rs10111772 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
11 |
container_start_page |
1772 |
_version_ |
1766319408878190592 |