Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach
This study assesses the capability of Surface Quasi-Geostrophy (SQG) to reconstruct the three-dimensional (3D) dynamics in four critical areas of the Arctic Ocean: the Nordic, Barents, East Siberian, and Beaufort Seas. We first reconstruct the upper ocean dynamics from TOPAZ4 reanalysis of sea surfa...
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2023
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Online Access: | http://hdl.handle.net/10261/308024 https://doi.org/10.3390/rs15071722 |
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ftcsic:oai:digital.csic.es:10261/308024 2024-02-11T10:00:40+01:00 Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach Umbert, Marta De-Andrés, Eva Gonçalves-Araujo, Rafael Gutiérrez, Marina Raj, Roshin Bertino, Laurent Gabarró, Carolina Isern-Fontanet, Jordi 2023-03-23 http://hdl.handle.net/10261/308024 https://doi.org/10.3390/rs15071722 unknown Multidisciplinary Digital Publishing Institute doi:10.3390/rs15071722 Remote Sensing 15 (7): 1722 (2023) http://hdl.handle.net/10261/308024 open artículo 2023 ftcsic https://doi.org/10.3390/rs15071722 2024-01-16T11:41:18Z This study assesses the capability of Surface Quasi-Geostrophy (SQG) to reconstruct the three-dimensional (3D) dynamics in four critical areas of the Arctic Ocean: the Nordic, Barents, East Siberian, and Beaufort Seas. We first reconstruct the upper ocean dynamics from TOPAZ4 reanalysis of sea surface height (SSH), surface buoyancy (SSB), and surface velocities (SSV) and validate the results with the geostrophic and total TOPAZ4 velocities. The reconstruction of upper ocean dynamics using SSH fields is in high agreement with the geostrophic velocities, with correlation coefficients greater than 0.8 for the upper 400 m. SSH reconstructions outperform surface buoyancy reconstructions, even in places near freshwater inputs from river discharges, melting sea ice, and glaciers. Surface buoyancy fails due to the uncorrelation of SSB and subsurface potential vorticity (PV). Reconstruction from surface currents correlates to the total TOPAZ4 velocities with correlation coefficients greater than 0.6 up to 200 m. In the second part, we apply the SQG approach validated with the reanalysis outputs to satellite-derived sea level anomalies and validate the results against in-situ measurements. Due to lower water column stratification, the SQG approach’s performance is better in fall and winter than in spring and summer. Our results demonstrate that using surface information from SSH or surface velocities, combined with information on the stratification of the water column, it is possible to effectively reconstruct the upper ocean dynamics in the Arctic and Subarctic Seas up to 400 m. Future remote sensing missions in the Arctic Ocean, such as SWOT, Seastar, WaCM, CIMR, and CRISTAL, will produce enhanced SSH and surface velocity observations, allowing SQG schemes to characterize upper ocean 3D mesoscale dynamics up to 400 m with higher resolutions and lower uncertainties. Article in Journal/Newspaper Arctic Arctic Ocean Sea ice Subarctic Digital.CSIC (Spanish National Research Council) Arctic Arctic Ocean Remote Sensing 15 7 1722 |
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Open Polar |
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Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
unknown |
description |
This study assesses the capability of Surface Quasi-Geostrophy (SQG) to reconstruct the three-dimensional (3D) dynamics in four critical areas of the Arctic Ocean: the Nordic, Barents, East Siberian, and Beaufort Seas. We first reconstruct the upper ocean dynamics from TOPAZ4 reanalysis of sea surface height (SSH), surface buoyancy (SSB), and surface velocities (SSV) and validate the results with the geostrophic and total TOPAZ4 velocities. The reconstruction of upper ocean dynamics using SSH fields is in high agreement with the geostrophic velocities, with correlation coefficients greater than 0.8 for the upper 400 m. SSH reconstructions outperform surface buoyancy reconstructions, even in places near freshwater inputs from river discharges, melting sea ice, and glaciers. Surface buoyancy fails due to the uncorrelation of SSB and subsurface potential vorticity (PV). Reconstruction from surface currents correlates to the total TOPAZ4 velocities with correlation coefficients greater than 0.6 up to 200 m. In the second part, we apply the SQG approach validated with the reanalysis outputs to satellite-derived sea level anomalies and validate the results against in-situ measurements. Due to lower water column stratification, the SQG approach’s performance is better in fall and winter than in spring and summer. Our results demonstrate that using surface information from SSH or surface velocities, combined with information on the stratification of the water column, it is possible to effectively reconstruct the upper ocean dynamics in the Arctic and Subarctic Seas up to 400 m. Future remote sensing missions in the Arctic Ocean, such as SWOT, Seastar, WaCM, CIMR, and CRISTAL, will produce enhanced SSH and surface velocity observations, allowing SQG schemes to characterize upper ocean 3D mesoscale dynamics up to 400 m with higher resolutions and lower uncertainties. |
format |
Article in Journal/Newspaper |
author |
Umbert, Marta De-Andrés, Eva Gonçalves-Araujo, Rafael Gutiérrez, Marina Raj, Roshin Bertino, Laurent Gabarró, Carolina Isern-Fontanet, Jordi |
spellingShingle |
Umbert, Marta De-Andrés, Eva Gonçalves-Araujo, Rafael Gutiérrez, Marina Raj, Roshin Bertino, Laurent Gabarró, Carolina Isern-Fontanet, Jordi Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
author_facet |
Umbert, Marta De-Andrés, Eva Gonçalves-Araujo, Rafael Gutiérrez, Marina Raj, Roshin Bertino, Laurent Gabarró, Carolina Isern-Fontanet, Jordi |
author_sort |
Umbert, Marta |
title |
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
title_short |
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
title_full |
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
title_fullStr |
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
title_full_unstemmed |
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach |
title_sort |
surface and interior dynamics of arctic seas using surface quasi-geostrophic approach |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
http://hdl.handle.net/10261/308024 https://doi.org/10.3390/rs15071722 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Sea ice Subarctic |
genre_facet |
Arctic Arctic Ocean Sea ice Subarctic |
op_relation |
doi:10.3390/rs15071722 Remote Sensing 15 (7): 1722 (2023) http://hdl.handle.net/10261/308024 |
op_rights |
open |
op_doi |
https://doi.org/10.3390/rs15071722 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
7 |
container_start_page |
1722 |
_version_ |
1790596373965438976 |