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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Published in:Remote Sensing
Main Authors: Marta Umbert, Eva De-Andrés, Rafael Gonçalves-Araujo, Marina Gutiérrez, Roshin Raj, Laurent Bertino, Carolina Gabarró, Jordi Isern-Fontanet
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2023
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Online Access:https://doi.org/10.3390/rs15071722
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spelling ftmdpi:oai:mdpi.com:/2072-4292/15/7/1722/ 2023-08-20T04:03:51+02:00 Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach Marta Umbert Eva De-Andrés Rafael Gonçalves-Araujo Marina Gutiérrez Roshin Raj Laurent Bertino Carolina Gabarró Jordi Isern-Fontanet agris 2023-03-23 application/pdf https://doi.org/10.3390/rs15071722 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs15071722 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 15; Issue 7; Pages: 1722 ocean currents Arctic ocean dynamics Surface Quasi-Geostrophy sea surface height remote sensing physical oceanography Text 2023 ftmdpi https://doi.org/10.3390/rs15071722 2023-08-01T09:23:52Z 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. Text Arctic Arctic Ocean Sea ice Subarctic MDPI Open Access Publishing Arctic Arctic Ocean Remote Sensing 15 7 1722
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic ocean currents
Arctic
ocean dynamics
Surface Quasi-Geostrophy
sea surface height
remote sensing
physical oceanography
spellingShingle ocean currents
Arctic
ocean dynamics
Surface Quasi-Geostrophy
sea surface height
remote sensing
physical oceanography
Marta Umbert
Eva De-Andrés
Rafael Gonçalves-Araujo
Marina Gutiérrez
Roshin Raj
Laurent Bertino
Carolina Gabarró
Jordi Isern-Fontanet
Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach
topic_facet ocean currents
Arctic
ocean dynamics
Surface Quasi-Geostrophy
sea surface height
remote sensing
physical oceanography
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 Text
author Marta Umbert
Eva De-Andrés
Rafael Gonçalves-Araujo
Marina Gutiérrez
Roshin Raj
Laurent Bertino
Carolina Gabarró
Jordi Isern-Fontanet
author_facet Marta Umbert
Eva De-Andrés
Rafael Gonçalves-Araujo
Marina Gutiérrez
Roshin Raj
Laurent Bertino
Carolina Gabarró
Jordi Isern-Fontanet
author_sort Marta Umbert
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 https://doi.org/10.3390/rs15071722
op_coverage agris
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_source Remote Sensing; Volume 15; Issue 7; Pages: 1722
op_relation Ocean Remote Sensing
https://dx.doi.org/10.3390/rs15071722
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs15071722
container_title Remote Sensing
container_volume 15
container_issue 7
container_start_page 1722
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