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: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
Q
Online Access:https://doi.org/10.3390/rs15071722
https://doaj.org/article/fef01e4ed53948faa51f21b04f9b11a8
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spelling ftdoajarticles:oai:doaj.org/article:fef01e4ed53948faa51f21b04f9b11a8 2023-06-06T11:49:47+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 2023-03-01T00:00:00Z https://doi.org/10.3390/rs15071722 https://doaj.org/article/fef01e4ed53948faa51f21b04f9b11a8 EN eng MDPI AG https://www.mdpi.com/2072-4292/15/7/1722 https://doaj.org/toc/2072-4292 doi:10.3390/rs15071722 2072-4292 https://doaj.org/article/fef01e4ed53948faa51f21b04f9b11a8 Remote Sensing, Vol 15, Iss 1722, p 1722 (2023) ocean currents Arctic ocean dynamics Surface Quasi-Geostrophy sea surface height remote sensing Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15071722 2023-04-16T00:33:20Z 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 Directory of Open Access Journals: DOAJ Articles Arctic Arctic Ocean Remote Sensing 15 7 1722
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic ocean currents
Arctic
ocean dynamics
Surface Quasi-Geostrophy
sea surface height
remote sensing
Science
Q
spellingShingle ocean currents
Arctic
ocean dynamics
Surface Quasi-Geostrophy
sea surface height
remote sensing
Science
Q
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
Science
Q
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 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 MDPI AG
publishDate 2023
url https://doi.org/10.3390/rs15071722
https://doaj.org/article/fef01e4ed53948faa51f21b04f9b11a8
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, Vol 15, Iss 1722, p 1722 (2023)
op_relation https://www.mdpi.com/2072-4292/15/7/1722
https://doaj.org/toc/2072-4292
doi:10.3390/rs15071722
2072-4292
https://doaj.org/article/fef01e4ed53948faa51f21b04f9b11a8
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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