Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach

Umbert Ceresuela, Marta ORCID: https://orcid.org/0000-0002-0748-7566, Andres Marruedo, Eva de ORCID: https://orcid.org/0000-0001-7053-3943, Gonçalves Araujo, Rafael ORCID: https://orcid.org/0000-0001-8344-8326, Gutiérrez García, Marina ORCID: https://orcid.org/0009-0000-5809-9048, Raj, Roshin P. ORCID: https://orcid.org/0000-0001-5863-5269, Bertino, Laurent ORCID: https://orcid.org/0000-0002-1220-7207, Gabarró Prats, Carolina ORCID: https://orcid.org/0000-0003-0004-1964 and Isern Fontanet, Jordi ORCID: https://orcid.org/0000-0002-9324-608X (2023). Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach. "Remote Sensing", v. 15 (n. 7); p. 1722. ISSN 20724292. https://doi.org/10.3390/rs15071722.

Descripción

Título: Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Remote Sensing
Fecha: 1 Abril 2023
ISSN: 20724292
Volumen: 15
Número: 7
Materias:
ODS:
Palabras Clave Informales: ALTIMETRY; Arctic; FRAM STRAIT; ice; NORDIC SEAS; ocean dynamics; physical oceanography; Reconstruction; remote sensing; ROSSBY RADIUS; Salinity; sea surface height; Surface Quasi-Geostrophy; TEMPERATURE; Variability; Arctic; OCEAN CIRCULATION; ocean currents; Ocean dynamics; physical oceanography; Remote Sensing; Sea Surface Height; Surface Quasi-Geostrophy
Escuela: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Departamento: Matemática Aplicada
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Horizonte 2020
840374
DYNACLIM
Umbert Ceresuela, Marta
Marie Skłodowska-Curie Actions. Ocean DYNAmics reconstruction using remotely sensed variables in two CLIMate hotspots
Universidad Politécnica de Madrid
UP2021-035
Sin especificar
Andres Marruedo, Eva de
Ayudas Margarita Salas para la formación de jóvenes doctores
Gobierno de España
2021-125324OB-I00
ARTIC-MON
Carolina Gabarró y Pedro Elosegui
Advances in monitoring sea ice thickness and snow depth, ocean dynamics, and freshwater content in the Arctic using remote sensing data
Gobierno de España
CEX2019-000928-S
Sin especificar
INSTITUTO DE CIENCIAS DEL MAR (ICM)
Sin especificar

Más información

ID de Registro: 81867
Identificador DC: https://oa.upm.es/81867/
Identificador OAI: oai:oa.upm.es:81867
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/10039145
Identificador DOI: 10.3390/rs15071722
URL Oficial: https://www.mdpi.com/2072-4292/15/7/1722
Depositado por: iMarina Portal Científico
Depositado el: 28 Jun 2024 11:50
Ultima Modificación: 28 Jun 2024 11:51