Artículo
Detection and characterization of submesoscale eddies from optical images: a case study in the Argentine continental shelf
Fecha de publicación:
05/2023
Editorial:
Taylor & Francis Ltd
Revista:
International Journal of Remote Sensing
ISSN:
0143-1161
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Eddies are structures of recognized physical and biogeochemical relevance. Because of their small space and time scales, submesoscale eddy detection is a challenge, and detection methods for these structures are scarce. In this study, we detect submesoscale eddies (SME) by means of a method implemented on satellite chlorophyll-a (CSAT) and sea surface temperature (SST) data from Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. The performance of this method is shown through the characterization of the shape and size of the detected eddies. The trajectory and characteristics of one particular eddy could be observed for 6 days over the Argentine continental shelf. The eddy reached the highest CSAT concentration (1.52 mg m−3, decreasing to less than 0.8 mg m−3 in about 3.5 km), and the lowest SST on the same day it developed its largest size. All SME detected within the study period are in agreement with cyclonic eddies and have a radius smaller than the baroclinic Rossby radius of deformation. This paper presents a workflow for the automated recognition of SME that could be applied to other regions with similar characteristics, or different ones with previous changes in the parameters.
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Articulos(CESIMAR)
Articulos de CENTRO PARA EL ESTUDIO DE SISTEMAS MARINOS
Articulos de CENTRO PARA EL ESTUDIO DE SISTEMAS MARINOS
Articulos(SEDE CENTRAL)
Articulos de SEDE CENTRAL
Articulos de SEDE CENTRAL
Citación
Becker, Fernando; Romero, Silvia Inés; Pisoni, Juan Pablo; Detection and characterization of submesoscale eddies from optical images: a case study in the Argentine continental shelf; Taylor & Francis Ltd; International Journal of Remote Sensing; 44; 10; 5-2023; 3146-3159
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