An Automated Approach to Detect Oceanic Eddies From Satellite Remotely Sensed Sea Surface Temperature Data

Cyclonic (anticyclonic) oceanic eddies drive local upwelling (downwelling), leaving footprints in the sea surface temperature (SST) field as local extremes. Satellite-measured SST images can therefore be used to obtain information of the characteristics of oceanic eddies. Remotely sensed measurements represent very large data sets, both spatially and temporally. Manual eddy detection and analysis are thus practically impossible. In this letter, an automated scheme for eddy detection from remote sensing SST data is presented. The method is based on the analysis of velocity fields derived from SST measurements (thermal-wind velocity field). Using the geometric features of the velocity field, we can identify positions of eddy centers and derive eddy size, intensity, path, and lifetime. The scheme is applied to a realistic remotely sensed SST data set in a strong eddy activity region: Kuroshio Extension region.

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Source ISSN: 1545-598X
Author Dong, Changming, Nencioli, Francesco, Liu, Yu, Mcwilliams, James C.
Maintainer CCSD
Last Updated May 17, 2026, 20:50 (UTC)
Created May 17, 2026, 20:50 (UTC)
Identifier hal-00699640
Language en
contributor Laboratoire d'océanographie et de biogéochimie (LOB) ; Université de la Méditerranée - Aix-Marseille 2-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
creator Dong, Changming
date 2011-05-17T00:00:00
harvest_object_id 25705019-51f7-4cb9-b5c3-6756b651a212
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2024-12-02T00:00:00
relation info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2011.2155029
set_spec type:ART