Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) and its application to coastal eddy formation

Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) and its application to coastal... AbstractAutomated methods are important for the identification of mesoscale eddies in the large volume of oceanic data provided by altimetric measurements or numerical simulations. This paper presents an optimized algorithm for the detection and tracking of eddies from two-dimensional velocity fields. This eddy identification uses a hybrid methodology based on physical parameters and geometrical properties of the velocity field and can be applied to various fields having different spatial resolutions without a specific fine tuning of the parameters. The efficiency and the robustness of the Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) was tested with three different types of input data: the 1/8° Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) geostrophic velocity fields available for the Mediterranean Sea, the output of idealized Regional Ocean Modeling System numerical model and the surface velocity field obtained from particle imagery on a rotating tank experiment. All these data sets describe the dynamical evolution of mesoscale eddies generated by the instability of a coastal current. The main advantages of AMEDA are the followings: the algorithm is robust to the grid resolution, it uses a minimal number of tunable parameters, the dynamical features of the detected eddies are quantified and the tracking procedure identifies the merging and the splitting events. The proposed method provides a complete dynamical evolution of the detected eddies during their lifetime. This allows to identify precisely the formation areas of long-lived eddies, the region where eddy splitting or merging occurs frequently and the interaction between eddies and oceanic currents. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) and its application to coastal eddy formation

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
D.O.I.
10.1175/JTECH-D-17-0010.1
Publisher site
See Article on Publisher Site

Abstract

AbstractAutomated methods are important for the identification of mesoscale eddies in the large volume of oceanic data provided by altimetric measurements or numerical simulations. This paper presents an optimized algorithm for the detection and tracking of eddies from two-dimensional velocity fields. This eddy identification uses a hybrid methodology based on physical parameters and geometrical properties of the velocity field and can be applied to various fields having different spatial resolutions without a specific fine tuning of the parameters. The efficiency and the robustness of the Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) was tested with three different types of input data: the 1/8° Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) geostrophic velocity fields available for the Mediterranean Sea, the output of idealized Regional Ocean Modeling System numerical model and the surface velocity field obtained from particle imagery on a rotating tank experiment. All these data sets describe the dynamical evolution of mesoscale eddies generated by the instability of a coastal current. The main advantages of AMEDA are the followings: the algorithm is robust to the grid resolution, it uses a minimal number of tunable parameters, the dynamical features of the detected eddies are quantified and the tracking procedure identifies the merging and the splitting events. The proposed method provides a complete dynamical evolution of the detected eddies during their lifetime. This allows to identify precisely the formation areas of long-lived eddies, the region where eddy splitting or merging occurs frequently and the interaction between eddies and oceanic currents.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Dec 26, 2017

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