Quasi-Objective Eddy Visualization from Sparse Drifter Data
Alex Pablo Encinas Bartos, Nikolas Aksamit, George Haller
Abstract
Open-access reader
Alex Pablo Encinas Bartos, Nikolas Aksamit, George Haller
Abstract
Open-access reader
Lagrangian eddies, generally referred to as elliptic Lagrangian coherent structures (LCS) in the dynamical systems literature, are material objects that trap and transport floating particles over large distances in the ocean in a coherent fashion. In order to expand our understanding of the transport of marine tracers, we need to accurately and reliably track the evolution of vortical flow structures. Drifter trajectories represent a valuable but sparse source of information for this purpose. We employ a recently developed single-trajectory Lagrangian diagnostic tool, the trajectory rotation average (TRA), to visualize oceanic vortices (or eddies) from sparse drifter data in a quasi-objective fashion. We apply the TRA to two drifter data sets that cover various oceanographic scales: the Grand Lagrangian Deployment (GLAD) and the Global Drifter Program (GDP). Based on the TRA, we develop a general algorithm that extracts approximate eddy boundaries. We find that the TRA outperforms other available single-trajectory-based eddy detection methodologies on sparse drifter data and identifies eddies on scales that are unresolved by satellite-altimetry.
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Lagrangian eddies, generally referred to as elliptic Lagrangian coherent structures (LCS) in the dynamical systems literature, are material objects that trap and transport floating particles over large distances in the ocean in a coherent fashion. In order to expand our understanding of the transport of marine tracers, we need to accurately and reliably track the evolution of vortical flow structures. Drifter trajectories represent a valuable but sparse source of information for this purpose. We employ a recently developed single-trajectory Lagrangian diagnostic tool, the trajectory rotation average (TRA), to visualize oceanic vortices (or eddies) from sparse drifter data in a quasi-objective fashion. We apply the TRA to two drifter data sets that cover various oceanographic scales: the Grand Lagrangian Deployment (GLAD) and the Global Drifter Program (GDP). Based on the TRA, we develop a general algorithm that extracts approximate eddy boundaries. We find that the TRA outperforms other available single-trajectory-based eddy detection methodologies on sparse drifter data and identifies eddies on scales that are unresolved by satellite-altimetry.
Key concepts: Drifter, Trajectory, Eddy, Lagrangian, Geology, Meteorology, Geodesy, Computer science