CoAuthors

Antoine Delepoulle (CLS, France); Clément Busché (CLS, France); Rosemary Morrow (LEGOS, France); Yannice Faugère (CLS, France); Gerald Dibarboure (CNES, France)

Mesoscale eddies are ubiquitous structures in the ocean. As mesoscale eddies can trap and transport water within their cores over long distances, they have been investigated globally since the availability of altimetry maps. Mesoscale eddies are first detected in the sea surface, and then tracked in time and space. Several methods of detection and tracking have been developed, most of them propose to describe the evolution of mesoscale eddies with an association in individual trajectories, with a beginning and an end. Few methods are able to take into account the interactions between trajectories, and when merging and splitting events are recorded, it is necessary to change the semantics and the metrics to describe the behaviour of mesoscale eddies. Here we present a new mesoscale eddies dataset, where the structures are gathered in networks. Eddies are detected on daily absolute topography maps with the Py-Eddy-Tracker algorithm (PET, Mason et al., 2014, https://github.com/AntSimi/py-eddy-tracker). Following Pegliasco et al. (2015), successive eddies with overlapping contours are associated in the same network if the overlap ratio, defined as the intersection of their area divided by the union of their areas, is more than 5 %. Within networks, segments represent the temporal evolution of individual eddies and nodes between segments correspond to merging or splitting events. Segments are what was previously called trajectories, but the individuality (no interactions) is not assumed. During merging and splitting events, more than two eddies present an overlap. The highest overlap ratio is used to determine which segment stops in a merging event and which segment starts in a splitting event. We developed simple functions to manipulate and visualize this new type of dataset.
To assess the networks’ coherence, we use a lagrangian perspective. A coherence level is obtained by advecting for 14 days particles injected within the eddy’s contours of maximum averaged speed, both backward and forward in time, with the surface currents derived from absolute dynamic topography. At the end of the advection, the number of particles still within the eddy’s contours is normalized by the initial number of particles. A coherence level is associated to each segment and each interaction and can be used for selection by the users.
The META-Networks (Mesoscale Eddy Trajectories Atlas – Networks) can be used for any interdisciplinary research topic, for example by coupling the mesoscale eddies’ contours with in situ data, or describe the displacement of tracers along eddies’ paths, at a regional or global scale.