Research On Eddy Lagrangian Visualization In South China Sea

Deep learning has recently made a great progress on semantic segmentation?In this paper,we applied the state-of-the-art model,Pyramid Scene Parsing Network and Pointwise Spatial Attention Network,to oceanic eddies detection,and assess their performance for a real eddy dataset of the South China Sea.In previous studies,Lagrangian analyses were used to assess large-scale ocean circulation,and the Lagrangian coherent structure could also reveal the evolution of the two-dimensional structure of the mesoscale eddies.However,few studies have demonstrated the three-dimensional structure of the mesoscale eddies via Lagrangian analysis.Compared with previous studies,which investigated the eddy structure via a Eulerian view,we used a Lagrangian view to provide a different perspective to study the eddy structure.As a significant phenomenon in the South China Sea,the dipole structure of the anticyclonic eddy(AE)/cyclonic eddy(CE)pair off of central Vietnam has been well studied but mainly at the sea surface.With a Lagrangian analysis,we illustrate the threedimensional structure of the eddy pair.More importantly,we found that there was no fluid exchange between the two eddies since the strong boundary jet separates them from each other.All the conclusions above have been verified and are supported by the computational error estimate.With a selected time step and integral period,the computational errors always present small values,although they increase with strong divergent and vertical diffusive flow.