• Corpus ID: 203593288

Machine-Learning Ocean Dynamics from Lagrangian Drifter Trajectories

  title={Machine-Learning Ocean Dynamics from Lagrangian Drifter Trajectories},
  author={Nikolas Olson Aksamit and Themistoklis P. Sapsis and George Haller},
  journal={arXiv: Dynamical Systems},
Lagrangian ocean drifters provide highly accurate approximations of ocean surface currents but are sparsely located across the globe. As drifters passively follow ocean currents, there is minimal control on where they will be making measurements, providing limited temporal coverage for a given region. Complementary Eulerian velocity data is available with global coverage, but is itself limited by the spatial and temporal resolution possible with satellite altimetry measurements. Additionally… 

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