Abstract:Using a probabilistic neural network and Lagrangian observations from the Global Drifter Program, we model the single particle transition probability density function (pdf) of ocean surface drifters. The transition pdf is represented by a Gaussian mixture whose parameters (weights, means, and covariances) are continuous functions of latitude and longitude determined to maximize the likelihood of observed drifter trajectories. This provides a comprehensive description of drifter dynamics allowing for the simula… Show more
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