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Filtering tide-generated internal waves using Convolutional Neural Networks

Thanks to recent developments in ocean numerical simulation, we can now have access to a considerable amount of simulation data with exceptional high spatial resolutions up to 1/60° and hourly temporal resolution. Here, we benefit from an advanced North Atlantic simulation of the ocean circulation (eNATL60) that models tidal motions, and design a supervised machine learning experiment that aims to test several techniques for filtering IGWs.