Real-Time Validation of Operational Ocean Models Via Eddy-Decting Deep Neural Networks

Evangelos Moschos, Alexandre Stegner, Briac Le Vu, Olivier Schwander

Abstract: Surface currents provided, in real time, by operational ocean models often differ from each other but also from satellite altimetry observations, especially in terms of mesoscale dynamics. Eddies, which play a dominant role on circulation at the regional scale, have a signature on both altimetry maps and satellite imagery, such as sea surface temperature. Combining these independent signatures allows for a highly reliable detection of reference eddies. To this end, we build a convolutional neural network capable of detecting the contours of mesoscale eddies on SST maps in real time. Combined with a standard eddy detection algorithm applied to altimetry maps, we were able to locate and identify with high accuracy more than 900 eddies, in the Mediterranean Sea, over a period of 6 months, and use them as a reference for numerical model validation. We compare as a case study the performance of two operational models: MERCATOR and MFS.