Deep Learning

AGU2019: Convolutional Neural Networks for Estimating Atmospherically-forced Sea Level Variations

The variability of sea-level anomalies (SLA) observed by satellite altimeters combines two components: a forced component paced by the atmospheric variability, and an intrinsic and chaotic component emerging from the ocean itself.

OST/ST2019: Attenuating the ocean chaotic variability in altimetric observations: from band-pass filtering to machine learning

The variability of sea-level anomalies (SLA) observed by satellite altimeters combines two components: a forced component paced by the atmospheric variability, and an intrinsic and chaotic component emerging from the ocean itself.