Loop Current System SSH and Subsurface Current Prediction with a Transfer Learning Approach

Description: Using 18 years of sea surface height (SSH) fields and sub-surface observations, this project will apply machine learning tools to predict Loop Current speed, vertical structure, and duration, to examine the eddy formation and shedding processes. The project aims to improve predictive capability of the location and duration of the Loop Current over a forecast period of one month; eddy shedding at two-three months; and predictive skill for Loop Current and Loop Current Eddy speed, vertical structure, and duration over a several day forecast.

Funding Cycle: Understanding Gulf Ocean Systems Grants 2
Funding Organization: National Academies of Science, Engineering, Medicine: Gulf Research Program

Forecasting 3D velocity structures of the Loop Current system in the Gulf of Mexico using a deep learning model