Our goal is to uncover and capture the unaccounted physical processes at the air-sea-ice interface, which will reduce climate model biases, and improve climate projections
Our funder
This project is supported by Schmidt Futures, a philanthropic initiative founded by Eric and Wendy Schmidt that bets early on exceptional people making the world better, particularly through innovative breakthroughs in science and technology.
Our international team is based in the US and in France and includes scientists from New York University, Princeton, GFDL, Columbia, LDEO, NCAR, MIT, CNRS-IGE, and CNRS-IPSL.
Machine Learning
Our project will develop interpretable Machine Learning models to deepen our understanding of complex processes in the climate system.
Innovation
This innovative effort will leverage the availability of big data from high-resolution simulations, as well as data assimilation products (learning from model errors), with machine learning models to improve the representation of subgrid physics in the ocean, sea-ice and atmosphere components of existing climate models.