M²LInES - Multiscale Machine Learning In Coupled Earth System Modeling

M²LInES (pronounced M-square-lines) is an international collaborative project with the goal of improving climate projections, using scientific and interpretable Machine Learning to capture unaccounted physical processes at the air-sea-ice interface.

About us

Learn more about our project.

More about us

Our Research

Deepening our understanding of key climate processes, such as ocean mixing, clouds, convection, using data

Developing new physics-aware multiscale machine learning tools for accelerating climate science discovery

Improving coupled climate models from leading modeling centers (NCAR, GFDL, and IPSL).

Our Team

Our international team of dedicated researchers has expertise in Climate Science, Machine Learning and Numerical Modeling.

Meet the team

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