About Us

M²LInES (pronounced M-square-lines) mission is to improve coupled climate models by reimagining physics model development through innovative use of data and AI. We aim to accelerate the pace of climate model development by learning physics from data with scientific machine learning, and ultimately enhance climate model fidelity and reliability for future projections.

Our funder

This project is supported by Schmidt Sciences, LLC, a philanthropy dedicated to fostering the advancement of science and technology. Read more in our press release

International team

Our project comprises ocean, atmosphere, sea-ice scientists, numerical model developers, and machine learning experts. Our collaboration spans 2 continents, 7 academic institutions, and 3 numerical climate modeling centers.

Machine Learning

Our project leads the developement of machine learning models for climate physics, and ultimately of interpretable data-driven models to deepen our understanding of complex multiscale processes in the climate system.

Innovation

This innovative effort leverages the availability of big data from high-resolution simulations, as well as data assimilation products (combining models and observations), with powerful machine learning algorithms to improve the representation of subgrid physics in the ocean, sea-ice and atmosphere components of existing climate models.

Code of conduct

You will find our code of conduct here

Code of Conduct