M²LInES
Talks and videos from the team members of M²LInES.
M²LInES is a large 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.
More info at: m2lines.github.io
AGU Fall 2022 - Laure Zanna - Benchmarking Machine Learning Parametrizations
Janni Yuval-Neural-network parameterization of subgrid momentum transport learned from HR simulation
Ryan Abernathey - Pangeo An Open Source Ecosystem for Data Intensive Science
Julien Le Sommer -Why and how to learn end to end subgrid closures for atmosphere and ocean models
Dhruv Balwada - AMS100
OceanCloud: Transforming oceanography with a new approach to data and computing
OpenOceanCloud @ Ocean Data Conference
OSM22 - Brandon Reichl
OSM22 - Mitch Bushuk
OSM22 - Dhruv Balwada - Gliders Tracers
OSM22 - Dhruv Balwada - Energy fluxes
OSM22 - Aakash Sane
OSM22 - Lorenzo Zampieri