ITS4.4/AS4.1

EDI
Co-organized by CL5.2/ESSI1/NP4
Convener: Julien Brajard | Co-conveners: Peter Düben, Redouane Lguensat, Francine SchevenhovenECSECS, Maike SonnewaldECSECS

There are many ways in which machine learning promises to provide insight into the Earth System, and this area of research is developing at a breathtaking pace.
Unsupervised, supervised as well as reinforcement learning are now increasingly used to address Earth system related challenges.
Machine learning could help extract information from numerous Earth System data, such as satellite observations, as well as improve model fidelity through novel parameterisations or speed-ups. This session invites submissions spanning modelling and observational approaches towards providing an overview of the state-of-the-art of the application of these novel methods