Speaker: Packard Chan
We are glad to have Packard to discuss machine learning in climate models. Please see the attached paper (link).
During he discussion, Packard will introduce the following points:
1. Deep learning can represent subgrid processes in climate models.
2. The prognostic multiyear simulations are stable and closely reproduce mean climate and variabilities.
3. Generalization works in some cases but fails the others.