Stephan Rasp (Climate AI): Hybrid machine learning-physics climate modeling: challenges and potential solutions
Zoom link: https://cwi-nl.zoom.us/j/9201774084?pwd=OFBqM1dUenFreGdPUWEwZFYvMlJ6UT09
Climate models still exhibit large structural errors caused by uncertainties in the representation of sub-grid processes. The recent availability of short-term high-resolution simulations motived the development of machine learning-based sub-grid schemes. Such hybrid models have been shown to have the potential to improve the representation of processes such as convection and radiation but fundamental problems remain, in particular instabilities and model drifts. In this talk I will discuss some potential solutions to the key issues facing hybrid modeling.
