Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
In order to improve climate projections, machine learning (ML)-based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid-scale processes or to accelerate computations by emulating existent parameterizations. These data-driven models have shown success in approximating subgrid-scale processes based on high-resolution storm-resolving simulations. However, …