67 citations · 96 across the 5 of their papers we have counts for
3 papers · 1 filter
Reduced Cloud Cover Errors in a Hybrid AI-Climate Model Through Equation Discovery And Automatic Tuning
Arthur Grundner, Tom Beucler, Julien Savre +3
Cloud-related parameterizations remain a leading source of uncertainty in climate projections. Although machine learning holds promise for Earth system models (ESMs), many data-dri…
Data-Driven Equation Discovery of a Cloud Cover Parameterization
Arthur Grundner, Tom Beucler, Pierre Gentine +1
A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning-based parameterizations using output…
Deep Learning Based Cloud Cover Parameterization for ICON
Arthur Grundner, Tom Beucler, Pierre Gentine +3
A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm-reso…