Machine Learning-Based Causally Informed Atmospheric Parametrizations for Climate Models
Machine Learning-Based Causally Informed Atmospheric Parametrizations for Climate Models
Veronika Eyring1,2, Arthur Grundner1, Fernando Iglesias-Suarez1, Tom Beucler3, Pierre Gentine4, Giorgetta A. Marco5, Mike S Pritchard6, Jakob Runge7 and Mierk Schwabe1, (1)German Aerospace Center DLR Oberpfaffenhofen, Institute of Atmospheric Physics, Oberpfaffenhofen, Germany, (2)University of Bremen, Institute of Environmental Physics, Bremen, Germany, (3)University of Lausanne, Institute of Earth Surface Dynamics, Lausanne, Switzerland, (4)Columbia University, Department of Earth and Environmental Engineering, New York, NY, United States, (5)Max Planck Institute for Meteorology, Hamburg, Germany, (6)University California Irvine, Earth System Science, Irvine, United States, (7)German Aerospace Center DLR Jena, Institute of Data Science, Jena, Germany