Inductive biases in deep learning models for weather prediction

arXiv:2304.04664v2 Announce Type: replace-cross
Abstract: Deep learning has gained immense popularity in the Earth sciences as it enables us to formulate purely data-driven models of complex Earth system processes. Deep learning-based weather prediction (DLWP) models have made significant progress in the last few years, achieving forecast skills comparable to established numerical weather prediction models with comparatively lesser computational costs. In order to train accurate, reliable, and tractable DLWP models with several millions of parameters, the model design needs to incorporate …

abstract arxiv biases cs.lg data data-driven deep learning earth earth sciences forecast inductive numerical physics.ao-ph prediction processes progress skills type weather weather prediction