Physically Constrained Generative Adversarial Networks for Improving Precipitation Fields from Earth System Models. (arXiv:2209.07568v1 [physics.ao-ph])

Precipitation results from complex processes across many scales, making its
accurate simulation in Earth system models (ESMs) challenging. Existing
post-processing methods can improve ESM simulations locally, but cannot correct
errors in modelled spatial patterns. Here we propose a framework based on
physically constrained generative adversarial networks (GANs) to improve local
distributions and spatial structure simultaneously. We apply our approach to
the computationally efficient ESM CM2Mc-LPJmL. Our method outperforms existing
ones in correcting local distributions, and leads to strongly improved spatial …

arxiv earth generative adversarial networks networks physics precipitation