Conditional diffusion models for downscaling & bias correction of Earth system model precipitation

arXiv:2404.14416v1 Announce Type: cross
Abstract: Climate change exacerbates extreme weather events like heavy rainfall and flooding. As these events cause severe losses of property and lives, accurate high-resolution simulation of precipitation is imperative. However, existing Earth System Models (ESMs) struggle with resolving small-scale dynamics and suffer from biases, especially for extreme events. Traditional statistical bias correction and downscaling methods fall short in improving spatial structure, while recent deep learning methods lack controllability over the output and suffer from unstable training. …

abstract arxiv bias change climate climate change cs.ai cs.lg diffusion diffusion models dynamics earth events flooding however losses physics.ao-ph physics.geo-ph precipitation property rainfall resolution scale simulation small struggle type weather