AI and the World's Hard Problems · Earth & climate science · Nature Machine Intelligence · 2026-09-28
Regional climate risk assessment from climate models using probabilistic machine learning
Climate models are too coarse for regional risk decisions, and existing downscaling methods are too costly for large ensembles, miss multivariate dependencies, or need time-aligned training pairs that free-running projections lack. GenFocal is a generative AI framework that produces statistically accurate fine-scale weather from coarse projections without paired training data. It synthesises long-lived hazards such as heatwaves and tropical cyclones, samples rare high-impact events more accurately than leading methods, and improves regional estimates of compound extremes.