AI RESEARCH

Guided Diffusion Sampling for Precipitation Forecast Interventions

arXiv CS.LG

ArXi:2605.14317v1 Announce Type: new Extreme precipitation causes severe societal and economic damage, and weather control has long been discussed as a potential mitigation strategy. However, to the best of our knowledge, perturbation-based interventions for weather control using data-driven weather forecasting models have not yet been explored. While adversarial attacks also generate perturbations that alter forecasts, they aim to exploit model artifacts and do not account for physical plausibility.