For Earth observation forecasting, explicitly conditioning on weather anomalies and cumulative physical stress—rather than treating weather as generic conditioning—improves predictions of how vegetation responds to extreme weather events.
EO-WM is a video diffusion model for predicting future Earth surface conditions from satellite imagery while accounting for weather effects. Unlike existing methods, it explicitly models how weather forcing (heat, drought) drives changes in vegetation and other surface features, using separate conditioning pathways for baseline climate and weather anomalies.