Physics-Constrained Adaptive Flow Matching for Climate Downscaling

ArXi:2604.03459v1 Announce Type: cross Regional climate information at kilometer scales is essential for assessing the impacts of climate change, but generating it with global climate models is too expensive due to their high computational costs. Machine learning models offer a fast alternative, yet they often violate basic physical laws and degrade when applied to climates outside of their