climate-ml

Researchers from KAIST, Kookmin University, and NYU propose a proper scoring rule-based diffusion framework for probabilistic weather forecasting that adds auxiliary conditional denoising tasks to CRPS-trained models, enabling improved forecast accuracy and calibration at longer horizons while keeping single-forward-pass ensemble generation.