Probabilistic recovery of high-impact urban convective rainfall from radar-assimilation experiments using conditional diffusion and distributional attribution
This study presents a hybrid forecasting framework that combines convection-permitting WRF simulations with 3DVAR radar assimilation and conditional diffusion postprocessing to substantially improve the probabilistic prediction of localized, high-impact convective rainfall over Baltimore, effectively correcting storm displacement errors and reducing forecast uncertainty despite the limitations of radar assimilation alone.