SwinVRNN: A Data‐Driven Ensemble Forecasting Model via Learned Distribution Perturbation
SwinVRNN: A Data‐Driven Ensemble Forecasting Model via Learned Distribution Perturbation
Abstract The data‐driven approaches for medium‐range weather forecasting are recently shown to be extraordinarily promising for ensemble forecasting due to their fast inference speed compared to the traditional numerical weather prediction models. However, their forecast accuracy can hardly match the state‐of‐the‐art operational ECMWF Integrated Forecasting System (IFS) model. Previous data‐driven …