Publications

2025

1. 

   Continuous Ensemble Weather Forecasting with Diffusion models

   Martin Andrae, Tomas Landelius, Joel Oskarsson, and Fredrik Lindsten

   In The Thirteenth International Conference on Learning Representations, 2025

   Abs Bib PDF Blog Code Poster

   Weather forecasting has seen a shift in methods from numerical simulations to data-driven systems. While initial research in the area focused on deterministic forecasting, recent works have used diffusion models to produce skillful ensemble forecasts. These models are trained on a single forecasting step and rolled out autoregressively. However, they are computationally expensive and accumulate errors for high temporal resolution due to the many rollout steps. We address these limitations with Continuous Ensemble Forecasting, a novel and flexible method for sampling ensemble forecasts in diffusion models. The method can generate temporally consistent ensemble trajectories completely in parallel, with no autoregressive steps. Continuous Ensemble Forecasting can also be combined with autoregressive rollouts to yield forecasts at an arbitrary fine temporal resolution without sacrificing accuracy. We demonstrate that the method achieves competitive results for global weather forecasting with good probabilistic properties.

   @inproceedings{andrae2025continuous,
     title = {Continuous Ensemble Weather Forecasting with Diffusion models},
     author = {Andrae, Martin and Landelius, Tomas and Oskarsson, Joel and Lindsten, Fredrik},
     booktitle = {The Thirteenth International Conference on Learning Representations},
     year = {2025},
   }