Krouma et al. (2026) Ensemble forecasts of isolated and compound wind and precipitation extremes in Europe using HC-SWG (v3.1) and MA-SWG (v1.1) Stochastic Weather Generators

Identification

• Journal: Geoscientific model development
• Year: 2026
• Date: 2026-07-23
• Authors: Meriem Krouma, Gabriele Messori
• DOI: 10.5194/gmd-19-6663-2026

Research Groups

• Department of Earth Sciences, Uppsala University
• Swedish Centre for Impacts of Climate Extremes (climes), Uppsala University
• Department of Meteorology, Stockholm University

Short Summary

This study presents two forecasting approaches that combine a stochastic weather generator with atmospheric circulation analogs to forecast extreme precipitation and wind speed in Europe. The first approach, HC-SWG, combines ECMWF ensemble reforecasts with the stochastic weather generator to forecast extreme precipitation at different locations in Europe. The second approach, MA-SWG, uses multivariate atmospheric analogs as input to the SWG to forecast extreme 10 m wind speed.

Objective

• Investigate the ability of a stochastic weather generator (SWG) combined with atmospheric circulation analogs to forecast extreme precipitation and wind speed events in Europe.
• Evaluate the performance of two different forecasting approaches: HC-SWG for extreme precipitation and MA-SWG for extreme wind speed.

Study Configuration

• Spatial Scale: Continental scale, focusing on Europe.
• Temporal Scale: Medium-range forecasts (1 to 10 days).

Methodology and Data

• Models used: Stochastic Weather Generator (SWG), ECMWF ensemble reforecasts, ERA5 reanalysis data.
• Data sources: European Climate Assessment and Data (ECA&D) project, ERA5 reanalysis data.

Main Results

• The HC-SWG approach outperforms ECMWF forecasts for extreme precipitation at all lead times considered.
• The MA-SWG approach captures the temporal occurrence of extreme wind speed events but tends to overestimate their magnitude.
• The reliability of the MA-SWG forecasts decreases with forecast lead time and is more station-dependent for the strongest events.

Contributions

• This study provides a new approach to forecasting extreme precipitation and wind speed events using a stochastic weather generator combined with atmospheric circulation analogs.
• The results demonstrate the added value of incorporating a stochastic approach like HC-SWG in ensemble forecast spread and better capturing precipitation extremes.

Funding

• Swedish Research Council (VR)
• European Union's Horizon 2020 research and innovation program (grant agreement No. [insert grant number])
• Other funding sources: [insert other funding sources]

Citation

@article{Krouma2026Ensemble,
  author = {Krouma, Meriem and Messori, Gabriele},
  title = {Ensemble forecasts of isolated and compound wind and precipitation extremes in Europe using HC-SWG (v3.1) and MA-SWG (v1.1) Stochastic Weather Generators},
  journal = {Geoscientific model development},
  year = {2026},
  doi = {10.5194/gmd-19-6663-2026},
  url = {https://doi.org/10.5194/gmd-19-6663-2026}
}