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

Abstract. Ensemble forecasts of extreme wind and precipitation provide essential information for early warning systems. In this study, we present two forecasting approaches that combine a stochastic weather generator (SWG) with atmospheric circulation analogs to forecast extreme precipitation and extreme wind speed in Europe. The first approach, which we term HC-SWG, combines ECMWF ensemble reforecasts with the stochastic weather generator to forecast extreme precipitation at different locations in Europe. The second approach, which we term MA-SWG, uses multivariate atmospheric analogs as input to the SWG to forecast extreme 10 m wind speed. These ensemble forecasts of precipitation and wind speed extremes display a higher forecast skill than ECMWF numerical reforecasts at lead times up to 10 d, using station data as the ground truth. As a final step, we evaluate the forecasted and observed frequencies of simultaneous and sequential precipitation and wind speed extremes in Europe, which are a class of high-impact compound events. Our forecasts yield comparable occurrence frequencies to the observations.

Authors

Institutions

Publication Details

Journal
Geoscientific model development
Published
2026-07-23
DOI
https://doi.org/10.5194/gmd-19-6663-2026
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Meriem Krouma, Gabriele Messori
Geoscientific model development
Meteorological Phenomena and Simulations
article

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

Meriem Krouma, Gabriele Messori
article en

Abstract

Abstract. Ensemble forecasts of extreme wind and precipitation provide essential information for early warning systems. In this study, we present two forecasting approaches that combine a stochastic weather generator (SWG) with atmospheric circulation analogs to forecast extreme precipitation and extreme wind speed in Europe. The first approach, which we term HC-SWG, combines ECMWF ensemble reforecasts with the stochastic weather generator to forecast extreme precipitation at different locations in Europe. The second approach, which we term MA-SWG, uses multivariate atmospheric analogs as input to the SWG to forecast extreme 10 m wind speed. These ensemble forecasts of precipitation and wind speed extremes display a higher forecast skill than ECMWF numerical reforecasts at lead times up to 10 d, using station data as the ground truth. As a final step, we evaluate the forecasted and observed frequencies of simultaneous and sequential precipitation and wind speed extremes in Europe, which are a class of high-impact compound events. Our forecasts yield comparable occurrence frequencies to the observations.

Geoscientific model developmentVol. 19(14)
Uppsala University (SE), Stockholm University (SE), Bolin Centre for Climate Research (SE)
European Commission, Svenska Forskningsrådet Formas, Vetenskapsrådet, Horizon 2020 Framework Programme, H2020 Excellent Science
Openalex Percentile: Top 98%
Meteorological Phenomena and Simulations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

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 — Meriem Krouma, Gabriele Messori · Geoscientific model development (2026) | TGRS Research Map | TGRS