This research demonstrates how ECMWF ensemble forecasts predict uncertainties in extreme weather from Mediterranean cyclones, highlighting the probabilistic method and case studies.
Extratropical cyclones are the main cause of high-impact weather events in the Mediterranean such as heavy precipitation, floods, severe winds, and dust storms. However, the accuracy in predicting the timing, location, and intensity of such events is often insufficient, which is typically related to errors in cyclone position, propagation, and intensity. In this two-part study we use operational forecasts from the ECMWF ensemble prediction system to quantify uncertainties in predicting high-impact weather conditions linked to Mediterranean cyclones. We apply an object-based approach to attribute Mediterranean cyclones to events of extreme precipitation and surface winds. In this first part, we introduce the probabilistic method and three illustrative case studies of Mediterranean cyclones that occurred between November 2022 and September 2023, including the infamous Storm Daniel as well as Storms Denise and Jan. We find that the cyclones as well as their attributed objects of extreme surface weather are predicted well for lead times ≤48 h. However, for longer lead times there is large case-to-case variability in the ensemble performance. Predictions of extreme surface weather objects are found to be more uncertain (i) for smaller and less coherent objects, (ii) if the attributed cyclone is captured by fewer ensemble members, and (iii) during the earlier stage of the cyclones' lifecycle.
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Hartmuth et al. (2025) studied this question.
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