| 29 Aug 2025
Quantifying forecast uncertainty of Mediterranean cyclone-related surface weather extremes in ECMWF ensemble forecasts. Part 1: Method and case studies
Abstract. 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.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Weather and Climate Dynamics.
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In their article, [Katharina Hartmuth et al.] present a novel method to assess the forecast skill of the ECMWF ensemble in predicting extreme weather events associated with Mediterranean cyclones. The first part of their study explains the methodology and illustrates it with three case studies of impactful Mediterranean cyclones. The forecast skill is evaluated based on the ability to predict the occurrence of extreme precipitation and extreme surface winds (both defined by exceedance of the local 99th percentile).
The paper is overall clear and well-structured. Particular attention has been given to the description of figures, which makes them especially pleasant to read. You will find attached some suggestions, mostly minor, that may help improve the paper.