| 17 Apr 2026
The Named Storms Catalogue: unlocking learnings from past events
Abstract. Extratropical cyclones are one of the leading causes of widespread damage from extreme weather over the United Kingdom and western Europe due to their strong winds and heavy precipitation. Storm naming has been used as a strategy to communicate risks and enhance preparedness of the general public and key affected sectors. Given the first ten seasons of storm naming, the opportunity arises to collect and characterise for the first time the set of named storms identified by the UK Storm Centre. Collecting information about these events enables to objectively assess what makes them different from other storms and from one another; and supports preparedness for future events.
This paper introduces the Named Storms Catalogue as an open-source dataset accessible from https://doi.org/10.5281/zenodo.18877013. The catalogue contains a set of storm tracks, storm development and hazard metrics that allow to objectively describe, rank and compare past named storm events, unlocking learning opportunities by the preparedness and resilience as well as the research communities.
This dataset introduction describes the content and metrics and the methodologies used to develop them, while a set of case studies highlights how the catalogue can be used to assess and compare past events. The paper presents a preliminary climatology for UK named storms and discusses some ongoing lines of research that the authors are exploring, such as using the metrics included in the catalogue to distinguish named events from others, and to identify different types of storms within the set.
Review of Earth System Science Data Discussion manuscript “The Named Storms Catalogue: unlocking learnings from past events” by Gonzalez et al.
This data description manuscript presents a new named storms dataset for the UK and western Europe. The dataset contains the tracks and development and intensity metrics of all named extratropical cyclones during the ten-year period from 2015/2016 to 2025/2026.
Several catalogues and databases of European windstorms already exist. However, these datasets often include only the most intense storms or do not systematically identify storms by their operational names, making it difficult to link individual events across different data sources and reports. Thus, the main novelty of the present dataset is that it provides a comprehensive collection of all officially named UK storms during the study period, together with consistent track and intensity information. As far as I am aware, such a dataset does not yet exist.
The manuscript was really clearly written and I enjoyed reading it. The structure of the paper was good, however, the authors could pay attention to the figures, especially their font sizes and the use of abbreviations (see comments below). Overall, I can still recommend publication of the paper. I have some relatively minor comments which I hope the authors can address before the publication.
Minor comments:
Line-to-line comments:
L46: Are all windstorms in the Western naming group named in advance based on forecasts, or are some named after impacts became evident? Have some storms been named retrospectively? A brief clarification of the naming procedure (and timing relative to forecast vs. observed impacts) would be useful here. For example, in Finland, a windstorm may sometimes be named once it is clear that it is causing significant impacts, sometimes on the same or even the next day it affects the country.
Section 2.1. I guess you used ERA5 in its native resolution (0.25°)? This is not mentioned.
Section 2.2. It was not fully clear from the text why there are two ocean datasets. Which one do you use e.g. in Fig. 12, and the figures in the database?
L71: Why did you track the systems with 6-hourly fields and not e.g. 3-hourly? 6-hourly data may be somewhat too coarse for representing local impacts, especially for fast-moving systems where the location and intensity of the strongest winds and precipitation can change substantially within six hours. Using 3-hourly fields could improve the representation of storm evolution by better resolving rapid deepening and the intensity peaks.
L98: Here you write that you calculated vorticity from wind components. But vorticity is available directly at pressure levels from ERA5. Why did you calculate the vorticity fields by yourselves?
L121: Vorticity maxima may not always be associated with MSLP minima, particularly during the early development stage of cyclones. Were such situations included in the tracking procedure, and how did you deal with them?
Table 1, bearing. I wasn’t sure about how this is calculated. Here you state “6h positions of maxima”. Which maxima?
L184: Surge residual is a new term for me. Can you explain it here a bit more?
L186: Section 0?
L216: “adding 6 hours on - 3 hours for each end of the track.” I can’t follow here, did you add 6 hours or 3 hours to the durations?
Table 2, Maximum wind gust. Is this the single highest ERA5 grid-point value within the storm footprint? Since peak gusts are often associated with mountainous / high-elevation regions, it would be useful to clarify whether these maxima are strongly influenced by high-elevation grid points.
Table 2, maximum wind gust. Your tracks are every 6 hours. Did you get the ERA5 wind gust data every 1 one hour to obtain the absolute maximum wind gust associated with the tracks, or are these just the instantaneous wind gusts from the 6-hourly wind gust fields? It was not entirely sure from L73 whether the wind gust data is hourly or not (it could be stated more explicitly).
L264: Full range may be misleading as it’s definitely not the physically possible “full range” due to small(ish) sample size. Maybe just the widest range?
Figure 6, 7 and others: There is no unit in the y-axis. Also, could the titles be explicitly written, without the abbreviations, in order to ease the interpretation (and with bigger size). The abbreviations may be clear for the authors that have used them for a long time, but not for a regular reader who reads the paper for the first time.
L281: What do you mean by “corrections to account for changes in the background climate”? Do you mean that the storms in 2015 occurred in a colder climate than the storms in 2025, and this may have an impact on the hazard metrics? The effect is probably very small, given the short 10-year period involved (~0.2 °C of global warming) and the relatively limited response of extratropical cyclones to warming.
L282: I think it’s interesting that DJF season has lots of named storms with close to zero hazard metrics (Fig. 7a–c), while this is clearly not the case for JJA. Does this imply that named JJA storms have a higher probability to cause damage? One possible explanation is that winter storms are more often named based on forecast intensity and anticipated impacts, even if their hazard metrics remain modest because strong winds are more common in winter climatology. This also seems somewhat inconsistent with the Introduction statement that naming is primarily based on impacts (L46-47), so a short discussion of this could be useful.
Figure 8. As commented earlier, the abbreviations could be written open. Particularly in the caption of the figure.
L375: Citation comes before the dot.
L387-388: Volonte et al. 2024 is missing from the reference list. How about the ERA5 resolution? Can that be one reason for the underestimation of the severity?
Conclusions. Are you planning to update the dataset in the future? If yes, this could be mentioned here.