the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying controls of extratropical cyclone intensity at genesis time and during intensification in the North Atlantic and Europe
Abstract. Extratropical cyclones (ETCs) are an important part of the atmospheric circulation, cause most of the day-to-day weather variability, and have societal impacts through strong winds and heavy precipitation in the mid-latitudes. Therefore, from both weather forecasting and climate change perspectives it is crucial to understand how they develop and intensify. In this study we aim to identify which environmental background conditions, here called ETC precursors, have the most control on the intensity of ETCs in the North Atlantic and Europe in the cold season. We apply an ensemble-based statistical method with ERA5 reanalysis data to associate climatologically typical perturbations in multiple ETC precursor fields at genesis time to distributions of five ETC intensity measures at time of maximum ETC intensity. We find that higher ETC wind intensity is associated with a stronger jet stream, especially downstream of the ETC centre, and increased meridional temperature gradients, with an emphasis on warmer upper levels south of the ETC centre. Precipitation is controlled by temperature and moisture throughout the tropospheric column, with higher values associated with more precipitation. We perform the same analysis for four groups of ETCs with different average intensities and show that while differences exist in the controlling precursors among the groups, no clear patterns are observed. Due to the non-linear growth of ETC intensity, the precursor fields at genesis time offer limited explanations about differences in ETC intensity. Through analysing the temporal evolution of the four ETC intensity groups, we conclude that to understand differences in ETC intensity, as quantified by the five intensity measures, it is necessary to investigate multiple ETC precursor fields and their time evolution.
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RC1: 'Comment on egusphere-2025-6335', Anonymous Referee #1, 27 Jan 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-6335/egusphere-2025-6335-RC1-supplement.pdfCitation: https://doi.org/
10.5194/egusphere-2025-6335-RC1 -
RC2: 'Comment on egusphere-2025-6335', Anonymous Referee #2, 11 Mar 2026
Review of egusphere-2025-6335
In this manuscript, the authors group extratropical cyclones based on their intensity (as described by various metrics) and consider the environmental precursors important for their development. Using ensemble sensitivity analysis it is shown that across all cyclones those that are identified as extreme based on wind metrics are most sensitive to the upper-level jet and low-level baroclinicity, whilst the cyclones that are extreme in terms of precipitation are more sensitive to temperature. The sensitivity analysis is then repeated for the different groups of cyclones but no clear differences are identified. Differences among the cyclone groups are found when considering the times between genesis and maximum intensity in terms of their composite evolution of the considered precursor fields. Differences between the cyclone groups for the different precursors generally agree with what one would expect from theory.
The manuscript is well written and structured and the story of the paper is easy to follow and well supported by the results presented. I think the manuscript contains some interesting results relating to the sensitivities for cyclones with differing intensity measures as well as the development of cyclones across the different classifications. These results would definitely be of interest to the WCD community. I do think the manuscript is quite long and some results could be cut without losing any impact (though I do appreciate the thorough investigation conducted by the authors). I also have some questions relating to methodological choices. I would therefore think the manuscript would be suitable for publication in WCD after the authors have addressed my comments below.
Main comments:
- This comment is regarding the use of intensity measures. The authors consider five intensity measure in the manuscript, with four based on wind speed and one on precipitation. I do not think there is much gained by showing/discussing results for all four wind-based measures: often the results are very similar comparing the wind based measures, e.g. the ensemble sensitivities. This is an obvious place to me to reduce the length of the manuscript without losing any impact. Focusing the results on one wind and one precipitation intensity measure could be sufficient.
- Choice of PV precursor. I was surprised that only one PV precursor was considered and the development of the cyclones seems largely insensitive to it (PV is not really mentioned in section 3.1). Do you have an explanation for this given that the magnitude and structure of PV anomalies varies a lot across different cyclones? It may be because you consider only PV anomalies and at only one pressure level. Have you included other levels or the full PV field to see if any differences appear? One would think the differences found for wind speed, baroclinicity, etc would be reflected in the PV.
- This comment relates to the cyclone groupings. You define the cyclone intensity measures on mostly, I believe, absolute values of e.g. wind or precipitation, and then group those that are extreme in one (or both) of these measures. The storm track densities for the different groups therefore largely correspond to regions that are climatologically windier or wetter (for example a southward shift in the storm track when comparing rainy vs dry). If you defined the intensity metrics on local percentiles/extremes do you think the results of the study would change much? I realise it would be a lot of work to redo the analyses in this way and do not necessarily suggest you do that, but your insight onto the potential impacts would be useful.
Other comments:
- Did you consider reproducing figures 7 through 10 but with ensemble sensitivities that could complement the composites? This may reveal clearer differences across the cyclone groups.
- Seasonality. Do the groups of cyclones occur preferentially in different periods during the extended winter? Do their sensitivities also change across the season?
- I wonder if figure 5 would be easier to interpret if you split the panels by cyclone group rather than intensity metric? I.e. remake figure 4 for each of the cyclone groups? Also, why do the numbers shown in the tables change from percentages in figure 4 to absolute values in figure 5? This also makes it harder for comparison.
Minor comments:
L132-135: Are the results sensitive to the choice of pressure levels here?
L160-165: how is the direction of propagation calculated? Is it an average across the whole storm track or does it change between each tracked point?
L207: what do you mean by a “statistically consistent time period? Please clarify.
L290-295: Does this have climate change implications? I.e. in a world that is generally warmer and moister ETC impacts are stronger? [I see you highlight this in the conclusions but might be worth mentioning here.]
Fig6: When discussing figure 6, a lot of detail is included comparing the different groups when the differences are often small and well within the spread and therefore may not be robust. Consider removing/rephrasing some text.
Technical corrections:
Fig.3 caption: I’d suggest highlighting that the sensitivities are for the cyclones at the time of maximum intensity.
L474: maybe change larger to more strongly negative as larger might be confused with more positive?
L493: “have the largest deepening rates” —> deepen fastest?
L663: Mediterranean are —> Mediterranean area
Citation: https://doi.org/10.5194/egusphere-2025-6335-RC2
Data sets
Identifying controls of extratropical cyclone intensity at genesis time and during intensification in the North Atlantic and Europe: Dataset Joona Cornér et al. https://doi.org/10.23729/fd-75f4f757-3eae-37c7-85df-1923c986796e
Model code and software
Identifying controls of extratropical cyclone intensity at genesis time and during intensification in the North Atlantic and Europe: Python code Joona Cornér et al. https://doi.org/10.5281/zenodo.17953426
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