the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying regions of Europe which may be less prepared for extreme rainfall
Abstract. Societal preparedness to extreme rainfall events varies geographically. We present a method to assess assumed preparedness based on observational data alone, investigating record daily rainfall across Europe. To define assumed preparedness, we use two metrics: 1) how recently the record daily rainfall occurred; and 2) how extreme the current record was. In locations where the record occurred further in the past, societal memory of the impacts may have faded, possibly reducing people’s interest in preparedness for extreme rainfall. In regions where the current record was not very extreme, a record-smashing event is statistically more likely, yet the region has not experienced such an event so may be less adequately prepared. We show that cities such as Sofia, Barcelona, Munich, and Amsterdam may have low levels of assumed preparedness. Such locations could benefit from communication about possible risks that the population might not be aware of, encouraging adaptation before a record-breaking event arrives.
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Status: open (until 02 Sep 2026)
- CC1: 'Comment on egusphere-2026-4100', Rasmus Benestad, 03 Aug 2026 reply
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RC1: 'Comment on egusphere-2026-4100', Anonymous Referee #1, 11 Aug 2026
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Dear authors,
Please find my comments attached.
Best regards -
RC2: 'Comment on egusphere-2026-4100', Anonymous Referee #2, 12 Aug 2026
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The presented study by Thompson et al. entitled "Identifying regions of Europe which may be less prepared for extreme rainfall" investigates, how well different regions across Europe are prepared regarding extreme precipitation events. For this purpose, they apply a metric on two observation-based gridded precipitation data (E-OBS, HadUK-Grid), which combines the statistical approach of the risk of a new rainfall extreme (absolute magnitude of an extreme) with the probability of a new extreme to happen (time since the last extreme occurred). The latter also includes a more social science related aspect in the form of "the memory of people" on extremes. The further back in the past the extreme event took place, the less "memory" exist. To my opinion this is a highly relevant aspect when it comes to climate communication and acceptance of adaptation measures.
The study is well-structured and easy to follow. Data and methods are well described, and the results are presented in a straightforward and easy to follow way. It fells within the scope of NHESS.
However, I have some major concerns on some specific points, which to my opinion would improve the quality of the study significantly and better highlights the importance of this type of analysis, especially regarding applications, and which should be considered in a revised version. Please find attached a detailed list of comments and recommendations.
Kind regards
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This is an interesting analysis, but I see that the paper does not look at past studies concerning record-braking events in climate research (e.g. dating back to 2003). One central point is how often record-breaking events take place, and the year of the last record is strongly affected by randomness. I have provided an overview of some of the literature on record-braking statistics and analysis in https://doi.org/10.1126/sciadv.ado3712, which I recommend the authors to look at for completeness.