Articles | Volume 25, issue 11
https://doi.org/10.5194/nhess-25-4545-2025
https://doi.org/10.5194/nhess-25-4545-2025
Research article
 | 
17 Nov 2025
Research article |  | 17 Nov 2025

Automated tail-informed threshold selection for extreme coastal sea levels

Thomas P. Collings, Callum J. R. Murphy-Barltrop, Conor Murphy, Ivan D. Haigh, Paul D. Bates, and Niall D. Quinn

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Latest update: 25 Jun 2026
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Short summary
Determining the threshold above which events are considered extreme is an important consideration for many modelling procedures. We propose an extension of an existing data-driven method for automatic threshold selection. We test our approach on tide gauge records, and show that it outperforms existing techniques. This helps improve estimates of extreme sea levels, and we hope other researchers will use this method for other natural hazards.
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