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Storm surges are the most important driver of flooding in many coastal areas. Understanding the spatial extent of storm surge events has important financial and practical implications for flood risk management, reinsurance, infrastructure reliability and emergency response. In this paper, we apply a new tracking algorithm to a high-resolution surge hindcast (CODEC, 1980–2017) to characterize the spatial dependence and temporal evolution of extreme surge events along the coastline of the UK and Ireland. We quantify the severity of each spatial event based on its footprint extremity to select and rank the collection of events. Several surge footprint types are obtained based on the most impacted coastal stretch from each particular event, and these are linked to the driving storm tracks. Using the collection of the extreme surge events, we assess the spatial distribution and interannual variability of the duration, size, severity, and type. We find that the northeast coastline is most impacted by the longest and largest storm surge events, while the English Channel experiences the shortest and smallest storm surge events. The interannual variability indicates that the winter seasons of 1989-90 and 2013–14 were the most serious in terms of the number of events and their severity, based on the return period along the affected coastlines. The most extreme surge event and the highest number of events occurred in the winter season 1989–90, while the proportion of events with larger severities was higher during the winter season 2013–14. This new spatial analysis approach of surge extremes allows us to distinguish several categories of spatial footprints of events around the UK/Ireland coast and link these to distinct storm tracks. The spatial dependence structures detected can improve multivariate statistical methods which are crucial inputs to coastal flooding assessments.
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Global analysis of temporal clusters of storm surges
Abstract Temporal storm surge clustering refers to a series of events affecting the same region within a short period of time, which can strongly influence coastal flooding impacts and erosion. Here, we analyze global storm surge clustering from tide gauges and a state-of-the-art global model hindcast to identify geographical hotspots of extreme storm surge clusters and assess event frequencies. We study the spatial distribution as well as the contribution of different event intensities to clustering. On average, globally, 92% of coastal locations show significant temporal clustering for 1-year return period events, and 25% for 5-year return level events, although notable spatial differences exist. Our results reveal two distinct clustering regimes: (i) short timescale clustering, where events occur in rapid succession (intra-annual), and (ii) long timescales (inter-annual), providing varying recovery times between events. We also test the validity of assuming a Poisson distribution, commonly used in storm surge frequency analyses. Our results show that >80% of the stations analyzed do not follow a Poisson distribution, at least when including events that are not the most extreme but exceeded, for example, the 1-year return level. These findings offer insights into temporal clustering dynamics of storm surges and their implications for coastal hazard assessments.
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- Award ID(s):
- 2141461
- PAR ID:
- 10646575
- Publisher / Repository:
- Cambridge University Press
- Date Published:
- Journal Name:
- Cambridge Prisms: Coastal Futures
- Volume:
- 3
- ISSN:
- 2754-7205
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/cft.2025.10008
