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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. 

Abstract. In coastal regions, floods can arise through a combination of multipledrivers, including direct surface run-off, river discharge, storm surge, andwaves. In this study, we analyse compound flood potential in Europe andenvirons caused by these four main flooding sources using state-of-the-artdatabases with coherent forcing (i.e. ERA5). First, we analyse thesensitivity of the compound flooding potential to several factors: (1)sampling method, (2) time window to select the concurrent event of theconditioned driver, (3) dependence metrics, and (4) wave-driven sea leveldefinition. We observe higher correlation coefficients using annual maximathan peaks over threshold. Regarding the other factors, our results showsimilar spatial distributions of the compound flooding potential. Second, thedependence between the pairs of drivers using the Kendall rank correlationcoefficient and the joint occurrence are synthesized for coherent patterns ofcompound flooding potential using a clustering technique. This quantitativemulti-driver assessment not only distinguishes where overall compound floodingpotential is the highest, but also discriminates which driver combinations aremore likely to contribute to compound flooding. We identify that hotspots ofcompound flooding potential are located along the southern coast of the NorthAtlantic Ocean and the northern coast of the Mediterranean Sea.