Abstract
Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. In the aftermath of an extreme event, the extent to which the event was unusual and the potential contribution of climate change in shaping the event are often debated. Commonly analyzes that allow for such assessments are not available right away but are only provided with often considerable time delay. To address this gap, a new tool was developed and applied to storm surges along the German North Sea and Baltic Sea coasts. The tool integrates real-time measurements with long-term statistics to put ongoing extremes or the course of a storm surge season into a climatological perspective in near real time. The approach and the concept of the tool are described and discussed. To illustrate the capabilities, several exemplary cases from the storm surge seasons 2018/2019 and 2019/2020 are discussed. It is concluded that the tool provides support in the near-real-time assessment and evaluation of storm surge extremes. It is further argued that the concept is transferable to other regions and/or coastal hazards.
Highlights
For many low-lying coastal areas, storm surges represent a substantial threat
We propose a concept in which real-time measurements are put into context with observed long-term conditions, that is, their statistics such as mean conditions, variability, expected extremes, or long-term changes in near real time
Since storm surges in the southwestern Baltic Sea are mainly connected with strong easterly winds, this variability in wind climate could further contribute to the insignificant trends in storm surge activity since 1950, against the background of rising mean sea level
Summary
For many low-lying coastal areas, storm surges represent a substantial threat. While many of the affected places can typically cope with or are more or less well-adapted to present-day risks, future risks may increase from, for example, mean sea level rise, subsidence, or changes in storm activity (e.g., von Storch et al, 2015; Wahl et al, 2017). This includes, for example, questions on physically plausible upper limits (Weisse et al, 2019); on probabilities for co-occurrences of storm surges and other hazards (e.g., river floods in estuaries); or, often in the immediate aftermath of an event, on the extent to which this event was “normal” or can be attributed to anthropogenic influences such as climate change The latter requires evaluating and assessing events in near real time within a detection and attribution framework.
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