Extreme sea levels and coastal flooding can cause devastating socio-economic damages and even loss of lives. Robust and timely risk mitigation requires knowledge of recurrence frequencies, but such estimates are riddled with uncertainties, especially regarding high-impact, low-probability events. In the North Sea–Baltic Sea region, considerable inter- and intra-decadal variability mean that the risks of present-day, wind-driven extreme sea levels are not fully determined. This knowledge gap is becoming more urgent for decision-makers and stakeholders since mitigation of the impacts of current and future flooding hazards, e.g. by coastal adaptation schemes, ideally requires detailed knowledge on the current and future storm-surge regime.

In the present study, we investigate the wind-driven sea-level responses across the entirety of the complex Danish coastlines. We use an idealised framework to map the ranges of critical wind directions systematically by applying an advanced oceanographic model for storm surges driven by synthetic wind fields. We find that the modelled extreme water levels increase linear-to-quadratically with increased wind speed. This increase shows no signs of levelling off even for static winds of 40 m s⁻¹, although this finding is dependent on the wind stress parameterisation, which becomes uncertain for such strong wind forcing. The magnitudes of the resulting extreme water levels are highest in the Wadden Sea region in the southeastern North Sea. Still, when taking local sea-level variability into account, the most extreme incidents are undoubtedly generated in the western Baltic Sea.

Hereafter, and based on the same synthetic wind fields, we investigate a complementary methodology’s potential to generalise the synthetic modelling results. For this purpose, site-specific relations between the dynamic wind forcing (i.e. wind speed and wind direction), parameters defining the local conditions and extreme sea levels are determined based on the dynamic model simulations that are generalised using a novel empirical–statistical method. The approach is tested for the North- and Baltic Seas and performs reasonably well for the highly complex coastlines around Denmark.

We propose that our method could pave the way for improved operational and physically-based impact assessments based on full, large-scale regional climate model projections as a complement to select sets of coupled ocean projections.

极端海平面和沿海洪水会造成毁灭性的社会经济损失，甚至造成生命损失。稳健而及时的风险缓解需要了解复发频率，但这种估计充满了不确定性，尤其是在高影响、低概率事件方面。在北海-波罗的海地区，相当大的年代际和年代际变化意味着目前风驱动的极端海平面的风险尚未完全确定。对于决策者和利益相关者来说，这种知识差距变得越来越紧迫，因为减轻当前和未来洪水灾害的影响，例如通过沿海适应计划，理想情况下需要对当前和未来风暴潮机制的详细了解。

在本研究中，我们调查了整个丹麦复杂海岸线的风驱动海平面响应。我们使用一个理想化的框架，通过对合成风场驱动的风暴潮应用先进的海洋学模型，系统地绘制关键风向的范围。我们发现，模拟的极端水位随着风速的增加呈线性至二次增加。 即使对于 40 m  s ^-1的静风，这种增加也没有趋于平稳的迹象，尽管这一发现取决于风应力参数化，这对于如此强的风力作用变得不确定。由此产生的极端水位的幅度在北海东南部的瓦登海地区最高。尽管如此，考虑到当地海平面的变化，最极端的事件无疑发生在波罗的海西部。

此后，基于相同的合成风场，我们研究了一种互补方法推广合成建模结果的潜力。为此，动态风力强迫（即风速和风向）、定义当地条件和极端海平面的参数之间的特定地点关系基于使用新的经验统计方法推广的动态模型模拟来确定。该方法已针对北海和波罗的海进行了测试，并且在丹麦周围高度复杂的海岸线上表现相当不错。

我们建议，我们的方法可以为改进基于全面、大规模区域气候模型预测的业务和基于物理的影响评估铺平道路，作为对选择的耦合海洋预测集的补充。