Simulating wind-driven extreme sea levels: Sensitivity to wind speed and direction

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 40ms−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.