High-resolution climate ensemble reveals low confidence in projected changes in storm surges for the mid-century

<p>In the coming decades, regions across the globe will be faced with increases in coastal flooding due to sea-level rise and changes in climate extremes. In a collective effort, we have produced new extreme sea level projections derived from an ensemble of high-resolution climate models. Our approach is based on the Global Tide and Surge Model forced with model outputs from the HighResMIP experiments. The HighResMIP models have a much higher spatial resolution than the previous generation of climate models, and can better resolve storms, including tropical cyclones. The dataset has global coverage and spans the period 1950-2050. The dataset provides: 1) timeseries of storm surges, astronomical tides, and total still water levels; and 2) water level statistics for different time slices, including percentiles and return periods.</p><p>In this contribution we focus on storm surges and have a first look at model performance for present-day climate conditions and at projected changes. Comparison of the 1 in 10-year surge levels against the ERA5 reanalysis reveals a large spatial bias for some of the HighResMIP models, highlighting the need for multi-model ensembles and bias correction. Comparison of the 1 in 10-year surge levels between the 1951-1980 and 2021-2050 period, shows that some regions, such as Northwest Europe, Alaska, China, and Patagonia, may be faced with an increase in storm surges (>0.1 m), while other regions, such as the Mediterranean and South Australia may see a decrease in storm surges. Overall, the projected changes are characterized by large intermodel variability due the uncertainties that arise from the climate models, internal variability, and extreme value statistics. Future research should aim to better constrain the uncertainties, which can be achieved by a more in-depth exploration of the changes in the meteorological conditions, enlarging the model ensemble, and the implementation of bias correction methods.</p><p>The full datasets will soon become openly available at the C3S Climate Data Store and can be used to inform climate impact assessments.</p>