Improving 10 4 ‐year surge level estimates using data of the ECMWF seasonal prediction system

The vulnerability of society on extreme weather has resulted in extensive research on the statistics of extremes. Although the theoretical framework of extreme value statistics is well developed, meteorological applications are often limited by the relative shortness of the available datasets. In order to overcome this problem, we use archived data from all past seasonal forecast ensemble runs of the European Centre for Medium‐Range Weather Forecasts (ECMWF). For regions where the forecasts have very little seasonal skill the archived seasonal forecast ensembles provide independent sets that cumulate to over 1500 years. We illustrate this approach by estimating 10 4 ‐year sea‐surge levels at high‐tide along the Dutch coast. No physical mechanisms occur in the ECMWF model that make the distribution of very extreme surges different from what is inferred from a direct analysis of the observations. In comparison with the observational sets, the ECMWF set shows a decrease in the statistical uncertainty of the estimated 10 4 ‐year return value by a factor four.