The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

In: Natural hazards and earth system sciences: NHESS, Band 18, Heft 11, S. 2991-3006

Abstract

Abstract. Extratropical cyclones are the most damaging
natural hazard to affect western Europe. Serial clustering occurs when many
intense cyclones affect one specific geographic region in a short period of
time which can potentially lead to very large seasonal losses. Previous
studies have shown that intense cyclones may be more likely to cluster than
less intense cyclones. We revisit this topic using a high-resolution climate
model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric
(storm severity index, SSI) that is based on near-surface meteorological
variables (10 m wind speed) and is a good proxy for losses. The SSI is used
to convert a wind footprint into losses for individual windstorms or seasons.
918 years of a present-day ensemble of coupled climate model simulations from
the High-Resolution Global Environment Model (HiGEM) are compared to
ERA-Interim reanalysis. HiGEM is able to successfully reproduce the
wintertime North Atlantic/European circulation, and represent the large-scale
circulation associated with the serial clustering of European windstorms. We
use two measures to identify any changes in the contribution of clustering to
the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is
up to 20 % larger than the accumulated seasonal loss from a set of random
resamples of the HiGEM data. Seasonal losses are increased by
10 %–20 % relative to randomized seasonal losses at a return period
of 200 years. The contribution of the single largest event in a season to the
accumulated seasonal loss does not change with return period, generally
ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM,
and comparable statistics to ERA-Interim, we conclude that our estimation of
clustering and its dependence on the return period will be useful for
informing the development of risk models for European windstorms,
particularly for longer return periods.