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Winter storms with high loss potential in a changing climate from a
regional point of view
Monika Rauthe, Michael Kunz and Susanna Mohr
Institute for Meteorology and Climate Research, University Karlsruhe/Forschungszentrum Karlsruhe,
monika.rauthe@imk.uka.de
1. Introduction
According to the recent publications of the IPCC, global
climate changes are unequivocal (IPCC, 2007). Many more
changes in the global climate systems are very likely in the
following decades and centuries. Concerning winter storms
in global climate models, an enhancement especially of
severe cyclones over Europe is found (see review by Ulbrich
et al., 2009 and references therein). But changes of strength
and/or occurrence of extreme natural hazards on the regional
scale are more or less unknown. Due to the low resolution of
current global climate models, regional effects can be hardly
estimated – especially for parameters like wind speed and
precipitation, which are strongly amplified by local scale
conditions (e.g. orographic effects). Because of the high loss
potential of winter storms the knowledge about changes of
the storm climate on the regional scales is very important
(see Figure 1).
In the RESTER (Strategien zur Reduzierung des
Sturmschadensrisikos für Wälder) project the impacts of
extreme storm events on the forests are analysed. The
investigations are conducted in the framework of the
cooperative research project “Herausforderung
Klimawandel” funded by the federal state of Baden-
Württemberg. Various institutions from different research
fields investigate the effects and impacts of climate change
on the regional scale. Within the RESTER project our
institute characterises the changes in winter storm climate in
Germany with a special focus on the region of Baden-
Württemberg in the southwest of Germany.
contrast to ECHAM5 with its horizontal resolution of
about 210 km, REMO and CLM have a resolution of
about 10 and 18 km, respectively. The REMO simulations
were commissioned by the German Federal Environment
Agency. The CLM simulations are part of the so-called
“Konsortialläufe”. For the projection period the
calculations are based on the IPCC SRES emission
scenarios A1B, A2 and B1 (IPCC, 2007). Details of the
regional climate simulations are summarized in Table 1.
Extreme value statistics are applied to quantify the storm
climate. The analyses are based on the time series of wind
gusts at each grid point. The maximum gusts of the 100
strongest events are fitted with a statistical distribution.
The generalized Pareto distribution (GPD) allows for the
best description of the data (Hosking and Wallis, 1987;
Palutikof et al., 1999). From the fitted probability
distribution, the strength of storms of a specific return
period is estimated. This analysis is applied to every single
grid point for both the control period (1971−2000) and the
projection period (2021−2050).
Forcing
Emission
scenario
REMO
ECHAM5
run 1
A1B, A2,
B1
Resolution 0.088°
≈ 10 km
CLM-KL
run 1
ECHAM5
run 1
A1B
0.167°
≈ 18 km
CLM-KL
run 2
ECHAM5
run 2
A1B
0.167°
≈ 18 km
Table 1. Details of the regional climate
simulations.
Figure 1. Losses after the winter storm ‘Lothar’ in the
Black Forest near Oberkirch in Baden-Württemberg
(Photo: Georg Müller).
2. Data and Methods
This study is based on different data sets from regional
climate models. In addition to the output of REMO also that
of CLM is used. These regional climate models are both
forced by the global circulation model ECHAM5. The
ECHAM5 and REMO model runs were all conducted at the
Max-Planck-Institute for Meteorology in Hamburg. In
3. Results
To estimate the reliability of the regional climate data,
they are evaluated for the control period against point
measurements and results of the so-called storm hazard
map from CEDIM (Center of Disaster Management and
Risk Reduction Technology) published by Heneka et al.
(2006) and Hofherr and Kunz (2009). Despite the
systematic underestimation of the wind speeds in the gusts
the spatial patterns due to the underlying orography are
well reproduced by the regional models. These results are
also confirmed by observations at several SYNOP
stations. Additionally, a dependency on the elevation
above sea level is clearly visible. Stations at higher
elevations show larger differences between observations
and model data than those at lower elevations. But the
effect exists only if the elevation differences are large
enough. Altogether, the regional climate models are able
to resolve the local amplifications of wind speeds e.g. due
to orography and land use. This is a big advantage over the
coarse resolution of the global models. The
underestimation of the absolute gust wind speeds in the