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| Titel |
Future projections of insured losses in the German private building sector following the A1B climatic change scenario |
| VerfasserIn |
H. Held, F.-W. Gerstengarbe, F. Hattermann, J. G. Pinto, U. Ulbrich, U. Böhm, K. Born, M. Büchner, M. G. Donat, M. Kücken, G. C. Leckebusch, K. Nissen, T. Nocke, H. Österle, T. Pardowitz, P. C. Werner, O. Burghoff, U. Broecker, A. Kubik |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250063703
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| Zusammenfassung |
| We present an overview of a complementary-approaches impact project dealing with the
consequences of climate change for the natural hazard branch of the insurance industry in
Germany. The project was conducted by four academic institutions together with the
German Insurance Association (GDV) and finalized in autumn 2011. A causal chain is
modeled that goes from global warming projections over regional meteorological
impacts to regional economic losses for private buildings, hereby fully covering
the area of Germany. This presentation will focus on wind storm related losses,
although the method developed had also been applied in part to hail and flood impact
losses.
For the first time, the GDV supplied their collected set of insurance cases, dating back for
decades, for such an impact study. These data were used to calibrate and validate event-based
damage functions which in turn were driven by three different types of regional climate
models to generate storm loss projections. The regional models were driven by a triplet of
ECHAM5 experiments following the A1B scenario which were found representative in the
recent ENSEMBLES intercomparison study.
In our multi-modeling approach we used two types of regional climate models that
conceptually differ at maximum: a dynamical model (CCLM) and a statistical model based
on the idea of biased bootstrapping (STARS). As a third option we pursued a hybrid
approach (statistical-dynamical downscaling). For the assessment of climate change
impacts, the buildings’ infrastructure and their economic value is kept at current
values.
For all three approaches, a significant increase of average storm losses and extreme event
return levels in the German private building sector is found for future decades assuming an
A1B-scenario. However, the three projections differ somewhat in terms of magnitude and
regional differentiation. We have developed a formalism that allows us to express the
combined effect of multi-source uncertainty on return levels within the framework of a
generalized Pareto distribution. |
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