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| Titel |
How to deal properly with a natural catastrophe database – analysis of flood losses |
| VerfasserIn |
W. Kron, M. Steuer, P. Löw, A. Wirtz |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 12, no. 3 ; Nr. 12, no. 3 (2012-03-02), S.535-550 |
| Datensatznummer |
250010599
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| Publikation (Nr.) |
 copernicus.org/nhess-12-535-2012.pdf |
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| Zusammenfassung |
| Global reinsurer Munich Re has been collecting data on losses from natural
disasters for almost four decades. Together with EM-Dat and sigma, Munich
Re's NatCatSERVICE database is currently one of three global databases of
its kind, with its more than 30 000 datasets. Although the database was
originally designed for reinsurance business purposes, it contains a host of
additional information on catastrophic events. Data collection poses
difficulties such as not knowing the exact extent of human and material
losses, biased reporting by interest groups, including governments, changes
over time due to new findings, etc. Loss quantities are often not separable
into different causes, e.g., windstorm and flood losses during a hurricane,
or windstorm, hail and flooding during a severe storm event. These
difficulties should be kept in mind when database figures are analysed
statistically, and the results have to be treated with due regard for the
characteristics of the underlying data. Comparing events at different
locations and on different dates can only be done using normalised data. For
most analyses, and in particular trend analyses, socio-economic changes such
as inflation or growth in population and values must be considered. Problems
encountered when analysing trends are discussed using the example of floods
and flood losses. |
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