Projections of global warming-induced impacts on winter storm losses in the German private household sector

dc.bibliographicCitation.firstPage195eng
dc.bibliographicCitation.issue2eng
dc.bibliographicCitation.volume121eng
dc.contributor.authorHeld, H.
dc.contributor.authorGerstengarbe, F.-W.
dc.contributor.authorPardowitz, T.
dc.contributor.authorPinto, J.G.
dc.contributor.authorUlbrich, U.
dc.contributor.authorBorn, K.
dc.contributor.authorDonat, M.G.
dc.contributor.authorKarremann, M.K.
dc.contributor.authorLeckebusch, G.C.
dc.contributor.authorLudwig, P.
dc.contributor.authorNissen, K.M.
dc.contributor.authorĂ–sterle, H.
dc.contributor.authorPrahl, B.F.
dc.contributor.authorWerner, P.C.
dc.contributor.authorBefort, D.J.
dc.contributor.authorBurghoff, O.
dc.date.accessioned2020-09-11T12:53:03Z
dc.date.available2020-09-11T12:53:03Z
dc.date.issued2013
dc.description.abstractWe present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971-2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6-35 % for 2011-2040, of 20-30 % for 2041-2070, and of 40-55 % for 2071-2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/5671
dc.identifier.urihttps://doi.org/10.34657/4300
dc.language.isoengeng
dc.publisherDordrecht [u.a.] : Springereng
dc.relation.doihttps://doi.org/10.1007/s10584-013-0872-7
dc.relation.ispartofseriesClimatic Change 121 (2013), Nr. 2eng
dc.relation.issn0165-0009
dc.rights.licenseCC BY 3.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/eng
dc.subjectConfidence intervaleng
dc.subjectDownscaling methodseng
dc.subjectDynamical downscalingeng
dc.subjectResidential buildingeng
dc.subjectSources of uncertaintyeng
dc.subjectStatistical distributioneng
dc.subjectStatistical relationshipeng
dc.subjectStatistical-dynamicaleng
dc.subjectGlobal warmingeng
dc.subjectInsuranceeng
dc.subjectStormseng
dc.subjectclimate changeeng
dc.subjectconfidence intervaleng
dc.subjectdownscalingeng
dc.subjectmeteorologyeng
dc.subjectresidential locationeng
dc.subjectreturn periodeng
dc.subjectstorm damageeng
dc.subjecttransfer functioneng
dc.subjectwintereng
dc.subjectGermanyeng
dc.subject.ddc550eng
dc.titleProjections of global warming-induced impacts on winter storm losses in the German private household sectoreng
dc.typearticleeng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitleClimatic Changeeng
tib.accessRightsopenAccesseng
wgl.contributorPIKeng
wgl.subjectUmweltwissenschafteneng
wgl.typeZeitschriftenartikeleng
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