Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9559
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dc.contributor.authorallGarcia-Aristizabal, A.; Analysis and Monitoring of Environmental Risk (AMRA), Naples, Italyen
dc.contributor.authorallBucchignani, E.; Centro Euro-Mediterraneao sui Cambiamenti Climatici (CMCC)-CIRA, Capua, Italyen
dc.contributor.authorallPalazzi, E.; Institute of Atmospheric Sciences and Climate (ISAC)-CNR, Turin, Italyen
dc.contributor.authorallD’Onofrio, D.; Department of Physics, Universita di Torino, Turin, Italyen
dc.contributor.authorallGasparini, P.; Analysis and Monitoring of Environmental Risk (AMRA), Naples, Italyen
dc.contributor.authorallMarzocchi, W.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.date.accessioned2015-04-22T09:02:03Zen
dc.date.available2015-04-22T09:02:03Zen
dc.date.issued2015-01en
dc.identifier.urihttp://hdl.handle.net/2122/9559en
dc.description.abstractIn this paper we have put forward a Bayesian framework for the analysis and testing of possible non-stationarities in extreme events. We use the extreme value theory to model temperature and precipitation data in the Dar es Salaam region, Tanzania. Temporal trends are modeled writing the location parameter of the generalized extreme value distribution in terms of deterministic functions of explanatory covariates. The analyses are performed using synthetic time series derived from a Regional Climate Model. The simulations, performed in an area around the Dar es Salaam city, Tanzania, take into account two Representative Concentration Pathways scenarios from the Intergovernmental Panel on Climate Change. Our main interest is to analyze extremes with high spatial and temporal resolution and to pursue this requirement we have adopted an individual grid box analysis approach. The approach presented in this paper is composed of the following key elements: (1) an advanced Bayesian method for the estimation of model parameters, (2) a rigorous procedure for model selection, and (3) uncertainty assessment and propagation. The results of our analyses are intended to be used for quantitative hazard and risk assessment and are presented in terms of hazard curves and probabilistic hazard maps. In the case study we found that for both the temperature and precipitation data, a linear trend in the location parameter was the only model performing better than the stationary one in the areas where evidence against the stationary model exists.en
dc.description.sponsorshipThis research has been developed in the framework of the FP7 European project CLUVA (Climate change and Urban Vulnerability in Africa), Grant No. 265137. This research has been funded by the FP7 European project CLUVA (Climate change and Urban ulnerability in Africa).en
dc.language.isoEnglishen
dc.publisher.nameSpringer Science+Business Media B.V.en
dc.relation.ispartofNatural Hazardsen
dc.relation.ispartofseries/ 75 (2015)en
dc.subjectNon-stationary extreme eventsen
dc.subjectClimate changeen
dc.subjectMulti-hazarden
dc.subjectBayesian inferenceen
dc.subjectExtreme precipitationen
dc.subjectExtreme temperatureen
dc.subjectDar es Salaamen
dc.subjectTanzaniaen
dc.titleAnalysis of non-stationary climate-related extreme events considering climate change scenarios: an application for multi-hazard assessment in the Dar es Salaam region, Tanzaniaen
dc.typearticleen
dc.description.statusPublisheden
dc.type.QualityControlPeer-revieweden
dc.description.pagenumber289-320en
dc.identifier.URLhttp://link.springer.com/article/10.1007/s11069-014-1324-zen
dc.subject.INGV01. Atmosphere::01.01. Atmosphere::01.01.02. Climateen
dc.subject.INGV03. Hydrosphere::03.02. Hydrology::03.02.05. Models and Forecastsen
dc.subject.INGV03. Hydrosphere::03.03. Physical::03.03.02. General circulationen
dc.subject.INGV05. General::05.08. Risk::05.08.99. General or miscellaneousen
dc.identifier.doi10.1007/s11069-014-1324-zen
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dc.description.obiettivoSpecifico4A. Clima e Oceanien
dc.description.journalTypeJCR Journalen
dc.description.fulltextopenen
dc.relation.issn0921-030Xen
dc.relation.eissn1573-0840en
dc.contributor.authorGarcia-Aristizabal, A.en
dc.contributor.authorBucchignani, E.en
dc.contributor.authorPalazzi, E.en
dc.contributor.authorD’Onofrio, D.en
dc.contributor.authorGasparini, P.en
dc.contributor.authorMarzocchi, W.en
dc.contributor.departmentAnalysis and Monitoring of Environmental Risk (AMRA), Naples, Italyen
dc.contributor.departmentCentro Euro-Mediterraneao sui Cambiamenti Climatici (CMCC)-CIRA, Capua, Italyen
dc.contributor.departmentInstitute of Atmospheric Sciences and Climate (ISAC)-CNR, Turin, Italyen
dc.contributor.departmentDepartment of Physics, Universita di Torino, Turin, Italyen
dc.contributor.departmentAnalysis and Monitoring of Environmental Risk (AMRA), Naples, Italyen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
item.openairetypearticle-
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item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Bologna, Bologna, Italia-
crisitem.author.deptCMCC-
crisitem.author.deptInstitute of Atmospheric Sciences and Climate, National Research Council (CNR-ISAC), Corso Fiume 4, I-10133, Torino, Italy.-
crisitem.author.deptDepartment of Physics, Universita di Torino, Turin, Italy-
crisitem.author.orcid0000-0001-9196-8452-
crisitem.author.orcid0000-0003-1683-5267-
crisitem.author.orcid0000-0002-0859-0856-
crisitem.author.orcid0000-0002-9114-1516-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.classification.parent01. Atmosphere-
crisitem.classification.parent03. Hydrosphere-
crisitem.classification.parent03. Hydrosphere-
crisitem.classification.parent05. General-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
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