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SUMMARY:Multivariate Statistical Modelling of Compound Events via Pair-Cop
 ula Constructions: Analysis of Floods in Ravenna (Italy) (by Emanuele Beva
 cqua)
DTSTART:20170418T100000Z
DTEND:20170418T113000Z
DTSTAMP:20170413T120644Z
UID:presentation-36.series-6
DESCRIPTION:Compound events (CEs) are multivariate extreme events in which
  the individual contributing variables may not be extreme themselves\, but
  their joint - dependent - occurrence causes an extreme impact. Convention
 al univariate statistical analysis cannot give accurate information regard
 ing the multivariate nature of these events. We develop a conceptual model
 \, implemented via pair-copula constructions\, which allows for the quanti
 fication of the risk associated with compound events in present day and fu
 ture climate\, as well as the uncertainty estimates around such risk. The 
 model includes predictors\, which could represent for instance meteorologi
 cal processes\, that provide insight into both the involved physical mecha
 nisms\, and the temporal variability of compound events. Moreover\, this m
 odel enables multivariate statistical downscaling of compound events. Down
 scaling is required to extend the compound events risk assessment to the p
 ast or future climate\, where climate models either do not simulate realis
 tic values of the local variables driving the events\, or do not simulate 
 them at all. Based on the developed model\, we study compound floods\, i.e
 . joint storm surge and high river runoff\, in Ravenna (Italy). To explici
 tly quantify the risk\, we define the impact of compound floods as a funct
 ion of sea and river levels. We use meteorological predictors to extend th
 e analysis to the past\, and get a more robust risk analysis. We quantify 
 the uncertainties of the risk analysis observing that they are very large 
 due to the shortness of the available data\, though this may also be the c
 ase in other studies where they have not been estimated. Ignoring the depe
 ndence between sea and river levels would result in an underestimation of 
 risk\, in particular the expected return period of the highest compound fl
 ood observed increases from about 20 to 32 years when switching from the d
 ependent to the independent case.
LOCATION:SR Wegener Center\, Brandhofgasse 5\, 1st floor
ORGANIZER;CN="Tobias Lichtenegger";ROLE=CHAIR:MAILTO:tobias.lichtenegger@u
 ni-graz.at
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