DOI: 10.5194/hess-21-2701-2017
Scopus记录号: 2-s2.0-85020479650
论文题名: Multivariate statistical modelling of compound events via pair-copula constructions: Analysis of floods in Ravenna (Italy)
作者: Bevacqua E ; , Maraun D ; , Hobæk Haff I ; , Widmann M ; , Vrac M
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 6 起始页码: 2701
结束页码: 2723
语种: 英语
Scopus关键词: Climate models
; Floods
; Multivariant analysis
; Risk analysis
; Risk perception
; Rivers
; Statistical methods
; Uncertainty analysis
; Conceptual model
; Developed model
; Multivariate extremes
; Physical mechanism
; Statistical downscaling
; Statistical modelling
; Temporal variability
; Uncertainty estimates
; Risk assessment
; climate modeling
; conceptual framework
; downscaling
; extreme event
; flood
; future prospect
; multivariate analysis
; return period
; risk assessment
; runoff
; storm surge
; temporal variation
; uncertainty analysis
; Emilia-Romagna
; Italy
; Ravenna [Emilia-Romagna]
英文摘要: 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. Conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual model, implemented via pair-copula constructions, which allows for the quantification of the risk associated with compound events in present-day and future climate, as well as the uncertainty estimates around such risk. The model includes predictors, which could represent for instance meteorological processes that provide insight into both the involved physical mechanisms and the temporal variability of compound events. Moreover, this model enables multivariate statistical downscaling of compound events. Downscaling is required to extend the compound events' risk assessment to the past or future climate, where climate models either do not simulate realistic 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 explicitly quantify the risk, we define the impact of compound floods as a function of sea and river levels. We use meteorological predictors to extend the 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 case in other studies where they have not been estimated. Ignoring the dependence between sea and river levels would result in an underestimation of risk; in particular, the expected return period of the highest compound flood observed increases from about 20 to 32 years when switching from the dependent to the independent case. ©Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79161
Appears in Collections: 气候变化事实与影响
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作者单位: Wegener Center for Climate and Global Change, University of Graz, Graz, Austria; Department of Mathematics, University of Oslo, Oslo, Norway; School of Geography,Earth and Environmental Science, University of Birmingham, Birmingham, United Kingdom; Laboratoire des Sciences du Climat et de l'Environnement, CNRS/IPSL, Gif-sur-Yvette, France
Recommended Citation:
Bevacqua E,, Maraun D,, Hobæk Haff I,et al. Multivariate statistical modelling of compound events via pair-copula constructions: Analysis of floods in Ravenna (Italy)[J]. Hydrology and Earth System Sciences,2017-01-01,21(6)