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Can we tell more than we can know? The limits of bivariate drought analyses in the United States
Publikationstyp
Journal Article
Date Issued
2016-08-01
Sprache
English
Author(s)
Serinaldi, Francesco
Volume
30
Issue
6
Start Page
1691
End Page
1704
Citation
Stochastic Environmental Research and Risk Assessment 30 (6): 1691-1704 (2016)
Publisher DOI
Scopus ID
Publisher
Springer
The joint occurrence of extreme hydroclimatic events, such as simultaneous precipitation deficit and high temperature, results in the so-called compound events, and has a serious impact on risk assessment and mitigation strategies. Multivariate frequency analysis (MFA) allows a probabilistic quantitative assessment of this risk under uncertainty. Analyzing precipitation and temperature records in the contiguous United States (CONUS), and focusing on the assessment of the degree of rarity of the 2014 California drought, we highlight some critical aspects of MFA that are often overlooked and should be carefully taken into account for a correct interpretation of the results. In particular, we show that an informative exploratory data analysis (EDA) devised to check the basic hypotheses of MFA, a suitable assessment of the sampling uncertainty, and a better understanding of probabilistic concepts can help to avoid misinterpretation of univariate and multivariate return periods, and incoherent conclusions concerning the risk of compound extreme hydroclimatic events. Empirical results show that the dependence between precipitation deficit and temperature across the CONUS can be positive, negative or not significant and does not exhibit significant changes in the last three decades. Focusing on the 2014 California drought as a compound event and based on the data used, the probability of occurrence strongly depends on the selected variables and how they are combined, and is affected by large uncertainty, thus preventing definite conclusions about the actual degree of rarity of this event.
Subjects
Bivariate frequency analysis
Copulas
Drought
Joint extreme events
Joint return periods
Moisture conditions
Precipitation deficit
Temperature
Uncertainty
DDC Class
620: Engineering