A bivariate approach to estimating the probability of very extreme precipitation events
Date
2020
Authors
Ben Alaya, Mohamed Ali
Zwiers, Francis W.
Zhang, Xuebin
Journal Title
Journal ISSN
Volume Title
Publisher
Weather and Climate Extremes
Abstract
We describe in this paper a semi-parametric bivariate extreme value approach for studying rare extreme precipitation events considered as events that result from a combination of extreme precipitable water (PW) in the atmospheric column above the location where the event occurred and extreme precipitation efficiency, described as the ratio between precipitation and PW. An application of this framework to historical 6-h precipitation accumulations simulated by the Canadian Regional Climate Model CanRCM4 shows that uncertainties and biases of very long-period return level estimates can be substantially reduced relative to the standard univariate approach that fits Generalized Extreme Value distributions to samples of annual maxima of extreme precipitation even when using modest amounts of data.
Description
Keywords
precipitation extreme, precipitable water, precipitation efficiency, statistical frequency analysis, extreme value theory, conditional approach to multivariate extreme values, Pacific Climate Impacts Consortium (PCIC)
Citation
Alaya, M. A. B., Zwiers, F. W., Zhang, X. (2020). A bivariate approach to estimating the probability of very extreme precipitation events. Weather and Climate Extremex, 30, 1-9. https://doi.org/10.1016/j.wace.2020.100290.