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Publication Additional Information Download
Publication Type
Journal Article
Authorship
Ben Alaya, M. A., Zwiers, F. W., & Zhang, X.
Title
A bivariate approach to estimating the probability of very extreme precipitation events
Year
2020
Publication Outlet
Weather and Climate Extremes, 30, 100290.
DOI
https://doi.org/10.1016/j.wace.2020.100290
Citation
Ben Alaya, M. A., Zwiers, F. W., & Zhang, X. (2020). A bivariate approach to estimating the probability of very extreme precipitation events. Weather and Climate Extremes, 30, 100290. https://doi.org/10.1016/j.wace.2020.100290
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.
Program Affiliations
GWF: Global Water Futures
Project Affiliations
GWF-CPE: Climate-Related Precipitation Extremes
GWF-SDEPFC: Short-Duration Extreme Precipitation in Future Climate
Publication Stage
Published
Additional Information
Climate-Related Precipitation Extremes
Download Links
https://doi.org/10.1016/j.wace.2020.100290
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