A bivariate approach to estimating the probability of very extreme precipitation events

Section 1: Publication

Publication Type

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

ISBN

ISSN

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.

Plain Language Summary

Section 2: Additional Information

Program Affiliations

GWF: Global Water Futures

Project Affiliations

GWF-CPE: Climate-Related Precipitation Extremes

Submitters

Name	Role	Email	Institution

Publication Stage

Theme

Presentation Format

Additional Information

Climate-Related Precipitation Extremes