Estimating concurrent climate extremes: A conditional approach
Date
2021
Authors
Huang, Whitney K.
Monahan, Adam H.
Zwiers, Francis W.
Journal Title
Journal ISSN
Volume Title
Publisher
Weather and Climate Extremes
Abstract
Simultaneous concurrence of extreme values across multiple climate variables can result in large societal and environmental impacts. Therefore, there is growing interest in understanding these concurrent extremes. In many applications, not only the frequency but also the magnitude of concurrent extremes are of interest. One way to approach this problem is to study the distribution of one climate variable given that another is extreme. In this work we develop a statistical framework for estimating bivariate concurrent extremes via a conditional approach, where univariate extreme value modeling is combined with dependence modeling of the conditional tail distribution using techniques from quantile regression and extreme value analysis to quantify concurrent extremes. We focus on the distribution of daily wind speed conditioned on daily precipitation taking its seasonal maximum. The Canadian Regional Climate Model large ensemble is used to assess the performance of the proposed framework both via a simulation study with specified dependence structure and via an analysis of the climate model-simulated dependence structure.
Description
This work was conducted as part of the Canadian Statistical Sciences Institute (CANSSI, http://www.canssi.ca/) Postdoctoral Fellowships program. The authors acknowledge the Canadian Center for Climate Modeling and Analysis of Environment and Climate Change Canada for executing and making available the CanRCM4 large ensemble simulations. The authors would also like to thank Dr. Alex Cannon and three anonymous reviewers for their valuable input.
Keywords
Concurrent wind and precipitation extremes, Quantile regression, Conditional extreme value model, Large climate ensembles, Pacific Climate Impacts Consortium (PCIC)
Citation
Huang, Whitney K, Monahan, Adam H., Zwiers, Francis W. (2021). “Estimating concurrent climate extremes: A conditional approach.” Weather and Climate Extremes, 33, 100332. DOI: https://doi.org/10.1016/j.wace.2021.100332