气候变化领域集成服务门户(CCPortal): Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations

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DOI	10.1007/s00382-020-05538-2
	Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations
	Singh H.; Najafi M.R.; Cannon A.J.
发表日期	2021
ISSN	0930-7575
卷号	56 期号:2021-05-06
英文摘要	The dependence structure of temperature-precipitation compound events is analyzed across Canada using three datasets derived from Canadian Regional Climate Model Large Ensemble simulations, including raw model outputs (CanRCM4-LE) and two sets of multivariate bias-corrected model outputs (Canadian Large Ensembles Adjusted Datasets, CanLEAD-EWEMBI/S14FD). The performance of the ensembles to represent tail dependencies corresponding to warm-wet and warm-dry events is evaluated against NRCANmet observations for 1951–2000 using the copula goodness of fit test. The parameters of the copula model are estimated using a Bayesian framework to characterize the corresponding uncertainties. The non-stationarity of compound extreme climate events is analyzed for 1951–2100 using an ensemble pooling approach and the results are compared with the ones based on the independence assumption. Results show that multivariate bias-corrected climate simulations (i.e. CanLEAD) can better represent the correlated temperature-precipitation extremes compared to raw CanRCM4-LE outputs. The estimated joint return periods reduce significantly when the dependence structure is considered, compared to the independence assumption, for most regions especially in winter and summer. Therefore, analysis of extreme temperature and precipitation in isolation can result in dramatic underestimations of compound warm-wet and warm-dry events. Further, there is strong non-stationarity in the dependence structure of temperature and precipitation under climate change that can play a significant role in future compound extremes. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Bayesian copula estimation; Compound events; Ensemble-pooling; Large-ensembles; Non-stationary events
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/183377
作者单位	Department of Civil and Environmental Engineering, Western University, London, ON, Canada; Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
推荐引用方式 GB/T 7714	Singh H.,Najafi M.R.,Cannon A.J.. Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations[J],2021,56(2021-05-06).
APA	Singh H.,Najafi M.R.,&Cannon A.J..(2021).Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations.Climate Dynamics,56(2021-05-06).
MLA	Singh H.,et al."Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations".Climate Dynamics 56.2021-05-06(2021).