气候变化领域集成服务门户(CCPortal): Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections

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DOI	10.1007/s00382-018-4241-0
	Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections
	Tan X.; Gan T.Y.; Chen S.; Liu B.
发表日期	2019
ISSN	0930-7575
起始页码	2105
结束页码	2124
卷号	52 期号:2020-03-04
英文摘要	Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Distribution changes; Large-scale climate patterns; Precipitation; Spatiotemporal quantile regression; Teleconnections
语种	英语
scopus关键词	air-sea interaction; Bayesian analysis; climate change; climate modeling; computer simulation; El Nino-Southern Oscillation; North Atlantic Oscillation; numerical model; Pacific Decadal Oscillation; precipitation (climatology); probability; spatiotemporal analysis; teleconnection; winter; Canada
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/146552
作者单位	Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, China; Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 2W2, Canada; State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
推荐引用方式 GB/T 7714	Tan X.,Gan T.Y.,Chen S.,et al. Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections[J],2019,52(2020-03-04).
APA	Tan X.,Gan T.Y.,Chen S.,&Liu B..(2019).Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections.Climate Dynamics,52(2020-03-04).
MLA	Tan X.,et al."Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections".Climate Dynamics 52.2020-03-04(2019).