气候变化领域集成服务门户(CCPortal): Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach

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DOI	10.1007/s11069-021-04608-w
	Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach
	Maposa D.; Seimela A.M.; Sigauke C.; Cochran J.J.
发表日期	2021
ISSN	0921030X
起始页码	2227
结束页码	2246
卷号	107 期号:3
英文摘要	A common problem that arises in extreme value theory when dealing with several variables (such as weather or meteorological) is to find an appropriate method to assess their joint or conditional multivariate extremal dependence behaviour. The method for choosing an appropriate threshold in peaks-over threshold approach is also another problem of endless debate. In this era of climate change and global warming, extreme temperatures accompanied by heat waves and cold waves pose serious economic and health challenges particularly in small economies or developing countries like South Africa. The present study attempts to address these problems, in particular, to deal with and capture dependencies in extreme values of two variables, by applying bivariate conditional extremes modelling with a time-varying threshold to Limpopo province’s monthly maximum temperature series. Limpopo and North West provinces are the two hottest provinces in South Africa characterised by heat waves and the present study is carried out in the Limpopo province at Mara, Messina, Polokwane and Thabazimbi meteorological stations for the period 1994–2009. With the aim to model extremal dependence of maximum temperature at these four meteorological stations, two modelling approaches are applied: bivariate conditional extremes model and time-varying threshold. The latter approach was used to capture the climate change effects in the data. The main contribution of this paper is in combining these two approaches in bivariate extremal dependence modelling of maximum temperature extremes in the Limpopo province of South Africa. The findings of the study revealed both significant positive and negative extremal dependence in some pairs of meteorological stations. Among the major findings were the significant strong positive extremal dependence of Thabazimbi on high-temperature values at Mara and the strong negative extremal dependence of Polokwane on high-temperature values at Messina. The findings of this study play an important role in revealing information useful to meteorologists, climatologists, agriculturalists, and planners in the energy sector among others. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
关键词	Bivariate extreme modelling Climate change Conditional extremes model Laplace margins Temperature extremes Time-varying threshold
英文关键词	climate change; extreme event; global warming; high temperature; Laplace transform; numerical model; temperature anomaly; Limpopo; South Africa
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206409
作者单位	Department of Statistics and Operations Research, University of Limpopo, Private Bag X1106, Sovenga Polokwane, South Africa; Department of Statistics, University of Venda, Private Bag X5050, Thohoyandou, 0950, South Africa; Department of Information Systems, Statistics and Management Science, University of Alabama, Tuscaloosa, AL, United States
推荐引用方式 GB/T 7714	Maposa D.,Seimela A.M.,Sigauke C.,et al. Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach[J],2021,107(3).
APA	Maposa D.,Seimela A.M.,Sigauke C.,&Cochran J.J..(2021).Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach.Natural Hazards,107(3).
MLA	Maposa D.,et al."Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach".Natural Hazards 107.3(2021).