气候变化领域集成服务门户(CCPortal): Stochastic generation of multi-site daily precipitation focusing on extreme events

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DOI	10.5194/hess-22-655-2018
	Stochastic generation of multi-site daily precipitation focusing on extreme events
	Evin G.; Favre A.-C.; Hingray B.
发表日期	2018
ISSN	1027-5606
起始页码	655
结束页码	672
卷号	22 期号:1
英文摘要	Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation amounts at the stations concerned. This paper proposes significant extensions to the multi-site daily precipitation model introduced by Wilks, with the aim of reproducing the statistical features of extremely rare events (in terms of frequency and magnitude) at different temporal and spatial scales. In particular, the first extended version integrates heavy-tailed distributions, spatial tail dependence, and temporal dependence in order to obtain a robust and appropriate representation of the most extreme precipitation fields. A second version enhances the first version using a disaggregation method. The performance of these models is compared at different temporal and spatial scales on a large region covering approximately half of Switzerland. While daily extremes are adequately reproduced at the stations by all models, including the benchmark Wilks version, extreme precipitation amounts at larger temporal scales (e.g., 3-day amounts) are clearly underestimated when temporal dependence is ignored. © Author(s) 2018.
语种	英语
scopus关键词	Precipitation (meteorology); Stochastic systems; Daily precipitations; Extended versions; Extreme precipitation; Heavy-tailed distribution; Statistical features; Stochastic generation; Temporal and spatial scale; Temporal dependence; Stochastic models; benchmarking; extreme event; performance assessment; precipitation (climatology); precipitation assessment; spatiotemporal analysis; stochasticity; Switzerland
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160180
作者单位	Evin, G., Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, Grenoble, France; Favre, A.-C., Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, Grenoble, France; Hingray, B., Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, Grenoble, France
推荐引用方式 GB/T 7714	Evin G.,Favre A.-C.,Hingray B.. Stochastic generation of multi-site daily precipitation focusing on extreme events[J],2018,22(1).
APA	Evin G.,Favre A.-C.,&Hingray B..(2018).Stochastic generation of multi-site daily precipitation focusing on extreme events.Hydrology and Earth System Sciences,22(1).
MLA	Evin G.,et al."Stochastic generation of multi-site daily precipitation focusing on extreme events".Hydrology and Earth System Sciences 22.1(2018).