气候变化领域集成服务门户(CCPortal): Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: A Bayesian statistical approach

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DOI	10.1088/1748-9326/aaf0cd
	Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: A Bayesian statistical approach
	Rohmer J.; Le Cozannet G.
发表日期	2019
ISSN	17489318
卷号	14 期号:1
英文摘要	Changes in mean sea level (MSL) are a major, but not the unique, cause of changes in high-percentile sea levels (HSL), e.g. the annual 99.9th quantile of sea level (among other factors, climate variability may also have huge influence). To unravel the respective influence of each contributor, we propose to use structural time series models considering six major climate indices (CI) (Artic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Southern Oscillation Index, Niño 1 + 2 and Niño 3.4) as well as a reconstruction of MSL. The method is applied to eight century-long tide gauges across the world (Brest (France), Newlyn (UK), Cuxhaven (Germany), Stockholm (Sweden), Gedser (Danemark), Halifax (Canada), San Francisco (US), and Honolulu (US)). The treatment within a Bayesian setting enables to derive an importance indicator, which measures how often the considered driver is included in the model. The application to the eight tide gauges outlines that MSL signal is a strong driver (except for Gedser), but is not unique. In particular, the influence of Artic Oscillation index at Cuxhaven, Stockholm and Halifax, and of Niño Sea Surface Temperature index 1 + 2 at San Francisco appear to be very strong as well. A similar analysis was conducted by restricting the time period of interest to the 1st part of the 20th century. Over this period, we show that the MSL dominance is lower, whereas an ensemble of CI contribute to a large part to HSL time evolution as well. The proposed setting is flexible and could be applied to incorporate any alternative predictive time series such as river discharge, tidal constituents or vertical ground motions where relevant. © 2019 The Author(s). Published by IOP Publishing Ltd.
英文关键词	Bayesian structure time series model; climate indices; extremes; Kalman-filter; mean sea level
语种	英语
scopus关键词	Atmospheric pressure; Climate models; Climatology; Kalman filters; Surface waters; Tide gages; Time series; Atlantic multidecadal oscillations; Bayesian statistical approach; Climate index; extremes; Mean sea level; Sea surface temperature (SST); Structural time series models; Time series modeling; Sea level; Bayesian analysis; climate change; extreme event; index method; Kalman filter; sea level change; sea surface temperature; tide gauge; time series analysis; Brest [Finistere]; Bretagne; California; Canada; Cornwall [England]; Cuxhaven; Denmark; England; Finistere; France; Gedser; Germany; Halifax; Hawaii [United States]; Hawaiian Islands; Honolulu; Lower Saxony; Newlyn; Nova Scotia; Oahu; San Francisco [California]; Sjaelland; Stockholm [Sweden]; Sweden; United Kingdom; United States
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154720
作者单位	BRGM, 3 av. C. Guillemin, Orléans Cedex 2, 45060, France
推荐引用方式 GB/T 7714	Rohmer J.,Le Cozannet G.. Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: A Bayesian statistical approach[J],2019,14(1).
APA	Rohmer J.,&Le Cozannet G..(2019).Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: A Bayesian statistical approach.Environmental Research Letters,14(1).
MLA	Rohmer J.,et al."Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: A Bayesian statistical approach".Environmental Research Letters 14.1(2019).