气候变化领域集成服务门户(CCPortal): Uncertainty component estimates in transient climate projections: Precision of estimators in a single time or time series approach

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DOI	10.1007/s00382-019-04635-1
	Uncertainty component estimates in transient climate projections: Precision of estimators in a single time or time series approach
	Hingray B.; Blanchet J.; Evin G.; Vidal J.-P.
发表日期	2019
ISSN	0930-7575
起始页码	2501
结束页码	2516
卷号	53 期号:2020-05-06
英文摘要	Quantifying model uncertainty and internal variability components in climate projections has been paid a great attention in the recent years. For multiple synthetic ensembles of climate projections, we compare the precision of uncertainty component estimates obtained respectively with the two Analysis of Variance (ANOVA) approaches mostly used in recent works: the popular Single Time approach (STANOVA), based on the data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the available simulation period. We show that the precision of all uncertainty estimates is higher when more members are used, when internal variability is smaller and/or the response-to-uncertainty ratio is higher. QEANOVA estimates are much more precise than STANOVA ones: QEANOVA simulated confidence intervals are roughly 3–5 times smaller than STANOVA ones. Except for STANOVA when less than three members is available, the precision is rather high for total uncertainty and moderate for internal variability estimates. For model uncertainty or response-to-uncertainty ratio estimates, the precision is low for QEANOVA to very low for STANOVA. In the most unfavorable configurations (small number of members, large internal variability), large over- or underestimation of uncertainty components is thus very likely. In a number of cases, the uncertainty analysis should thus be preferentially carried out with a time series approach or with a local-time series approach, applied to all predictions available in the temporal neighborhood of the target prediction lead time. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	ANOVA; Climate projections; Internal variability; Model uncertainty; Precision of estimates; Scenario uncertainty; Uncertainty sources
语种	英语
scopus关键词	climate prediction; precision; scenario analysis; time series; uncertainty analysis; variance analysis
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/146015
作者单位	Univ. Grenoble Alpes, CNRS, IGE UMR 5001, Grenoble, 38000, France; Univ. Grenoble Alpes, Irstea, UR ETNA, Grenoble, 38000, France; Irstea, UR RiverLy, centre de Lyon-Villeurbanne, Villeurbanne, 69625, France
推荐引用方式 GB/T 7714	Hingray B.,Blanchet J.,Evin G.,et al. Uncertainty component estimates in transient climate projections: Precision of estimators in a single time or time series approach[J],2019,53(2020-05-06).
APA	Hingray B.,Blanchet J.,Evin G.,&Vidal J.-P..(2019).Uncertainty component estimates in transient climate projections: Precision of estimators in a single time or time series approach.Climate Dynamics,53(2020-05-06).
MLA	Hingray B.,et al."Uncertainty component estimates in transient climate projections: Precision of estimators in a single time or time series approach".Climate Dynamics 53.2020-05-06(2019).