气候变化领域集成服务门户(CCPortal): Correlating paleoclimate time series: Sources of uncertainty and potential pitfalls

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DOI	10.1016/j.quascirev.2019.03.017
	Correlating paleoclimate time series: Sources of uncertainty and potential pitfalls
	Franke J.G.; Donner R.V.
发表日期	2019
ISSN	0277-3791
起始页码	69
结束页码	79
卷号	212
英文摘要	Comparing paleoclimate time series is complicated by a variety of typical features, including irregular sampling, age model uncertainty (e.g., errors due to interpolation between radiocarbon sampling points) and time uncertainty (uncertainty in calibration), which—taken together—result in unequal and uncertain observation times of the individual time series to be correlated. Several methods have been proposed to approximate the joint probability distribution needed to estimate correlations, most of which rely either on interpolation or temporal downsampling. Here, we compare the performance of some popular approximation methods using synthetic data resembling common properties of real world marine sediment records. Correlations are determined by estimating the parameters of a bivariate Gaussian model from the data using Markov Chain Monte Carlo sampling. We complement our pseudoproxy experiments by applying the same methodology to a pair of marine benthic δ 18 O records from the Atlantic Ocean. We find that methods based upon interpolation yield better results in terms of precision and accuracy than those which reduce the number of observations. In all cases, the specific characteristics of the studied time series are, however, more important than the choice of a particular interpolation method. Relevant features include the number of observations, the persistence of each record, and the imposed coupling strength between the paired series. In most of our pseudoproxy experiments, uncertainty in observation times introduces less additional uncertainty than unequal sampling and errors in observation times do. Thus, it can be reasonable to rely on published time scales as long as calibration uncertainties are not known. © 2019 Elsevier Ltd
语种	英语
scopus关键词	Calibration; Interpolation; Markov processes; Monte Carlo methods; Probability distributions; Submarine geology; Uncertainty analysis; Approximation methods; Calibration uncertainty; Interpolation method; Irregular sampling; Joint probability distributions; Markov chain monte carlo samplings; Sources of uncertainty; Uncertain observations; Time series; calibration; error analysis; interpolation; marine sediment; Markov chain; Monte Carlo analysis; paleoclimate; probability; sampling; time series; uncertainty analysis; Atlantic Ocean
来源期刊	Quaternary Science Reviews
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/151949
作者单位	Potsdam Institut for Climate Impact Research, Potsdam, Germany; Humboldt University Berlin, Berlin, Germany; Magdeburg-Stendal University of Applied Sciences, Magdeburg, Germany
推荐引用方式 GB/T 7714	Franke J.G.,Donner R.V.. Correlating paleoclimate time series: Sources of uncertainty and potential pitfalls[J],2019,212.
APA	Franke J.G.,&Donner R.V..(2019).Correlating paleoclimate time series: Sources of uncertainty and potential pitfalls.Quaternary Science Reviews,212.
MLA	Franke J.G.,et al."Correlating paleoclimate time series: Sources of uncertainty and potential pitfalls".Quaternary Science Reviews 212(2019).