DOI: 10.5194/cp-12-31-2016
Scopus记录号: 2-s2.0-84956651730
论文题名: Inferring climate variability from nonlinear proxies: Application to palaeo-ENSO studies
作者: Emile-Geay J. ; Tingley M.
刊名: Climate of the Past
ISSN: 18149324
出版年: 2016
卷: 12, 期: 1 起始页码: 31
结束页码: 50
语种: 英语
英文摘要: Inferring climate from palaeodata frequently assumes a direct, linear relationship between the two, which is seldom met in practice. Here we simulate an idealized proxy characterized by a nonlinear, thresholded relationship with surface temperature, and we demonstrate the pitfalls of ignoring nonlinearities in the proxy-climate relationship. We explore three approaches to using this idealized proxy to infer past climate: (i) methods commonly used in the palaeoclimate literature, without consideration of nonlinearities; (ii) the same methods, after empirically transforming the data to normality to account for nonlinearities; and (iii) using a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting nonlinearity often exaggerates changes in climate variability between different time intervals and leads to reconstructions with poorly quantified uncertainties. In contrast, explicit recognition of the nonlinear relationship, using either a mechanistic model or an empirical transform, yields significantly better estimates of past climate variations, with more accurate uncertainty quantification. We apply these insights to two palaeoclimate settings. Accounting for nonlinearities in the classical sedimentary record from Laguna Pallcacocha leads to quantitative departures from the results of the original study, and it markedly affects the detection of variance changes over time. A comparison with the Lake Challa record, also a nonlinear proxy for El Ninõ-Southern Oscillation, illustrates how inter-proxy comparisons may be altered when accounting for nonlinearity. The results hold implications for how univariate, nonlinear recorders of normally distributed climate variables are interpreted, compared to other proxy records, and incorporated into multiproxy reconstructions. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49079
Appears in Collections: 气候变化与战略
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Recommended Citation:
Emile-Geay J.,Tingley M.. Inferring climate variability from nonlinear proxies: Application to palaeo-ENSO studies[J]. Climate of the Past,2016-01-01,12(1)