DOI: 10.1016/j.quascirev.2016.09.007
Scopus记录号: 2-s2.0-84987941442
论文题名: Joint palaeoclimate reconstruction from pollen data via forward models and climate histories
作者: Parnell A.C. ; Haslett J. ; Sweeney J. ; Doan T.K. ; Allen J.R.M. ; Huntley B.
刊名: Quaternary Science Reviews
ISSN: 2773791
出版年: 2016
卷: 151 起始页码: 111
结束页码: 126
语种: 英语
英文关键词: Chronological uncertainty
; Climate histories
; Forward models
; Joint inference
; Palaeoclimate reconstruction
; Palynology
; Statistical modelling
Scopus关键词: Climate change
; Open source software
; Open systems
; Uncertainty analysis
; Chronological uncertainty
; Climate history
; Forward models
; Palaeoclimate reconstruction
; Palynology
; Statistical modelling
; Climate models
; chronology
; climate variation
; Monte Carlo analysis
; multivariate analysis
; paleoclimate
; palynology
; radiocarbon dating
; reconstruction
; statistical analysis
; uncertainty analysis
; Basilicata
; Castilla y Leon
; Italy
; Lago Grande di Monticchio
; Laguna de la Roya
; Potenza
; Spain
; Zamora [Castilla y Leon]
英文摘要: We present a method and software for reconstructing palaeoclimate from pollen data with a focus on accounting for and reducing uncertainty. The tools we use include: forward models, which enable us to account for the data generating process and hence the complex relationship between pollen and climate; joint inference, which reduces uncertainty by borrowing strength between aspects of climate and slices of the core; and dynamic climate histories, which allow for a far richer gamut of inferential possibilities. Through a Monte Carlo approach we generate numerous equally probable joint climate histories, each of which is represented by a sequence of values of three climate dimensions in discrete time, i.e. a multivariate time series. All histories are consistent with the uncertainties in the forward model and the natural temporal variability in climate. Once generated, these histories can provide most probable climate estimates with uncertainty intervals. This is particularly important as attention moves to the dynamics of past climate changes. For example, such methods allow us to identify, with realistic uncertainty, the past century that exhibited the greatest warming. We illustrate our method with two data sets: Laguna de la Roya, with a radiocarbon dated chronology and hence timing uncertainty; and Lago Grande di Monticchio, which contains laminated sediment and extends back to the penultimate glacial stage. The procedure is made available via an open source R package, Bclim, for which we provide code and instructions. © 2016 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/59418
Appears in Collections: 过去全球变化的重建
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作者单位: School of Mathematics and Statistics, Insight Centre for Data Analytics, University College Dublin, Ireland; Discipline of Statistics, Trinity College Dublin, Ireland; School of Business, University College Dublin, Ireland; Novartis Ltd, Ireland; School of Biological and Biomedical Sciences, University of Durham, United Kingdom
Recommended Citation:
Parnell A.C.,Haslett J.,Sweeney J.,et al. Joint palaeoclimate reconstruction from pollen data via forward models and climate histories[J]. Quaternary Science Reviews,2016-01-01,151