DOI: 10.1175/JCLI-D-12-00016.1
Scopus记录号: 2-s2.0-84874793299
论文题名: A pseudoproxy evaluation of bayesian hierarchical modeling and canonical correlation analysis for climate field reconstructions over europe
作者: Werner J.P. ; Luterbacher J. ; Smerdon J.E.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 3 起始页码: 851
结束页码: 867
语种: 英语
Scopus关键词: Bayesian hierarchical model
; Bayesian hierarchical modeling
; Bayesian methods
; Canonical correlation analysis
; Climate field reconstruction
; Community climate system model
; Error estimates
; European regions
; Gaussian white noise
; Multi proxies
; Noise properties
; Principal components analysis
; Real-world
; Temperature data
; Bayesian networks
; Climate change
; Hierarchical systems
; Principal component analysis
; Regression analysis
; Climate models
; Bayesian analysis
; canonical analysis
; climate change
; correlation
; hierarchical system
; numerical model
; principal component analysis
; reconstruction
; regression analysis
; Europe
英文摘要: A pseudoproxy comparison is presented for two statistical methods used to derive annual climate field reconstructions (CFRs) for Europe. The employed methods use the canonical correlation analysis (CCA) procedure presented by Smerdon et al. and the Bayesian hierarchical model (BHM) method adopted from Tingley and Huybers. Pseudoproxy experiments (PPEs) are constructed from modeled temperature data sampled from the 1250-yr paleo-run of the NCAR Community Climate System Model (CCSM) version 1.4 model by Ammann et al. Pseudoproxies approximate the distribution of the multiproxy network used by Mann et al. over the European region of interest. Gaussian white noise is added to the temperature data to mimic the combined signal and noise properties of real-world proxies. Results indicate that, while both methods perform well in areas with good proxy coverage, the BHM method outperforms the CCA method across the entire field and additionally returns objective error estimates. © 2013 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52014
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geography, Justus-Liebig-University, Giessen, Germany; Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, United States
Recommended Citation:
Werner J.P.,Luterbacher J.,Smerdon J.E.. A pseudoproxy evaluation of bayesian hierarchical modeling and canonical correlation analysis for climate field reconstructions over europe[J]. Journal of Climate,2013-01-01,26(3)