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www.clim-past.net/5/607/2009/
doi:10.5194/cp-5-607-2009
© Author(s) 2009. This work is distributed
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Extracting a common high frequency signal from Northern Quebec black spruce tree-rings with a Bayesian hierarchical model
1The University of Liège, Arlon, Belgium
2Laboratoire des Sciences du Climat et de l'Environnement, IPSL-CNRS, France
3Institut de Recherche d'Hydro-Quebec, Montréal, Canada
Abstract. One basic premise of dendroclimatology is that tree rings can be viewed as climate proxies, i.e. rings are assumed to contain some hidden information about past climate. From a statistical perspective, this extraction problem can be understood as the search of a hidden variable which represents the common signal within a collection of tree-ring width series. Classical average-based techniques used in dendrochronology have been applied to estimate the mean behavior of this latent variable. Still, depending on tree species, regional factors and statistical methods, a precise quantification of uncertainties associated to the hidden variable distribution is difficult to assess. To model the error propagation throughout the extraction procedure, we propose and study a Bayesian hierarchical model that focuses on extracting an inter-annual high frequency signal. Our method is applied to black spruce (Picea mariana) tree-rings recorded in Northern Quebec and compared to a classical average-based techniques used by dendrochronologists (Cook and Kairiukstis, 1992).
Final Revised Paper (PDF, 2764 KB) Discussion Paper (CPD) Special Issue
Citation: Boreux, J.-J., Naveau, P., Guin, O., Perreault, L., and Bernier, J.: Extracting a common high frequency signal from Northern Quebec black spruce tree-rings with a Bayesian hierarchical model, Clim. Past, 5, 607-613, doi:10.5194/cp-5-607-2009, 2009. Bibtex EndNote Reference Manager XML
