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doi:10.5194/cpd-5-797-2009
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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. Dendrochronology, the scientific dating method based on the analysis of tree-ring growth patterns, has been frequently applied in climatology. The 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, with different degrees of success (depending on tree species, regional factors and statistical methods), applied to estimate the mean behavior of this latent variable. Still, 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.
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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 Discuss., 5, 797-816, doi:10.5194/cpd-5-797-2009, 2009. Bibtex EndNote Reference Manager XML
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