[en] 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.
Disciplines :
Mathematics
Author, co-author :
Boreux, Jean-Jacques ; Université de Liège - ULiège > Département des sciences et gestion de l'environnement > Surveillance de l'environnement
Naveau, P.
Guin, O.
Perreault, L.
Bernier, J.
Language :
English
Title :
Extracting a common high frequency signal from Northern Quebec black spruce tree-rings with a Bayesian hierarchical model
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