Articles | Volume 5, issue 4
Clim. Past, 5, 607–613, 2009
https://doi.org/10.5194/cp-5-607-2009

Special issue: Data/model interactions: the biological perspective of understanding...

Clim. Past, 5, 607–613, 2009
https://doi.org/10.5194/cp-5-607-2009

  14 Oct 2009

14 Oct 2009

Extracting a common high frequency signal from Northern Quebec black spruce tree-rings with a Bayesian hierarchical model

J.-J. Boreux1, P. Naveau2, O. Guin2, L. Perreault3, and J. Bernier1 J.-J. Boreux et al.
  • 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).