Statistical Modeling of Extreme Value Behavior in North American Tree-Ring Density Series

• Activity Number: 329
• Type: Topic Contributed
• Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Elizabeth Mannshardt*+ and Peter F Craigmile and Martin P. Tingley
• Companies: North Carolina State University and The Ohio State University and Harvard University
• Keywords: Bayesian hierarchical modeling ; Generalized extreme value (GEV) distribution ; Spatially varying trends ; Tree ring proxies ; Decadal maxima and minima

Abstract

Many analyses of the paleoclimate record include conclusions about extremes, with a focus on the unprecedented nature of recent climate events. This article develops a Bayesian hierarchical model to investigate spatially varying trends and dependencies in the parameters characterizing the extremes of a proxy data set, and applies it to the site-wise decadal maxima and minima of a gridded network of temperature sensitive tree ring density time series over northern North America. The statistical analysis reveals significant spatial associations in the temporal trends of the location parameters of the generalized extreme value distributions. To the extent that the extremal behavior of the tree ring densities reflects extremal behavior in surface temperatures, results indicate that the distribution which describes temperature extremes varies as a function of both space and time, with temperature maxima becoming more extreme as a function of time and minima having diverging spatial patterns. Results of this proxy-only analysis are a first step towards directly reconstructing extremal climate behavior, by linking extremes in the proxy record to extremes in the instrumental record.