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June 2011 Bayesian hierarchical modeling for temperature reconstruction from geothermal data
Jenný Brynjarsdóttir, L. Mark Berliner
Ann. Appl. Stat. 5(2B): 1328-1359 (June 2011). DOI: 10.1214/10-AOAS452

Abstract

We present a Bayesian hierarchical modeling approach to paleoclimate reconstruction using borehole temperature profiles. The approach relies on modeling heat conduction in solids via the heat equation with step function, surface boundary conditions. Our analysis includes model error and assumes that the boundary conditions are random processes. The formulation also enables separation of measurement error and model error. We apply the analysis to data from nine borehole temperature records from the San Rafael region in Utah. We produce ground surface temperature histories with uncertainty estimates for the past 400 years. We pay special attention to use of prior parameter models that illustrate borrowing strength in a combined analysis for all nine boreholes. In addition, we review selected sensitivity analyses.

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Jenný Brynjarsdóttir. L. Mark Berliner. "Bayesian hierarchical modeling for temperature reconstruction from geothermal data." Ann. Appl. Stat. 5 (2B) 1328 - 1359, June 2011. https://doi.org/10.1214/10-AOAS452

Information

Published: June 2011
First available in Project Euclid: 13 July 2011

zbMATH: 1223.62173
MathSciNet: MR2849776
Digital Object Identifier: 10.1214/10-AOAS452

Keywords: Boreholes , borrowing strength , climate proxies , heat equation , Paleoclimate , physical-statistical modeling , sensitivity analyses

Rights: Copyright © 2011 Institute of Mathematical Statistics

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Vol.5 • No. 2B • June 2011
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