Bayesian model selection for the glacial-interglacial cycle

Carson, Jake and Crucifix, Michel and Preston, Simon and Wilkinson, Richard (2017) Bayesian model selection for the glacial-interglacial cycle. Journal of the Royal Statistical Society: Series C . ISSN 0035-9254

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A prevailing viewpoint in paleoclimate science is that a single paleoclimate record contains insufficient information to discriminate between typical competing explanatory models. Here we show that by using SMC 2 (sequential Monte Carlo squared) combined with novel Brownian bridge type proposals for the state trajectories, it is possible to estimate Bayes factors to sufficient accuracy to be able to select between competing models, even with relatively short time series. The results show that Monte Carlo methodology and computer power have now advanced to the point where a full Bayesian analysis for a wide class of conceptual climate models is now possible. The results also highlight a problem with estimating the chronology of the climate record prior to further statistical analysis, a practice which is common in paleoclimate science. Using two datasets based on the same record but with different estimated chronologies, results in conflicting conclusions about the importance of the astronomical forcing on the glacial cycle, and about the internal dynamics generating the glacial cycle, even though the difference between the two estimated chronologies is consistent with dating uncertainty. This highlights a need for chronology estimation and other inferential questions to be addressed in a joint statistical


Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: 10.1111/rssc.12222
Depositing User: Preston, Simon
Date Deposited: 14 Mar 2017 10:52
Last Modified: 28 May 2017 04:41

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