Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points

Caiado, C.C.S.; Goldstein, M.

Abstract

In this paper we present and illustrate basic Bayesian techniques for the uncertainty analysis of complex physical systems modelled by computer simulators. We focus on emulation and history matching and also discuss the treatment of observational errors and structural discrepancies in time series. We exemplify such methods using a four-box model for the termohaline circulation. We show how these methods may be applied to systems containing tipping points and how to treat possible discontinuities using multiple emulators.

Citation

Caiado, C., & Goldstein, M. (2015). Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points. Communications in Nonlinear Science and Numerical Simulation, 26(1-3), 123-136. https://doi.org/10.1016/j.cnsns.2015.02.006

• Journal Article Type: Article
• Acceptance Date: Feb 4, 2015
• Online Publication Date: Feb 13, 2015
• Publication Date: Sep 1, 2015
• Deposit Date: Sep 29, 2015
• Publicly Available Date: Oct 5, 2015
• Journal: Communications in Nonlinear Science and Numerical Simulation
• Print ISSN: 1007-5704
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 26
• Issue: 1-3
• Pages: 123-136
• DOI: https://doi.org/10.1016/j.cnsns.2015.02.006
• Keywords: Bayesian analysis, Emulation, History matching, Uncertainty quantification, Tipping points.
• Public URL: https://durham-repository.worktribe.com/output/1421821