Tomassini, Lorenzo; Reichert, Peter; Knutti, Reto; Stocker, Thomas F.; Bosuk, Mark E. (2007). Robust Bayesian uncertainty analysis of climate system properties using Markov chain Monte Carlo methods. Journal of Climate, 20(7), pp. 12391254. American Meteorological Society 10.1175/JCLI4064.1

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A Bayesian uncertainty analysis of 12 parameters of the Bern2.5D climate model is presented. This includes an extensive sensitivity study with respect to the major statistical assumptions. Special attention is given to the parameter representing climate sensitivity. Using the framework of robust Bayesian analysis, the authors first define a nonparametric set of prior distributions for climate sensitivity S and then update the entire set according to Bayes’ theorem. The upper and lower probability that S lies above 4.5°C is calculated over the resulting set of posterior distributions. Furthermore, posterior distributions under different assumptions on the likelihood function are computed. The main characteristics of the marginal posterior distributions of climate sensitivity are quite robust with regard to statistical models of climate variability and observational error. However, the influence of prior assumptions on the tails of distributions is substantial considering the important political implications. Moreover, the authors find that ocean heat change data have a considerable potential to constrain climate sensitivity.
Item Type: 
Journal Article (Original Article) 

Division/Institute: 
08 Faculty of Science > Physics Institute > Climate and Environmental Physics 08 Faculty of Science > Physics Institute 
UniBE Contributor: 
Stocker, Thomas 
Subjects: 
500 Science > 530 Physics 
ISSN: 
08948755 
Publisher: 
American Meteorological Society 
Language: 
English 
Submitter: 
Factscience Import 
Date Deposited: 
04 Oct 2013 14:59 
Last Modified: 
05 Dec 2022 14:18 
Publisher DOI: 
10.1175/JCLI4064.1 
Web of Science ID: 
000245548100008 
BORIS DOI: 
10.7892/boris.25269 
URI: 
https://boris.unibe.ch/id/eprint/25269 (FactScience: 57574) 