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Uncertainty in Climate Science and Climate Policy

  • Jonathan Rougier
  • Michel Crucifix
Chapter

Abstract

In this chapter, we argue for and describe the gap that exists between current practice in mainstream academic climate science, and the practical needs of policymakers charged with exploring possible interventions in the context of climate change. By ‘mainstream academic climate science’ we mean the type of climate science that dominates in universities and research centres. We argue that academic climate science does not equip climate scientists to be as helpful as they might be, when involved in climate policy assessment. We attribute this partly to an over-investment in high-resolution climate simulators, and partly to a culture that is uncomfortable with the inherently subjective or personalistic nature of the probabilities in climate science.

References

  1. Andrieu, C., A. Doucet, and R. Holenstein. 2010. Particle Markov Chain Monte Carlo Methods. Journal of the Royal Statistical Society, Series B 72 (3): 269–302. With Discussion, 302–342.CrossRefGoogle Scholar
  2. Aspinall, W.P. 2010. A Route to More Tractable Expert Advice. Nature 463: 294–295.CrossRefGoogle Scholar
  3. Aspinall, W.P., and R.M. Cooke. 2013. Quantifying Scientific Uncertainty from Expert Judgment Elicitation. In Rougier et al. (2013), Chapter 4.Google Scholar
  4. Barnston, A.G., M.K. Tippett, M.L. L’Heureux, S. Li, and D.G. DeWitt. 2012. Skill of Real-Time Seasonal ENSO Model Predictions During 2002–11: Is Our Capability Increasing? Bulletin of the American Meteorological Society 93 (5): 631–651.CrossRefGoogle Scholar
  5. Cooke, R.M., and L.H.J. Goossens. 2000. Procedures Guide for Structured Expert Judgement in Accident Consequence Modelling. Radiation Protection Dosimetry 90 (3): 303–309.Google Scholar
  6. Crucifix, M. 2012. Oscillators and Relaxation Phenomena in Pleistocene Climate Theory. Philosophical Transactions of the Royal Society, Series A, Reprint Available at arXiv:1103.3393v1.Google Scholar
  7. Curry, J.A., and P.J. Webster. 2011. Climate Science and the Uncertainty Monster. Bulletin of the American Meteorological Society 92 (12): 1667–1682.CrossRefGoogle Scholar
  8. de Finetti, B. 1964. Foresight: Its Logical Laws, Its Subjective Sources. In Studies in Subjective Probability, ed. H. Kyburg and H. Smokler, 93–158. New York: Wiley. (2nd ed., New York: Krieger, 1980).Google Scholar
  9. Gigerenzer, G. 2003. Reckoning with Risk: Learning to Live with Uncertainty. London: Penguin.Google Scholar
  10. Goldstein, M. 1997. Prior Inferences for Posterior Judgements. In Structures and Norms in Science. Volume Two of the Tenth International Congress of Logic, Methodology and Philosophy of Science, Florence, August 1995, ed. M.L.D. Chiara, K. Doets, D. Mundici, and J. van Benthem, 55–71. Dordrecht: Kluwer.Google Scholar
  11. Goldstein, M., and D.A. Wooff. 2007. Bayes Linear Statistics: Theory & Methods. Chichester: Wiley.CrossRefGoogle Scholar
  12. Goodman, S. 1999. Toward Evidence-Based Medical Statistics. 1: The p-value Fallacy. Annals of Internal Medicine 130: 995–1004.CrossRefGoogle Scholar
  13. Goodman, S., and S. Greenland. 2007. Why Most Published Research Findings Are False: Problems in the Analysis. PLoS Medicine 4(4): e168. A Longer Version of the Paper Is Available at http://www.bepress.com/jhubiostat/paper135
  14. Guilyardi, E., A. Wittenberg, A. Fedorov, M. Collins, C. Wang, A. Capotondi, G.J. van Oldenborgh, and T. Stockdale. 2009. Understanding El Niño in Ocean—Atmosphere General Circulation Models: Progress and Challenges. Bulletin of the American Meteorological Society 90 (3): 325–340.CrossRefGoogle Scholar
  15. Hájek, A. 2012. Interpretations of Probability. In ed. E.N. Zalta, The Stanford Encyclopedia of Philosophy (Summer Edition). Forthcoming URL http://plato.stanford.edu/archives/sum2012/entries/probability-interpret/
  16. Howson, C., and P. Urbach. 2006. Scientific Reasoning: The Bayesian Approach. 3rd ed. Chicago: Open Court Publishing Co.Google Scholar
  17. Ioannidis, J.P.A. 2005. Why Most Published Research Findings Are False. PLoS Medicine 2 (8): e124. See also Goodman and Greenland (2007) and Ioannidis (2007).CrossRefGoogle Scholar
  18. ———. 2007. Why Most Published Research Findings Are False: Author’s Reply to Goodman and Greenland. PLoS Medicine 4 (6): e215.CrossRefGoogle Scholar
  19. Jaynes, E.T. 2003. Probability Theory: The Logic of Science. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  20. Jeffrey, R.C. 2004. Subjective Probability: The Real Thing. Cambridge: Cambridge University Press. Unfortunately This First Printing Contains Quite a Large Number of Typos.CrossRefGoogle Scholar
  21. Kalnay, E. 2002. Atmospheric Modeling, Data Assimilation and Predictability. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  22. Lad, F. 1996. Operational Subjective Statistical Methods. New York: Wiley.Google Scholar
  23. Lorenz, A., M.G.W. Schmidt, E. Kriegler, and H. Held. 2012. Anticipating Climate Threshold Damages. Environmental Modeling and Assessment 17: 163–175.CrossRefGoogle Scholar
  24. Mastrandrea, M.D., C.B. Field, T.F. Stocker, O. Edenhofer, K.L. Ebi, D.J. Frame, H. Held, E. Kriegler, P.R. Matschoss K.J. Mach, G.-K. Plattner, G.W. Yohe, and F.W. Zwiers. 2010. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Technical report, Intergovernmental Panel on Climate Change (IPCC).Google Scholar
  25. Murphy, J.M., D.M.H. Sexton, D.N. Barnett, G.S. Jones, M.J. Webb, M. Collins, and D.A. Stainforth. 2004. Quantification of Modelling Uncertainties in a Large Ensemble of Climate Change Simulations. Nature 430: 768–772.CrossRefGoogle Scholar
  26. Murphy, J., R. Clark, M. Collins, C. Jackson, M. Rodwell, J.C. Rougier, B. Sanderson, D. Sexton, and T. Yokohata. 2011. Perturbed Parameter Ensembles as a Tool for Sampling Model Uncertainties and Making Climate Projections. In Proceedings of ECMWF Workshop on Model Uncertainty, 20–24 June 2011, pp. 183–208. Available Online, http://www.ecmwf.int/publications/library/ecpublications/_pdf/workshop/2011/Model_uncertainty/Murphy.pdf
  27. Newman, T.J. 2011. Life and Death in Biophysics. Physical Biology 8: 1–6.Google Scholar
  28. Paris, J.B. 1994. The Uncertain Reasoner’s Companion: A Mathematical Perspective. Cambridge: Cambridge University Press.Google Scholar
  29. Parker, W.S. 2010. Predicting Weather and Climate: Uncertainty, Ensembles and Probability. Studies in History and Philosophy of Modern Physics 41: 263–272.CrossRefGoogle Scholar
  30. Ramsey, F.P. 1931. Truth and Probability. In Foundations of Mathematics and Other Essays, ed. R.B. Braithwaite, 156–198. London: Kegan, Paul, Trench, Trubner, & Co.Google Scholar
  31. Rougier, J.C. 2007. Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations. Climatic Change 81: 247–264.CrossRefGoogle Scholar
  32. Rougier, J.C., R.S.J. Sparks, and L.J. Hill, eds. 2013. Risk and Uncertainty Assessment for Natural Hazards. Cambridge: Cambridge University Press.Google Scholar
  33. Santner, T.J., B.J. Williams, and W.I. Notz. 2003. The Design and Analysis of Computer Experiments. New York: Springer.CrossRefGoogle Scholar
  34. Savage, L.J. 1954. The Foundations of Statistics. New York: Dover. Revised 1972 Edition.Google Scholar
  35. Savage, L.J., et al. 1962. The Foundations of Statistical Inference. London: Methuen.Google Scholar
  36. Smith, J.Q. 2010. Bayesian Decision Analysis: Principle and Practice. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  37. Tetlock, P.E. 2005. Expert Political Judgment: How Good Is It? How Can We Know? Princeton/Oxford: Princeton University Press.Google Scholar
  38. Walley, P. 1991. Statistical Reasoning with Imprecise Probabilities. London: Chapman & Hall.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Jonathan Rougier
    • 1
    • 2
  • Michel Crucifix
    • 3
  1. 1.School of MathematicsUniversity of BristolBristolUK
  2. 2.University WalkCharlotteUSA
  3. 3.Université catholique de LouvainLouvain-la-NeuveBelgium

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