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Climate Change Uncertainty Quantification: Lessons Learned from the Joint EU-USNRC Project on Uncertainty Analysis of Probabilistic Accident Consequence Codes

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  • Cooke, Roger M.

    () (Resources for the Future)

  • Kelly, G.N.

Abstract

Between 1990 and 2000 the U.S. Nuclear Regulatory Commission and the Commission of the European Communities conducted a joint uncertainty analysis of accident consequences for nuclear power plants. This study remains a benchmark for uncertainty analysis of large models involving high risks with high public visibility, and where substantial uncertainty exists. The study set standards with regard to structured expert judgment, performance assessment, dependence elicitation and modeling and uncertainty propagation of high dimensional distributions with complex dependence. The integrated assessment models for the economic effects of climate change also involve high risks and large uncertainties, and interest in conducting a proper uncertainty analysis is growing. This article reviews the EU-USNRC effort and extracts lessons learned, with a view toward informing a comparable effort for the economic effects of climate change.

Suggested Citation

  • Cooke, Roger M. & Kelly, G.N., 2010. "Climate Change Uncertainty Quantification: Lessons Learned from the Joint EU-USNRC Project on Uncertainty Analysis of Probabilistic Accident Consequence Codes," Discussion Papers dp-10-29, Resources For the Future.
  • Handle: RePEc:rff:dpaper:dp-10-29
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    Cited by:

    1. Werner, Christoph & Bedford, Tim & Cooke, Roger M. & Hanea, Anca M. & Morales-NĂ¡poles, Oswaldo, 2017. "Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions," European Journal of Operational Research, Elsevier, vol. 258(3), pages 801-819.

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    Keywords

    uncertainty analysis; expert judgment; expert elicitation; probabilistic inversion; dependence modeling; nuclear safety;

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