Incorporating uncertainty in national-level climate change-mitigation policy: possible elements for a research agenda

  • Daniel PuigEmail author
  • Fatemeh Bakhtiari


Decision making for climate change management seldom incorporates uncertainty in the analysis that underpins the policy process. First, uncertainty is seldom characterised fully, and attempts to reduce uncertainty—when this is possible—are rare. Second, scientists are ill-equipped to communicate about uncertainty with policy makers, and policy makers most often favour pretended certainty over nuance and detail. Third, the uncertainty analysis that may have been conducted most often fails to actually influence policy in a significant manner. The case is made for (i) characterising and, to the extent possible, reducing uncertainty, (ii) communicating uncertainty, and (iii) reflecting uncertainty in the design of policy initiatives for climate change management. Possible elements for a research agenda on each of these areas are proposed.


Government accountability Decision-support tools Science-policy interface 


  1. Benveniste H, Boucher O, Guivarch C, Le Treut H, Criqui P (2018) Impacts of nationally determined contributions on 2030 global greenhouse gas emissions: uncertainty analysis and distribution of emissions. Environ Res Lett 13(1):014022CrossRefGoogle Scholar
  2. Broomell SB, Kane PB (2017) Public perception and communication of scientific uncertainty. J Exp Psychol Gen 146(2):286–304CrossRefGoogle Scholar
  3. Dessai S, O’Brien K, Hulme M (2007) On uncertainty and climate change. Glob Environ Chang 17(7):1–3CrossRefGoogle Scholar
  4. Enserink B, Kwakkel JH, Veenman S (2013) Coping with uncertainty in climate policy making: (mis) understanding scenario studies. Futures 53:1–12CrossRefGoogle Scholar
  5. Fischhoff B (2012) Communicating uncertainty fulfilling the duty to inform. Issues Sci Technol 28(4):63–70Google Scholar
  6. Fischhoff B, Davis AL (2014) Communicating scientific uncertainty. Proc Natl Acad Sci 111(Supplement 4):13664–13671CrossRefGoogle Scholar
  7. Funtowicz S, Ravetz J (1993) Science for the post-normal age. Futures 25(7):739–755CrossRefGoogle Scholar
  8. Gluckman P (2016) Science advice to governments: an emerging dimension of science diplomacy. Science Diplomacy 5(2):9Google Scholar
  9. Heal G, Kriström B (2002) Uncertainty and climate change. Environ Resour Econ 22(1):3–39CrossRefGoogle Scholar
  10. IPCC (2006) 2006 IP CC guidelines for national greenhouse gas inventories. IntergovernmentalPanel on Climate Change, GenevaGoogle Scholar
  11. Katz RW (2002) Techniques for estimating uncertainty in climate change scenarios and impact studies. Clim Res 20(2):167–185CrossRefGoogle Scholar
  12. Knaggård Å (2014) What do policy-makers do with scientific uncertainty? The incremental character of Swedish climate change policy-making. Policy Stud 35(1):22–39CrossRefGoogle Scholar
  13. Kwakkel JH, Walker WE, Marchau VA (2010) Classifying and communicating uncertainties in model-based policy analysis. Int J Technol Policy Manag 10(4):299–315CrossRefGoogle Scholar
  14. Kwakkel JH, Eker S, Pruyt E (2016) How robust is a robust policy? Comparing alternative robustness metrics for robust decision-making. In: Robustness Analysis in Decision Aiding, Optimization, and Analytics. Springer, Cham, pp 221–237Google Scholar
  15. Mathijssen J, Petersen A, Besseling P et al (2008) Dealing with uncertainty in policymaking. PBL publication 550032011. Netherlands Environmental Assessment Agency, BilthovenGoogle Scholar
  16. Montibeller G, von Winterfeldt D (2015) Biases and debiasing in multi-criteria decision analysis. In System Sciences (HICSS), 2015 48th Hawaii International Conference on System Sciences. IEEE, pp 1218-1226Google Scholar
  17. Morgan MG (2009) Best practice approaches for characterizing, communicating and incorporating scientific uncertainty in climate decision making. U.S. Climate Change Science Program Synthesis and Assessment Product 5.2. DIANE Publishing, CollingdaleGoogle Scholar
  18. Petersen AC, Cath A, Hage M, Kunseler E, van der Sluijs JP (2011) Post-normal science in practice at the Netherlands environmental assessment agency. Sci Technol Hum Values 36(3):362–388CrossRefGoogle Scholar
  19. Puig D, Bakhtiari F (2017) The impact of debiasing on uncertainty communication: an application to multi-criteria decision analysis in the area of climate change. UNEP DTU Partnership, CopenhagenGoogle Scholar
  20. Puig D, Morales-Nápoles O, Bakhtiari F, Landa G (2017) The accountability imperative for quantifying the uncertainty of emission forecasts: evidence from Mexico. Clim Pol 18(6):742–751Google Scholar
  21. Rogelj J, Fricko O, Meinshausen M, Krey V, Zilliacus JJ, Riahi K (2017) Understanding the origin of Paris agreement emission uncertainties. Nat Commun 8:15748CrossRefGoogle Scholar
  22. UNFCCC (2016) Aggregate effect of the intended nationally determined contributions: an update. Synthesis report by the secreatariat (FCCC/CP/2016/2). United Nations Framework Convention on Climate Change, BonnGoogle Scholar
  23. Unwin SD, Moss RH, Rice JS et al (2011) Characterizing uncertainty for regional climate change mitigation and adaptation decisions (PNNL report 20788). Pacific Northwest National Laboratory, RichlandGoogle Scholar
  24. Walker WE, Marchau VA, Kwakkel JH (2013) Uncertainty in the framework of policy analysis. In public policy analysis. Springer, Boston, pp 215–261Google Scholar

Copyright information

© AESS 2018

Authors and Affiliations

  1. 1.Technical University of DenmarkCopenhagen ØDenmark

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