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The coupling of optimal economic growth and climate dynamics

  • Olivier Bahn
  • Laurent Drouet
  • Neil R. Edwards
  • Alain Haurie
  • Reto Knutti
  • Socrates Kypreos
  • Thomas F. Stocker
  • Jean-Philippe Vial

Abstract

In this paper, we study optimal economic growth programs coupled with climate change dynamics. The study is based on models derived from MERGE, a well established integrated assessment model (IAM). We discuss first the introduction in MERGE of a set of “tolerable window” constraints which limit both the temperature change and the rate of temperature change. These constraints, obtained from ensemble simulations performed with the Bern 2.5-D climate model, allow us to identity a domain intended to preserve the Atlantic thermohaline circulation. Next, we report on experiments where a two-way coupling is realized between the economic module of MERGE and an intermediate complexity “3-D-” climate model (C-GOLDSTEIN) which computes the changes in climate and mean temperature. The coupling is achieved through the implementation of an advanced “oracle based optimization technique” which permits the integration of information coming from the climate model during the search for the optimal economic growth path. Both cost-effectiveness and cost-benefit analysis modes are explored with this combined “meta-model” which we refer to as GOLDMERGE. Some perspectives on future implementations of these approaches in the context of “collaborative” or “community” integrated assessment modules are derived from the comparison of the different approaches.

Keywords

Climate Policy Climate Sensitivity Query Point Integrate Assessment Model Stochastic Programming Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Aubin J-P, Bernardo T, Saint-Pierre P (2005) A viability approach to global climate change issues. In: Haurie A and Viguier L (eds.) The coupling of climate and economic dynamics. Kluwer, pp 113–140Google Scholar
  2. Babonneau F, Beltran C, Haurie A, Tadonki C, Vial J-P (2005) Proximal-ACCPM: a versatile oracle based optimization method. Computational and Management Science. Submitted.Google Scholar
  3. Bahn O, Edwards N, Knutti R, Stocker T (2004) Climate policy preserving an atlantic thermohaline circulation collapse. Climatic Change. Submitted. Available in Les Cahiers du GERAD, reference G-2004-72Google Scholar
  4. Bruckner T, Zickfeld K (2004) Low risk emissions corridors for safeguarding the atlantic thermohaline circulation. In: paper presented at the Expert Workshop “Greenhouse Gas Emissions and Abrupt Climate Change”, Paris.Google Scholar
  5. Drouet L, Beltran C, Edwards N, Haurie A, Vial J-P, Zachary D (2005a) An oracle method to couple climate and economic dynamics. In: Haurie A and Viguier L (eds.) The coupling of climate and economic dynamics. Kluwer pp 69–94Google Scholar
  6. Drouet L, Edwards N, Haurie (2005b) Coupling climate and economic models in a cost-benefit framework: a convex optimization approach. Environmental Modeling and Assessment. Submitted.Google Scholar
  7. Edwards N, Marsh R (2005) Uncertainties due to transport-parameter sensitivity in an efficient 3-D ocean-climate model. Climate Dynamics 24:415–433CrossRefGoogle Scholar
  8. Goffin J-L, Haurie A, Vial J-P (1992) Decomposition and non-differentiable optimization with the projective algorithm. Management Science 38:284–302CrossRefGoogle Scholar
  9. Gordon C, Cooper C, Senior C, Banks H, Gregory J, Johns T, Mitchell J, Wood R (2000) The simulation of SST, sea-ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dynamics 16:147–168CrossRefGoogle Scholar
  10. Haarsma R, Goosse H, Selten F, Opsteegh JD (2001) Decadal variability in high northern latitudes as simulated by an intermediate-complexity climate model. Annals of Glaciology 33:525–532Google Scholar
  11. Hargreaves J, Annan J, Edwards N, Marsh R (2005) Climate forecasting using an intermediate complexity earth system model and the ensemble kalman filter. Climate Dynamics 23(7–8):745–760Google Scholar
  12. IPCC (2001a) Climate change 2001: mitigation, contribution of working group III to the third assessment report of the intergovernmental panel on climate change. Metz B et al. (eds) Cambridge University Press. Cambridge, U.K.Google Scholar
  13. IPCC (2001b) Climate change 2001: the scientific basis, contribution ofworking group I to the third assessment report of the intergovernmental panel on climate change. Houghtom J et al. (eds) Cambridge University Press, Cambridge, U.K.Google Scholar
  14. Jaeger CC, Leimbach M, Carraro C, Hasselmann K, Hourcade JC, Keeler A, Klein R (2002) Integrated assessment modeling: modules for cooperation. FEEM Working Paper No. 53Google Scholar
  15. Keller K, Bolker B, Bradford D (2004) Uncertain climate thresholds and optimal economic growth. Journal of Environmental Economics and Management 48(1):723–741CrossRefGoogle Scholar
  16. Knutti R, Meehl G, Allen MR, Stain forth DA (2005) Constraining climate sensitivity from the seasonal cycle in surface temperature. J. Climate 19:4224–4233CrossRefGoogle Scholar
  17. Knutti R, Stocker T (2002) Limited predictability of the future thermohaline circulation close to an instability threshold. Journal of Climate 15:179–186CrossRefGoogle Scholar
  18. Knutti R, Stocker T, Joos F, Plattner G-K (2002) Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature 416:719–723CrossRefGoogle Scholar
  19. Knutti R, Stocker TF, Joos F, Plattner G-K (2003) Probabilistic climate change projections using neural networks. Climate Dynamics 21:257–272CrossRefGoogle Scholar
  20. Leimbach M, Jaeger C (2004) A modular approach to integrated assessment modeling. Environmental Modelling and Assessment 9(4):207–220CrossRefGoogle Scholar
  21. Lenton TM, Williamson MS, Edwards NR, Marsh R, Price AR, Ridgwell AJ, Shepherd JG, and the GENIE team (2005) Millennial timescale carbon cycle and climate change in an efficient Earth system model. Climate Dynamics. Submitted.Google Scholar
  22. Manne A, Mendelsohn R, Richels R (1995) MERGE-a model for evaluating regional and global effects of GHG reduction policies. Energy Policy 23(1):17–34CrossRefGoogle Scholar
  23. Manne A, Richels R (2005) MERGE: an integrated assessment model for global climate change. In: Loulou R, Waaub J-P, Zaccour G, (eds) Energy and Environment. GERAD 25th Anniversary Series. Springer, pp 175–189Google Scholar
  24. Moré J (1983) Recent developments in algorithms and software for trust region methods. In: Mathematical Programming: The State of the Art. Springer Verlag, Berlin, pp. 258–287Google Scholar
  25. Negishi T (1972) General equilibrium theory and international trade. North-Holland.Google Scholar
  26. Nordhaus W (1993) Rolling the ‘DICE’: an optimal transition path for controlling greenhouse gases. Resource and Energy Economics 15:27–50CrossRefGoogle Scholar
  27. Nordhaus W, Boyer J (2000) Warming the world: economic models of global warming. MIT PressGoogle Scholar
  28. Péton O, Vial J-P (2001) A brief tutorial on ACCPM. Technical report. Logilab, University of GenevaGoogle Scholar
  29. Prinn R, et al. (1999) Integrated global system model for climate policy assessment: feedbacks and sensitivity studies. Climatic Change 3/4(41):469–546CrossRefGoogle Scholar
  30. Schmittner A, Stocker T (1999) The stability of the thermohaline circulation in global warming experiments. Journal of Climate 12:1117–1133CrossRefGoogle Scholar
  31. Schramm H, Zowe J (1992) A version of the bundle idea for minimizing a non-smooth function: conceptual idea, convergence analysis, numerical results. SIAM Journal on Optimization 2:121–152CrossRefGoogle Scholar
  32. Stainforth D, et al (2005) Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 433:403–406CrossRefGoogle Scholar
  33. Stocker T, Schmittner A (1997) Influence of CO2 emissions rates on the stability of the thermohaline circulation. Nature 388:862–865CrossRefGoogle Scholar
  34. Stocker T, Wright D, Mysak L (1992) A zonally averaged, coupled ocean-atmosphere model for paleoclimate studies. Journal of Climate 4:773–797CrossRefGoogle Scholar
  35. Stott P, Mitchell J, Gregory J, Santer B, Meehl G, Delworth T, Allen M (2005) Observational constraints on past attributable warming and predictions of future global warming. J. Climate 19:3055–3069CrossRefGoogle Scholar
  36. Toth F, Bruckner T, Fuessel H-M, Leimbach M, Petshel-Held G (2003) Integrated assessment of long-term climate policies: part 1 — model presentation. Climatic Change 56:37–56CrossRefGoogle Scholar
  37. WBGU (2003) Climate protection strategies for the 21st century. Earthscan, London.Google Scholar
  38. Weaver A, Eby M, Wiebe E, Bitz C, Duffy P, Ewen T, Fanning A, Holland M, MacFadyen A, Matthews H, Meissner K, Saenko O, Schmittner A, Wang H, Yoshimori M (2001) The UVic earth system climate model: model description, climatology, and applications to past, present and future climates. Atmos-Ocean 39:361–428Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • Olivier Bahn
    • 1
  • Laurent Drouet
    • 2
  • Neil R. Edwards
    • 3
  • Alain Haurie
    • 2
  • Reto Knutti
    • 4
  • Socrates Kypreos
    • 5
  • Thomas F. Stocker
    • 6
  • Jean-Philippe Vial
    • 2
  1. 1.GERAD and MQGHEC MontréalMontréalCanada
  2. 2.LOGILAB-HECUniversity of GenevaGenevaSwitzerland
  3. 3.Earth Sciences, CEPSAROpen UniversityMilton KeynesUK
  4. 4.National Center for Atmospheric ResearchBoulderUSA
  5. 5.Paul Scherrer InstituteVilligenSwitzerland
  6. 6.Climate and Environmental Physics, Physics InstituteUniversity of BernBernSwitzerland

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