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Uncertainty, Complexity and Concepts of Good Science in Climate Change Modelling: Are GCMs the Best Tools?

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Abstract

In this paper we explore the dominant position of a particular style of scientific modelling in the provision of policy-relevant scientific knowledge on future climate change. We describe how the apical position of General Circulation Models (GCMs) appears to follow ‘logically’ both from conventional understandings of scientific representation and the use of knowledge, so acquired, in decision-making. We argue, however, that both of these particular understandings are contestable. In addition to questioning their current policy-usefulness, we draw upon existing analyses of GCMs which discuss model trade-offs, errors, and the effects of parameterisations, to raise questions about the validity of the conception of complexity in conventional accounts. An alternative approach to modelling, incorporating concepts of uncertainty, is discussed, and an illustrative example given for the case of the global carbon cycle. In then addressing the question of how GCMs have come to occupy their dominant position, we argue that the development of global climate change science and global environmental ‘management’ frameworks occurs concurrently and in a mutually supportive fashion, so uniting GCMs and environmental policy developments in certain industrialised nations and international organisations. The more basic questions about what kinds of commitments to theories of knowledge underpin different models of ‘complexity’ as a normative principle of ‘good science’ are concealed in this mutual reinforcement. Additionally, a rather technocratic policy orientation to climate change may be supported by such science, even though it involves political choices which deserve to be more widely debated.

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  49. These values come from the continuoustime reduced order model reported in Young and Parkinson (1996),which explains the ELmodel data a little better than the discretetimemodel describedpreviously in Young et al. (1996) [29]. However, the time constants of both models are quite similar and the mechanistic interpretations are the same. (Young, P. and Parkinson, S.: 1996, Simplicity out of Complexity in Forecasting Climate Change, Technical Note Centre for Research on Environmental Systems and Statistics, Lancaster University, p. 37.)

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  65. It might be objected that this is a circular argument, since the status of GCMs in policy derives itself in part from the prominence and credibility of GCMs within science. However, what we are proposing is a process of mutual reinforcement of status in which both processes occur concurrently (Shackley, S. and Wynne, B.: 1995, ‘Global Climate Change: The Mutual Construction of an Emergent Science Policy Domain’, Sci. Publ. Pol. 22(4), 218–230.)

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  66. It could be countered that versions of the science emphasising the climate system's chaotic nature might act to strengthen the rationale for global environmental policy action, especially if the precautionary principle is accepted. Note, however, that a dominant response to the suggestion that the climate systemmight face abrupt, chaotic and unexpected changes, has been modelbased analyses of whether this feature affects our ability to find an optimal solution to the problem of managing climate change. Hence it attempts to reimpose a control and management ethos at a subsequent level. (e.g., see: Lempert, R., Schlesinger, M., and Hammitt, J.: 1994, ‘The Impact of Potential Abrupt Climate Changes on NearTerm Policy Choices’, Clim. Change 26, 351–376). Nevertheless, as James Risbey points out, Palmer's analysis may point to a happy marriage between chaos and GCMs, since the latter are needed to represent regime structure, identify climate attractors and perform ensemble climate forecasts. A similar point has been made by a GCM modeller, who noted that: ‘GCMs provide the most practical means of investigating instability, given that the details of the “mean” climate or attractor determine the nature of the instability.... to get the right answer the detailed shape of the attractor may be important’ (personal communication, November 1995).

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  69. For example, there is good reason to believe that the overwhelmingly technical framing of the climate change issue structures the policy agenda in a way which fails to engage with the diverse constituencies (such as local government, industry and lay members of the public) whose commitment would be necessary for any serious policy on global climate change. (Macnaghten, P., GroveWhite, R., Wynne, B., and Jacobs, M.: 1995, Public Perceptions and Sustainability in Lancashire: Indicators, Institutions and Participation, Lancashire County Council, Preston, p. 96; Macnaghten, P. and Jacobs, M.: 1997, ‘Public Identificationwith SustainableDevelopment: Investigating Cultural Barriers to Participation’, Global Environ. Change 7 (1), 5–24.)

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  1. Centre for the Study of Environmental Change (CSEC) Bowland Tower East, Lancaster University, Lancaster, LA1 4YN, U.K

    Simon Shackley & Brian Wynne

  2. Centre for Research into Environmental System (CRES), Institute of Environmental and Biological Sciences, Lancaster University, LAI 4YQ, U.K

    Peter Young & Stuart Parkinson

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Shackley, S., Young, P., Parkinson, S. et al. Uncertainty, Complexity and Concepts of Good Science in Climate Change Modelling: Are GCMs the Best Tools?. Climatic Change 38, 159–205 (1998). https://doi.org/10.1023/A:1005310109968

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