Uncertainty, complexity and concepts of good science in climate change modelling: Are GCMs the best tools?

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.