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

TitleUncertainty, complexity and concepts of good science in climate change modelling: Are GCMs the best tools?
Publication TypeManual Entry
Year of Publication1998
AuthorsShackley, S., P. Young, S. Parkinson, and B. Wynne
Climatic Change
Volume38
Pagination159-205
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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Community Notes

Shackley et al. bring forth a very detailed critique of GCMs and discuss their usefulness in climate change planning.  GCMs represent the best available science based on the human perception of the physical mechanisms of the earth system, but GCMs are deterministic and do not capture the inherent uncertainties associated with them.  Climate model rankings are presented to show the wide range of available models for studying climate.  For example, one-dimensional radiative-convective models may have more sophisticated handling of radiation compared to a GCM.  Atmospheric GCMs (AGCMs) coupled to 3-D dynamical ocean models (OGCMs), together with models of land surface vegtation and sea-ice represent the “state of the art” in scientific research.  Although GCMs are at the top of the climate-modelling pyramid, there is great uncertainty in what they produce.  These uncertainties arise in part from the parameterizations used in the models.  “It should be recalled that, even if the theoretical equations of the GCM were able to provide exact descriptions of the global climate, … the numerical solution of these equations in the computer would still be approximate since an accurate, analytic solution of the equations is not possible”.  Shackley et al. investigate the use of a stochastic model and produced estimates of uncertainty that were significantly greater than those by deterministic models.  The result is that many climate researchers are not considering these significant sources of uncertainty.  They do acknowledge limitations to the stochastic approach.  This article presents a perspective of GCMs which is not commonly addressed.  They discuss the positives and negatives of simple versus complex GCMs as well as introducing the idea of stochastic climate models.  They support alternative forms of climate modeling that incorporate concepts of uncertainty.