Uncertainty in Integrated Assessment Modelling

Integrated Assessment (IA) aims to facilitate decision-making processes on complex issues. Dealing with uncertainty is principally at the core of Integrated Assessment. IA practitioners realise that. However: – Not all uncertainties can be adequately addressed with existingmethods and tools. This especially holds for uncertainty in model structure and uncertainty due to behavioural and societal variability, value diversity, technological surprise, ignorance and indeterminacy. – Uncertainty is usually treated as a marginal issue, as an additional physical variable, as a mathematical artifact. The current methods merely involve evaluation of the impacts of `certain uncertainties', i.e. uncertainties for which estimates or probability distributions are available.– Current methods give no indication of the magnitude and sources of thevarious underlying uncertainties and the aggregated uncertainty measures are difficult to understand to decision-makers and other audiences.Within the International Centre for Integrative Studies, Maastricht University (the Netherlands), the research project `Perspectives on uncertainty and risk' aims to develop alternative, complementary approaches to uncertainty management in Integrated Assessment. The current paper summarises the theoretical analysis of the concept of uncertainty, and it proposes a typology of sources of uncertainty. This paper further discusses insights and experiences with pluralistic uncertainty management in thecontext of Integrated Assessment modelling in order to assess the strengths and weaknesses of such an approach. Although systematic fundamental uncertainty research is still needed in the context of Integrated Assessment, this paper argues that significant profit in quality terms can be gained by using the available methods, including the pluralistic approach, more consciously and systematically.

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