IIASA RepositoryIntegrated Assessment Models and the Management of UncertaintiesJ. van derSluijsauthorIn this paper, the main focus is on the IMAGE model (Integrated Model to Assess the Greenhouse Effect), which served as a case study. IMAGE has a leading role in process-oriented integrated modeling. According to an independent evaluation of the Dutch NRP (National Research Programme on Global Air Pollution and Climate Change), "IMAGE is an outstanding undertaking, the first attempt to produce a comprehensive integrated assessment framework for the climate change problem and still at the forefront of the field internationally," and "IMAGE has established a niche as a world leader in integrated systems modeling." (Science and Policy Associates, Inc., 1995). In the following, we first describe the rise of IAMs [Integrated Assessment Models] in the mid-eighties as devices to interface science with policy. We describe what IAMs are, in the detail that is necessary for a good understanding of the next sections. Then, we discuss the key uncertainties and limitations in each stage of the causal chain of the climate issue. Next, we discuss the controversy on the (policy) usefulness of IAMs for the climate issue. In a next step, we analyze the mismatch between the types and sources of uncertainty that should be addressed on the one hand and the current practice of uncertainty management in IAMs and available methodologies to address different types and sources of uncertainty in models on the other hand. Furthermore, we look at the reasons for the mismatch and identify areas for the improvement of uncertainty management. In the final section, we discuss the question of how to proceed from the current problems in uncertainty management and, building further on the work by Funtowicz and Ravetz (1990), we propose a method for disentangling the uncertainty problem in complex Integrated Assessment Models.1996-10WP-96-119Monograph

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