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Integrated assessment models of global environmental problems play an increasingly important role in decision making. This use demands a good insight regarding the reliability of these models. In this paper we analyze uncertainty management in the IMAGE-project (Integrated Model to Assess the Greenhouse Effect). We use a classification scheme comprising type and source of uncertainty. Our analysis shows reliability analysis as main area for improvement. We briefly review a recently developed methodology, NUSAP, that systematically addresses the strength of data in terms of spread, reliability and scientific status (pedigree) of information. This approach is being tested through interviews with model builders.
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