Multi-Scenario Searches: Implementing Uncertainty Management in Integrated Assessment

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Tremendous amounts of information have been gathered to assist in addressing questions associated with global climatic change, but this information has not been sufficient for answering some of the most basic questions, such as the seriousness of the climate change problem and how much it might cost to prevent it. Answers to such questions are fundamentally unpredictable and depend on the divergent value judgments of many individuals. The challenge facing those engaged in integrated assessments of climate change therefore is to best make use of the available information in the context of extreme uncertainty and highly variable social values. This Methods and Models for Integrated Assessment research project will continue the development of methods associated with exploratory modeling to address this challenge. Simulation models will create a large database of plausible future scenarios. Search engines and human decision makers employing advanced visualization techniques then will extract from the database information that is useful to distinguish among policy choices. The research design will look for robust strategies and those that are reasonably successful over a wide range of plausible futures. Bayesian decision theory is used to capture uncertainties in model structure, priors, and loss functions. These methods also will examine some of the best features of scenario-based planning, including the ability to combine quantitative and qualitative information, the use of multiple perspectives for transmitting and receiving information about risk, and the language of managing extreme uncertainty through flexible strategies using signposts and hedging and shaping actions. New capabilities in computer search and visualization techniques have greatly facilitated this type of approach. This study will contribute toward a general framework for managing uncertainty in integrated assessment, using robust strategies as a framework for handling risk and uncertainty and database searches of multiple scenarios as a means for finding these strategies and for combining diverse types of information. This project will enable the investigators to generalize the methods developed in their previous work; to implement the special search algorithms required for this application; and to demonstrate the use of these methods with stakeholder groups, in particular as a means to consider robustness against multiple social values. The project therefore will help develop methods and analytic tools with broad utility for treating uncertainty and combining different types of information in a wide variety of other integrated assessment frameworks and models.