Uncertainty in integrated assessment models: modeling with MiniCAM 1.0

Abstract

Human-initiated climate change remains one of the major science-based public policy issues facing the nations of the world. One feature of the issue that inhibits effective decisions is the ubiquity of uncertainty: many if not most of the parameters of mathematical relationships that forecast emissions, atmospheric processes, impacts, and effectiveness of countermeasures are uncertain. We have added a stochastic simulation capability to the commonly used integrated assessment model MiniCAM 1.0 to analyze the sources of uncertainty and their relative importance and to help devise strategies for depicting and coping with uncertainty. The analysis shows that: (1) the projected range of uncertainty in global temperature increase during the next century is greater than previously supposed, but the central tendency is not dramatically higher; (2) many of the major sources of uncertainty previously discussed in the literature remain significant, but not all; (3) an adaptive policy of “act, then learn, then act” appears to offer better prospects for balancing uncertain costs and benefits of controlling greenhouse gas emissions than do rigid precautionary measures; and (4) current targets for atmospheric stabilization appear excessively ambitious.