Decision makers frequently cite uncertainty about climate change and its impacts as a reason to delay policy action to limit greenhouse gas emissions, yet many other decisions are made under great uncertainty. Although recent economic analyses find that delay is not an efficient response to uncertainty, earnest decision makers can be forgiven for being confused on this point because for many years authoritative scientists and economists claimed that climate change would progress linearly and gradually, giving society plenty of time to learn how best to respond. Only recently have many scientists (and some economists) abandoned this view in large numbers as observed climate changes and associated effects on natural systems have become obvious much earlier than expected. Decision makers are interested in knowing about risks, yet risk reduction is only now emerging as a decision making framework for climate change within the analytical community and this framework is far from fully developed.
The climate change research community has been slow to come to grips with the distinct roles that uncertainty plays in knowledge discovery and in decision making, two very different undertakings. In knowledge discovery, uncertainty analysis is a tool for hypothesis testing and building confidence in new understanding. In decision making, uncertainty is a determinant of risk, which in turn is used to judge appropriate policy actions. It should be evident that the standard of confidence is much different in these two cases. In knowledge discovery, scientists require not more than a five percent chance that a conclusion might be wrong. In terms of risk, a five percent chance that an intolerable outcome might occur might be unacceptable to decision makers. To communicate effectively with policymakers, scientists need to communicate uncertainty in terms of risk of intolerable outcomes rather than in terms of knowledge discovery.