We lay out a simplified progression of cause and effect, showing how the problem can be decoupled into a series of largely independent steps. Population and energy policy studies together with the models of climate system serve as inputs to climate change assessments. Impact assessment is concerned with the effects of climate change. World population, energy consumption and CO 2 emissions appear as endpoints in risk management decisions about climatic change. We believe that such vertical integration is more important than horizontal integration where all outcomes are considered simultaneously, although ideally, a full integration considers all of these facets at once.
Uncertainty is a central feature of any analysis of the potential risks of global climate change.
The scatter of predictions provided by different climate models to the doubling of CO 2 concentrations is, in some ways, analogous to the uncertainty associated with the slope of a dose-response curve of a chemical carcinogen. In this respect, the major uncertainty we are addressing is not stochastic in character. We discuss the de minimis risk for nonstochastic uncertainty. This allows to distinguish between scenarios that are believed possible and those that are rejected as improbable. Empirical evidence suggests that overconfidence in predictions of future development is widespread which results in long tails of the probability distribution, and therefore in unexpectedly high probabilities of surprise.