The intrinsic difficulties in building realistic climate models and in providing complete, reliable and meaningful observational datasets, and the conceptual impossibility of testing theories against data imply that the usual Galilean scientific validation criteria do not apply to climate science. The different epistemology pertaining to climate science implies that its answers cannot be singular and deterministic; they must be plural and stated in probabilistic terms. Therefore, in order to extract meaningful estimates of future climate change from a model, it is necessary to explore the model's uncertainties. In terms of societal impacts of scientific knowledge, it is necessary to accept that any political choice in a matter involving complex systems is made under unavoidable conditions of uncertainty. Nevertheless, detailed probabilistic results in science can provide a baseline for a sensible process of decision making.

© 2004-2006 Inderscience Enterprises Limited.