Authors: Valerio Lucarini
Addresses: Department of Earth, Atmospheric and Planetary Sciences, Building 54, Room 17-19, Massachusetts Institute of Technology, 02138 Cambridge, Massachusetts, USA
Abstract: 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.
Keywords: climate change; complex systems; decision-making process under uncertainty; model-system bias; scientific uncertainty.
International Journal of Environment and Pollution, 2002 Vol.18 No.5, pp.413-422
Available online: 15 Jul 2003 *Full-text access for editors Access for subscribers Purchase this article Comment on this article