  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'
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.
