For computer simulation models to usefully inform climate risk management decisions, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that need less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and extent of uncertainty quantification. Seeing this trade-off for the important epistemic issue that it is requires a shift in perspective from the established simplicity literature in philosophy of science.
IntroductionComputer simulation models are now essential tools in many scientific fields, and a rapidly-expanding philosophical literature examines a host of accompanying methodological and epistemological questions about their roles and uses (e.g.