Abstract
Large-scale numerical simulations are increasingly used for scientific investigation; however, given that they are often needed precisely because ordinary experimental and observational methods cannot be used, their epistemic justification is often in question. Drawing on the adequacy-for-purpose framework, I characterize the problem of model assessment under conditions of scarce empirical evidence. I argue that, while a single model may not suffice under these conditions, a suitable collection of models may be used in concert to advance a community's scientific understanding of a target phenomena and provide a foundation for the progressive development of more adequate models.
