Models are used to make forecasts of volcanic ash dispersion during eruptions. These models have unknown inputs relating to the eruption itself, physical processes, and meteorological conditions. We use statistical models to predict the output of the expensive physical model and show we can account for the effects of the different inputs. We compare the model to real-world observations and show that accounting for all sources of uncertainty may lead to different conclusions about the inputs.