Title: Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output,
Abstract: In order to understand underlying processes governing environmental and
physical processes, and predict future outcomes, a complex computer model is
frequently required to simulate these dynamics. However there is inevitably
uncertainty related to the exact parametric form or the values of such
parameters to be used when developing these simulators, with \emph{ranges} of
plausible values prevalent in the literature. Systematic errors introduced by
failing to account for these uncertainties have the potential to have a large
effect on resulting estimates in unknown quantities of interest. Due to the
complexity of these types of models, it is often unfeasible to run large
numbers of training runs that are usually required for full statistical
emulators of the environmental processes. We therefore present a method for
accounting for uncertainties in complex environmental simulators without the
need for very large numbers of training runs and illustrate the method through
an application to the Met Office's atmospheric transport model NAME. We
conclude that there are two principle parameters that are linked with
variability in NAME outputs, namely the free tropospheric turbulence parameter
and particle release height. Our results suggest the former should be
significantly larger than is currently implemented as a default in NAME, whilst
changes in the latter most likely stem from inconsistencies between the model
specified ground height at the observation locations and the true height at
this location. Estimated discrepancies from independent data are consistent
with the discrepancy between modelled and true ground height.