parameterisations

Abstract. Complex physical systems can often be simulated using very high resolution models but this is not always prac-tical because of computational restrictions. In this case the model must be simplified or parameterised in order to make it computationally tractable. A parameterised model is created using an ad-hoc selection of techniques which range from the formal to the purely intuitive, and as a result it is very diffi-cult to objectively quantify the fidelity of the model to the physical system. It is rare that a parameterised model can be formally shown to simulate a physical system to within some bounded error. Here we introduce a new approach to param-eterising models which allows error to be formally bounded. The approach makes use of a newly developed computer pro-gram, which we call iGen, that analyses the source code of a high-resolution model and formally derives a much faster, parameterised model that closely approximates the original, reporting bounds on the error introduced by any approxima-tions. These error bounds can be used to formally justify conclusions about a physical system based on observations of the model’s behaviour. Using increasingly complex phys-ical systems as examples we illustrate that iGen has the abil-ity to produce parameterisations that run typically orders of magnitude faster than the underlying, high-resolution mod-els from which they are derived.