Inspired by the techniques used by animators, it is argued that sub-gridscale parametrizations (such as those representing deep convection and mountain drag) could be computed on a finer grid than the Numerical Weather Prediction (NWP) model and use the same dynamical equations but with reduced-complexity physics and reduced-accuracy numerical techniques. This fine-scale parametrization grid would correctly capture the spatial and temporal correlation scales of the modelled processes as well as non-equilibrium aspects which are usually absent from conventional parametrization schemes (e.g. diurnal cycle in convection). Reducing the accuracy requirement at the fine scale, as well as the algorithmic complexity of multiple interacting physical processes, could bring forward in time some of the benefits of global convective-scale resolution that are beyond current computational resources. © Crown Copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.