High-resolution forecast models which allow convective storms to form explicitly are central to improving forecasts of heavy rainfall and related weather.
Kilometre-scale versions of the Met Office Unified Model are a key component of the Met Office's forecast system, providing vital information about small-scale weather phenomena such as severe storms which may lead to flooding. To improve our forecasts we need to understand how processes in the atmosphere operate on these scales.
The details of convection and convective initiation, for example, often depend on small scale features. These fall into two categories - those associated with the surface topography (hills, coastlines etc) and those originating from larger scale structures in the atmosphere (fronts etc). The representation of both of these are improved if the model resolution is increased through having more detailed surface data and through having a higher resolution representation of the atmosphere itself.
The accuracy of forecasts can depend on the way we represent small-scale processes like convection and turbulence in the model. In order to understand and improve model representation of these small scale features we are working to improve key parts of the model, in particular the convective, boundary layer, turbulence and microphysics parametrizations. In order to understand the effects of changing these parts of the model we carry out case study work i.e. rerunning particular cases of interest with a view to understanding the model performance.
We are also interested in improving model representation of other weather elements such as wind and fog. Future work will investigate the benefits of coupling high resolution atmospheric models with ocean, wave and hydrology models which may lead to the representation of important feedbacks in the combined system.
We often work in close collaboration with colleagues in academia particularly from the University of Reading Department of Meteorology. We have been involved in a number of previous field projects e.g. CSIP and expect to be involved in more in the future.