DEMON was part of NERC's Storm Risk Mitigation project, which was looking at improving the ability to quantify the impact from storms and predicting the impact on flooding in urban areas in greater detail.
I produced model precipitation data to be used as input for hydrological models, via a dynamical downscaling process. The dynamical downscaling process involved nesting a Limited Area Model run at 12, 4 and 1.5 km, within global operational analysis data to provide precipitation data for historical flood producing events, and within global climate model data to gain information on potential flood producing events in a a warmer climate. My work also focussed on quantifying the uncertainties in model precipitation by using ensemble forecast data to drive the limited area model.
Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.
Champion, A.J. and Hodges, K.I., 2014: Importance of resolution and model configuration when downscaling extreme precipitation, Tellus 66A, 23993, doi:10.3402/tellusa.v66.23993. http://dx.doi.org/10.3402/tellusa.v66.23993