Climate Models
WP2: Assessing the influence of RCM and NWP model parameterisation on extreme rainfall simulation
Hayley Fowler, Stephen Blenkinsop, Elizabeth Kendon
Model schemes and parameterisations for physical and dynamical processes determine the ability of a climate model to generate extreme events. This work package will advance existing work by Hayley Fowler and project partners Dan Cooley and Stephan Sain (NCAR) by using RCM and NWP ensembles to identify mechanisms (predictors) and model parameters responsible for the generation of extreme rainfall. Along with WP3 this will help us to understand “the reasons for differences between models in their projected changes in precipitation: how much of the uncertainty is due to differences in the representation of large-scale atmospheric features, and how much is due to the representation of small-scale precipitation formation processes” (NERC CWC Science Plan) through the examination of model parameterisations and resolution and their effect on the simulation of extreme rainfall.
Model parameters and parameterisation schemes which have an effect on extreme rainfall generation will be identified from the transient 25km 11–member UKCP09 HadRM3 Perturbed Physics Ensemble (PPE). Additionally, WP2 will explore how different model parameterisations affect RCM ability to reproduce seasonal observed daily extreme rainfall statistics (WP1). A PhD project at Exeter will also develop statistical methods which will support analyses that are more effective at quantifying the effects of RCM structure on extreme precipitation.
WP3: Assessing the influence of model resolution on extreme rainfall simulation
Elizabeth Kendon, Steven Chan, Nigel Roberts, Richard Jones, Hayley Fowler
Existing and new runs of Hadley Centre ERA-reanalysis data driven RCMs and NWP models will be used to assess how simulations of extreme rainfall vary with model resolution. In both cases, 1.5km resolution models will be run and methodologies developed to relate information from these to coarser resolution models (e.g. 12km or 50km). We are seeking to identify large-scale predictors of local precipitation from the high resolution modelling work, informed in the first instance by those predictors identified from observations of extreme rainfall events (WP1). Processes linking large-scale predictors and extreme rainfall will be explored on different space and timescales and across model resolutions. This, combined with analysis of NWP case studies will allow us to understand which extreme rainfall situations benefit from higher resolution. This understanding will also be used to assess the reliability of coarser model predictions. It is hoped that results will provide valuable insight into the characteristics of convective-scale models and into the relationship between models of different resolution that can be applied in the context of climate change predictions.
