Evaluation of different ensemble configurations for the analysis and prediction of high-impact mesoscale convective systems

Probabilistic prediction of high-impact convective weather has advanced greatly in recent years with the development of ensembles of numerical weather prediction models at convection-allowing resolutions. Likewise, these high-resolution ensembles have enabled in-depth analysis of the mesoscale and storm-scale processes that contribute to the development of severe weather and heavy precipitation. However, the optimal design of such ensembles remains in question, including the application of perturbations to the initial conditions and the model physics.

In this presentation, different ensemble configurations will be evaluated for their utility in analyzing and predicting high-impact mesoscale convective systems (MCSs). In particular, the Center for the Analysis and Prediction of Storms (CAPS) Storm-Scale Ensemble Forecast (SSEF) system, which was run for real-time experimental forecasts and includes initial-condition perturbations drawn from the coarser Short-Range Ensemble Forecast (SREF) system, will be compared with ensembles using initial conditions drawn from an ensemble-based data assimilation method, and using different combinations of physical parameterizations. Two MCS cases from 2010 will be analyzed here, one that led to deadly flash flooding and one associated with widespread damaging winds. In addition to an evaluation of these methods for prediction, their utility for ensemble-based diagnositic analysis will also be discussed.