The success of ensemble forecasting in the medium range forecasts in the past decade has spurred considerable interest in developing ensemble techniques for mesoscale predictions. The design of a mesoscale ensemble prediction system (MEPS), however, poses many challenges. They include the development of optimal strategies for creating the initial perturbations and determining the appropriate roles of ensembles resulting from initial condition perturbations versus those generated using perturbations to model physics. At the University of Illinois, we have developed a MEPS system that includes uncertainties in both initial conditions and model physics. In addition, we are also exploring the usefulness of a multi-model ensemble prediction system for the mesoscale. In the first part of this study, we compare three well-established techniques for generating initial condition perturbations: a) the simple Monte Carlo method; b) the breeding of growing modes method, which is used at NCEP; and c) the perturbed observations method, which is used operationally at the Canadian Meteorological Center. In the second part, we examine model physics uncertainties through the use of three planetary boundary layer parameterization schemes, four cumulus parameterization schemes and four microphysical schemes.

The ensemble prediction system we have developed is applied to two different phenomena: a) Hurricane prediction; and b) Mid-latitude cyclogenesis prediction. The MEPS system is based on the Penn State / NCAR MM5V3 non-hydrostatic modeling system. Simulations incorporating variations in model input data, physical processes and parameters make up the ensemble set. The ensemble approach outlined herein is being applied to Atlantic Ocean and Gulf of Mexico cyclones, including but not limited to three recent cyclones: hurricanes Opal (1995), Georges (1998), and Floyd (1999). The combination of perturbations to the initial cyclone structure, its environment and the model physical parameterizations are being used to provide a range of plausible solutions with which to explore and improve hurricane track forecasting.

In the second application, the ensemble system is applied to the prediction of three mid-latitude cyclogenesis events. Results from the analysis of these cases suggest that the mesoscale ensemble prediction system using just initial condition perturbations does provide value for a range of sensible weather forecasts, including quantitative and areal extent of precipitation, time of frontal passage, as well as location, central pressure, and maximum winds in a cyclone.