A mesoscale ensemble prediction system (MEPS) is designed and its application for mid-latitude cyclones explored in this paper. The uncertainties existing in the initial data, model physics, and lateral boundary condition are considered and incorporated into the MEPS. Three separate ensemble subsets are created with respect to the three uncertainties, respectively. Three mid-latitude cyclones that occurred over the United States are chosen for the initial implementation of the MEPS, using the Penn State–NCAR fifth-generation Mesoscale Model (MM5).

The perturbations used to represent the initial condition errors in this study are generated by three breeding methods, which are the Bred Monte-Carlo Perturbations method (MC), the Breeding of Growing Modes (BGM) method and the Perturbed Observations (PO) method. The uncertainties existing in model physics is explored by changing model physical parameterizations, and the use of breeding perturbations in the lateral boundary generates the lateral boundary ensemble subset. Each ensemble subset consists of twenty members.

Through the examination of the ensemble prediction results such as verifying cyclone central pressure, cyclone track, and etc., combining with statistical analysis, we gain a good understanding of the applicability of the MEPS for mid-latitude cyclone prediction. Questions to be addressed will concern the relative merits and role of the each ensemble subset in the MEPS. The ensemble that can provide sufficient information to contain realistic atmospheric states will lead us to examine whether an ensemble forecast could provide insight into the potential forecast skill and improve the accuracy of subsequent probabilistic forecasts for mid-latitude cyclones.