We have compared methods for generating ensemble simulations of seasonal precipitation using the summer 1993 flood (1 June - 31 July) over the north-central U.S. as a test case. The methods used are:
- Lagged-average-forecast ensemble: Several instances of the MM5 mesoscale mdoel are executed with the same physics and numerics but with differing initial conditions for each ensemble member. Each ensemble member is started at a different initial time with all simulations overlapping for the period of interest. Results for this overlapping period are used as members of the ensemble.
- Perturbed physics ensemble: This method uses MM5 with a single set of physics options, but internal parameters within the convective parameterization are varied to create realizations for the ensemble. All simulations use the same initial conditions.
- Mixed physics ensemble: A number of simulations are performed with MM5 using a variety of physics options but the same initial conditions. The resulting simulations are then evaluated as an ensemble.
- Multi-model ensemble: The various models participating in the PIRCS 1-B experiment, which considered the 1993 flood period, are considered as individual realizations of an ensemble.
Each ensemble was evaluated using a variety of error measures such as mean square error, equitable threat score, etc. Results show that the multi-model and mixed-physics ensembles had the largest spread; notably, the spread obtained by using different cumulus parameterizations was as large as the spread obtained by using completely different models. The lagged-average and mixed-physics ensembles had much lower spread and appear to be less useful as ensemble forecasts than the other two types of ensembles.