Evaluation of a Short-Range Multimodel Ensemble System

Abstract

Forecasts from the National Centers for Environmental Prediction?s experimental short-range ensemble system are examined and compared with a single run from a higher-resolution model using similar computational resources. The ensemble consists of five members from the Regional Spectral Model and 10 members from the 80-km Eta Model, with both in-house analyses and bred perturbations used as initial conditions. This configuration allows for a comparison of the two models and the two perturbation strategies, as well as a preliminary investigation of the relative merits of mixed-model, mixed-perturbation ensemble systems. The ensemble is also used to estimate the short-range predictability limits of forecasts of precipitation and fields relevant to the forecast of precipitation. Whereas error growth curves for the ensemble and its subgroups are in relative agreement with previous work for large-scale fields such as 500-mb heights, little or no error growth is found for fields of mesoscale interest, such as convective indices and precipitation. The difference in growth rates among the ensemble subgroups illustrates the role of both initial perturbation strategy and model formulation in creating ensemble dispersion. However, increase spread per se is not necessarily beneficial, as is indicated by the fact that the ensemble subgroup with the greatest spread is less skillful than the subgroup with the least spread. Further examination into the skill of the ensemble system for forecasts of precipitation shows the advantage gained from a mixed-model strategy, such that even the inclusion of the less skillful Regional Spectral Model members improves ensemble performance. For some aspects of forecast performance, even ensemble configurations with as few as five members are shown to significantly outperform the 29-km Meso-Eta Model.