Forecasts from the National Centers for Environmental Prediction's experime
ntal short-range ensemble system are examined and compared with a single ru
n 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 pert
urbations used as initial conditions. This configuration allows for a compa
rison of the two models and the two perturbation strategies, as well as a p
reliminary investigation of the relative merits of mixed-model, mixed-pertu
rbation ensemble systems. The ensemble is also used to estimate the short-r
ange predictability limits of forecasts of precipitation and fields relevan
t to the forecast of precipitation.
Whereas error growth curves for the ensemble and its subgroups are in relat
ive agreement with previous work for large-scale fields such as 500-mb heig
hts, little or no error growth is found for fields of mesoscale interest, s
uch as convective indices and precipitation. The difference in growth rates
among the ensemble subgroups illustrates the role of both initial perturba
tion strategy and model formulation in creating ensemble dispersion. Howeve
r, increase spread per se is not necessarily beneficial, as is indicated by
the fact that the ensemble subgroup with the greatest spread is less skill
ful 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 member
s improves ensemble performance. For some aspects of forecast performance,
even ensemble configurations with as few as five members are shown to signi
ficantly outperform the 29-km Meso-Eta Model.