Wednesday, 1 August 2001: 1:29 PM
Forecast evaluation of a mixed-physics ensemble
Matthew S. Wandishin, Univ. of Arizona, Tucson, AZ; and S. L. Mullen, D. J. Stensrud, and H. E. Brooks
Poster PDF
(665.5 kB)
The aim of ensemble forecasting is to get a probability density function
(pdf) of a forecast field of interest instead of the traditional approach
of determining a best guess for that field at the valid forecast time.
There are two major aspects to this problem: obtaining an appropriate pdf
for the analysis and correctly modeling the evolution of that pdf through
the forecast period. The former aspect of the problem has been much more
extensively studied, typically through the use of the perfect model
assumption in which modeling error is neglected. Obviously, this assumption
is not valid and just as multiple realizations of the analysis are needed in
an attempt to envelop the true initial state of the atmosphere, in the same
way multiple realizations of the evolution of the analysis pdf are needed in
order to envelop the final state of the atmosphere. (The terms initial and
final are used here in the context of a forecast cycle.)
One method for achieving different realizations of the atmospheric evolution
is for different ensemble members to use different physical parameterizations.
This method is employed in a nine-member MM5 ensemble that has been run on 43
cases from the spring of 1999. The nine members consist of the possible
combinations of three planetary boundary layer (PBL) schemes and three
convection parameterizations (CP). With this configuration, the relative
effect of the PBLs and CPs, in general, on the evolution of the model
atmosphere can be examined, along with possible differences in how a
particular CP interacts with the different PBLs. Preliminary results from the
evaluation of precipitation forecasts from the mixed-physics ensemble will be
presented, including that the PBL scheme appears to play a dominant role in
whether the model produces precipitation while the CP plays a dominant role
in determining whether the model produces substantial precipitation amounts.
Supplementary URL: