ENSEMBLE FORECASTING AND PREDICTION OF MODEL PERFORMANCE
Sim D. Aberson
Morris Bender (NOAA/GFDL)
Robert Tuleya (NOAA/GFDL)
Stephen Lord (NOAA/NCEP)
Evaluation of methods to improve operational forecasts of tropical cyclone
Recent years have shown a slow and steady increase in skill of
operational tropical cyclone track forecasts. A number of operational track
forecast models have average skill approaching 40%, yet none of them performs
well consistently, and a serious challenge for operational forecasters is
to choose which of the various possibilities presented by the ensemble of
different models is the most likely to occur. Not only should the
guidance itself be presented to forecasters, but an estimate of the
confidence which should be placed in that forecast as well. Thus, a method
for the Prediction of Model Performance (POMP), and methods in ensemble
forecasting are studied.
A method to objectively estimate the confidence in track forecasts
has been developed for the ensemble of models currently in use. Data from
the synoptic situation in the environment of each tropical cyclone,
climatological data, and past performance of each model are analyzed from the
1989 - 1995 hurricane seasons to allow a linear discriminant analysis to
differentiate between forecasts which are expected to perform well from
those expected to be poor, giving the forecasters an object estimate of
confidence of the individual forecasts.
In addition, ensemble forecasting of hurricane tracks using both the
HRD VICBAR model and the GFDL model developed at the Geophysical
Fluid Dynamics Laboratory will be used during the 1996 hurricane season
to quantify the value of using the bred growing modes from the NCEP
ensemble forecasting program to assess the variability of forecast
motion in the models. Assuming that the ensemble perturbations quantify
the local amount of uncertainty in the model analysis and forecast, use
of the ensembles for the purpose of adaptive observations, making
observations in certain locations likely to have impact on the tropical
cyclone, will be studied (Figure 1).
The linear discriminant analysis for the HRD VICBAR
model has shown that individual forecasts which are expected to be
poor can be separated from those expected to be good, allowing forecasters
to disregard the expected-poor information and improve their forecasts.
Preliminary results from the ensemble forecasting study show that there
may be value in using the ensembles developed at NCEP to find problem
areas in the individual guidance models.
The following manuscript has been accepted for
Aberson, S. D., 1996: The prediction of the performance of a nested
barotropic hurricane track forecast model. Wea. Forecasting,
Ooyama, K. V., 1987: Scale controlled objective analysis. Mon. Wea.
Rev., 115, 2479-2506.
DeMaria, M., S. D. Aberson, K. V. Ooyama, and S. J. Lord,
1992: A nested spectral model for hurricane track forecasting. Mon. Wea. Rev., 120, 1628-1643.
Aberson, S. D., and M. DeMaria, 1994: Verification of a nested
barotropic hurricane track forecast model (VICBAR). Mon. Wea. Rev.,
Last modified: 9/11/96