ENSEMBLE FORECASTING OF TROPICAL CYCLONES

Principal Investigator: Sim D. Aberson

Collaborating scientist(s):
Morris Bender (NOAA/GFDL)
Robert Tuleya (NOAA/GFDL)
Objective: Evaluation of methods to improve operational forecasts of tropical cyclone motion and intensity.
Rationale: Researchers and forecasters are increasingly turning toward methods of ensemble forecasting in order to work toward improving operational forecasters. Uncertainty in the initial conditions grows with time until deterministic forecasts show no skill over forecasts from simply climatology and/or persistence models. However, by optimally perturbing model initial conditions using methods such as the breeding of growing modes used operationally at the National Centers for Environmental Prediction (NCEP), a set of forecasts which exemplifies the uncertainty in the model forecast and the range of possibilities of the forecast is presented. This allows for highly useful probabilistic forecasts instead of single deterministic ones. Diagnostics, such as the ensemble mean, ensemble spread, and bias information are clearly presented in this framework.
Method:

Ensemble forecasting of hurricane tracks and intensity using the Geophysical Fluid Dynamics Laboratory (GFDL) model will be used during the 1997 hurricane season to further quantify the value of using the bred growing modes from the NCEP ensemble forecasting program to assess the variability of forecasts.


Accomplishment: A set of almost 100 eleven-member ensembles have been run for cases during the 1996 and 1997 hurricane seasons in both the Atlantic and East Pacific basins. The control (GFCT) has been shown to provide forecasts better than those provided by perturbations (Fig. 1), and that the ensemble mean (GFMN) provides better forecasts than even the GFCT (Fig 2.). Rank distributions show that the forecasts tend to have a westward bias, and that about half of the forecasts do not fall within the envelope of possibilities presented by the ensemble forecasts (Fig 3.). Finally, the amount of ensemble spread seems to place an upper limit on the actual error, with those forecasts with large spread having the largest errors (Fig 4.). Results from the intensity study are similar, except that the bias is toward weaker forecasts. Two papers will be presented at the AMS Annual Meeting in Phoenix, AZ, in January, 1998, at the Numerical Weather Prediction Conference and at the Special Session on Tropical Cyclone Intensity Change.
Key references:

Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74, 2317-2330.

Bender, M. A., R. J. Ross, R. E. Tuleya, and Y. Kurihara: 1003: Improvements in tropical cyclone track and intensity forecasts using the GFDL initialization system. Mon. Wea. Rev., 121, 2046-2061.

Lord, S. J., 1993: Recent developments in troical cyclone track forecasting with the NMC global analysis and forecasting system. Preprints of the 20th Conference on Hurricanes and Tropical Meteorology, San Antonio, Amer. Meteor. Soc., 290-291.


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Last modified: 6/26/97