ENSEMBLE FORECASTING OF TROPICAL CYCLONES

Principal Investigator: Sim D. Aberson

Collaborating scientist(s):
Craig Bishop (PSU)
Sharan Majumdar (PSU)
Brian Etheron (PSU)
Kerry Emanuel (MIT)
Objective:
Evaluation of methods to improve operational forecasts of tropical cyclone motion and intensity, and in data assimilation.
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. The perterbations can also aide in the development of flow-dependent data assimilation techninques.


Method:
Ensemble forecasting of hurricane tracks using the Beta and advection model will be used during the 1999 hurricane season to quantify the value of using the bred growing modes from the NCEP ensemble forecasting program to assess the variability of forecasts. Ensemble forecasts from the VICBAR model using bred-mode and related techniques will help to assess the potential of ensemble track forecasting and flow-dependent data assimilation. NCEP and ECMRWF global model emsembles will be investigated for skill in predicting tropical cyclogenesis.
Accomplishment:
A set of almost 100 eleven-member GFDL ensembles have been run for cases during the 1996 and 1997 hurricane seasons in both the Atlantic and East Pacific basins. The control has been shown to provide forecasts better than those provided by perturbations, and that the ensemble mean provides better forecasts than even the GFCT. Rank distributions show similar results have been obtained with the BAM model in the Atlantic in 1998, and that less than a quarter of the forecasts do not fall within the envelope of possibilities presented by the ensemble forecasts. 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 . Initial results from VICBAR ensembles show even greater ability to span the truth. Global ensembles have been shown to correctly forecast more than 3/4 of all cases of cyclogenesis, with very few false alarms, as far as seven days in advance. This is in sharp contrast to the lack of skill of high-resolution deterministic models.


Key references:

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

Aberson, S.D., and M. DeMaria, 1994: Verification of a nested barotropic hurricane track forecast model (VICBAR) Mon. Wea. Rev., 122, 2804-2815.

Aberson, S.D., 1999: The depth of the Environmental Steering layer of Tropical Cyclones in the North Atlantic Basin, Submitted to Mon. Wea. Rev..

Hautekamer, P.L., and J.L. Mitchell, 1998: Data Assimilation using an ensemble Kalman filter technique, Mon. Wea. Rev., 126, 796-811.

Bender, M. A., R. J. Ross, R. E. Tuleya, and Y. Kurihara: 99: 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: 5/24/99