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.
Sim Aberson administrative
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Last modified: 5/24/99