Ensemble forecasting of tropical cyclone motion using a barotropic model. Part I: Perturbations of the environment

The technique of ensemble forecasting is applied to the problem of tropical cyclone motion prediction. Three methods of generating perturbations for the environmental flow, Monte Carlo forecast (MCF), lagged-average forecast (LAF), and the breeding of growing modes (BGM), are tested with a barotropic model using 66 cases from the Tropical Cyclone Motion (TCM-90) Experiment. For the MCF, the ensemble mean forecast is almost identical to that without any perturbation. The other two methodologies are verified both under the perfect model assumption and using the best tracks. On average, in about half of the cases improvement in forecast can be demonstrated in the former verification. A high degree of correlation (with linear correlation coefficient >0.9) is also found between the spread of the ensemble and the root-mean-square forecast error. In the best-track verification, improvement in forecasts can also be obtained in 36% (42%) of all the cases using the LAF (BGM) technique. The spread-skill correlation is still significant (correlation coefficients vary from similar to 0.4 to 0.7 for different forecast times). An examination of the synoptic how associated with cases in which the forecast is improved suggests some favorable conditions for the application of ensemble forecasting. These include a tropical cyclone (TC) making a transition from one synoptic region to another, an apparent break in the subtropical ridge (STR), a rapid strengthening/weakening of the STR, recurvature of a TC, and multiple-TC situations.