Ensemble forecasting of tropical cyclone motion using a barotropic model. Part II: Perturbations of the vortex

In Part I of this study, the technique of ensemble forecasting is applied to the problem of tropical cyclone motion prediction by perturbing the environmental flow. In this part, the focus is shifted to perturbation of the vortex structure. The same barotropic model as in Part I is used to predict 66 cases from the Tropical Cyclone Motion (TCM-90) experiment. Two series of experiments are performed. The first consists of the Monte Carlo forecast for the vortex (MCFV), lagged-average forecast for the vortex (LAFV), and breeding of growing modes for the vortex (BGMV). These are applied to the original analyses without adding any synthetic vortex, and their techniques of generating perturbations are similar to those in Part I. The second series adopts a technique that simulates uncertainties in estimating the synthetic vortex structure. The effect of adding an initial position error (IPER) is first explored. Then a set of four experiments (BETA) is carried out to study the consequence of perturbing the persistence vector and/or various parameters used to generate the β gyres in a spun-up vortex. Response of the model forecasts to random noise added in the experiment MCFV is found to be low, and the ensemble mean is thus always close to the control forecast. The situation is similar when the rms size of the noise is slightly varied, or when its characteristic length scale is changed. The skill of the IPER experiment also differs little from the control forecast. The remaining experiments other than the MCFV and IPER show a similar average skill to one another when verified both under the perfect model assumption (PMA) and by the best tracks. In the PMA verification, potential improvement over the control forecast can be obtained by the ensemble mean in the LAFV, BGMV, and some sets of the BETA experiments. However, some failure cases are found in the LAFV and BGMV experiments when the vorticity center cannot be well identified during the model integration. When compared with the best tracks, a portion of the cases can still outperform the control in the LAFV, BGMV, and BETA experiments. Since different control forecasts are used in different experiments, the forecast errors are scaled to the same benchmark before they are compared. It is found that among the BETA experiments, the configuration with the best performance is to perturb the parameters for generating the β gyres and persistence vector simultaneously. It can outperform LAFV after 48 h and has comparable performance with BGMV. This set of BETA ensemble may therefore be suitable for substituting BGMV when a synthetic vortex is necessary. Another implication is that since the persistence vector represents an improved large-scale flow, potential skill should exist for combining the perturbed β gyres with the environmental perturbations used in Part I.