Abstract:

The basic principles of two methods of a Breeding of growing mode (BGM) and an ensemble transform Kalman filter (ETKF) for the generation of initial perturbation value were introduced and compared with each other. Based on the GRAPES-Meso model, two mecoscale ensemble forecast systems were established, i.e. a GRAPES-BGM and a GRAPES-ETKF. Using the Sepat typhoon event as a case study, the prediction accuracy of two methods for precipitation was compared. The results indicate that two systems can catch the information of precipitation and improve the sever rainfall events. The accuracy of ensemble forecast is higher than that of control forecast, especially for falling area and intensity of the heavy rain to some extent. The talagrand distribution of the ETKF scheme is better than that of the BGM scheme in terms of the poststamps and other verification, while the reverse is true in terms of the TS score of precipitation. Furthermore, the BGM scheme is easy and convenient for weather forecast service.

Key words: Ensemble forecast, Breeding of growing mode (BGM), Ensemble transform Kalman