Error-Estimation Ensemble Method in the Forecasting of Tropical Cyclone Tracks.

ABSTRACT Pan, Y.; Chen, Y.-P.; Yuan, J.-Y.; Liu, Y., and Xu, Z.-S., 2018. Error-Estimation Ensemble method in the forecasting of tropical cyclone tracks. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 771–775. Coconut Creek (Florida), ISSN 0749-0208. Tropical cyclones pose a great threat to coastal areas and accurate forecasting of their tracks is important for reducing and preventing coastal disasters. Multi-mode super-ensemble method was proposed to make full use of the forecasted tracks from different forecasting institutes. This paper proposed a modified multi-mode super-ensemble method, namely Error-Estimation Ensemble method, to overcome the shortcomings of traditional multi-mode super-ensemble method. The hypothesis, methodology and implementation of Error-Estimation Ensemble method are described. The EEE hindcast results of two typical tropical cyclones and all tropical cyclones that affects China coast are compared to those of four forecasting institutes. The comparison show that the EEE method reduces both the mean error and root-mean-square error of tropical cyclone track forecast, indicating that EEE method has better prediction accuracy and reliability. Discussions on present performance of EEE method and future works are present at last. [ABSTRACT FROM AUTHOR]