Short-term Forecasts of TC Tracks over the Western Pacific Using the Multimodel Ensemble Approach

Abstract

Based on the TC track ensemble forecast data of China Meteorological Administration (CMA), European Centre for Medium-Range Weather Fore-casts (ECMWF), Japan Meteorological Agency (JMA), and United Kingdom Met Office (UKMO) in the TIGGE dataset during the period from 1 May until 31 August 2009, the 24h~72h multimodel ensemble forecasts of the TC tracks over the western Pacific have been conducted by using the multimodel superensemble approaches including the multimodel ensemble mean (EMN), the bias-removed ensemble mean (BREM), and multimodel superensemble in terms of the weighted bias-removed ensemble mean (WEM). A terrifying typhoon Morakot which brought record-breaking rainfalls over Taiwan and caused huge damages in both Taiwan and mainland China was chosen for case study. The results show that forecast skills of the aforementioned four models are quite different for 24h~72h forecasts. The weighted bias-removed ensemble mean and bias-removed ensemble mean reduce the TC track errors considerably. Both of the WEM and BREM techniques show a significant improvement on the forecast skill of TC tracks against the best individual model forecast and the EMN forecast. The multimodel superensemble in terms of the WEM shows the best performance in 24h~72h forecast of TC tracks over the western Pacific. In addition, the multimodel superensemble in terms of the weighted average of different individual model forecasts has better performance than the bias-removed ensemble mean with equal weights of all independent forecasts.