A Probabilistic Tropical Cyclone Track Forecast Scheme Based on the Selective Consensus of Ensemble Prediction Systems

Selective consensus and a grand ensemble based on an ensemble prediction system (EPS) have been found to be effective in improving deterministic tropical cyclone (TC) track forecasts, while little attention has been paid to quantitative applications of the forecast uncertainty information provided by EPSs. In this paper the forecast uncertainty information is evaluated for two operational EPSs and their grand ensemble. Then, a probabilistic TC track forecast scheme is proposed based on the selective consensus of the two EPSs; this scheme is composed of member picking, mean track shifting, and probability ellipses. The operational EPSs are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the National Centers for Environmental Prediction (NCEP-GEFS). Evaluation exhibits that the hit ratios of ECMWF-EPS are above 80% for the 70% probability ellipses at all lead times until 120 h and are used in the proposed scheme. The other components of the proposed scheme are about picking potentially good EPS members. A picking ratio of 1/2 is found to be the best choice, and the member-picking technique is used for the grand ensemble but only for lead times out to 48 h. For lead times longer than 48 h, all of the grand ensemble members are used in obtaining the mean track. The effectiveness of the proposed scheme shows a 10% improvement in the mean track forecast errors over the grand ensemble and a 4.5% improvement in the hit ratio of 70% probability ellipses over the ECMWF-EPS at 24 h, demonstrating its good potential to be applied in operations.