The Forecast Skill of Tropical Cyclone Genesis in Two Global Ensembles

Abstract

Abstract Tropical cyclone (TC) genesis forecasts during 2018–20 from two operational global ensemble prediction systems (EPSs) are evaluated over three basins in this study. The two ensembles are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the MetOffice in the United Kingdom (UKMO-EPS). The three basins include the northwest Pacific, northeast Pacific, and the North Atlantic. It is found that the ensemble members in each EPS show a good level of agreement in forecast skill, but their forecasts are complementary. Probability of detection (POD) can be doubled by taking all the member forecasts in the EPS into account. Even if an ensemble member does not make a hit forecast, it may predict the presence of cyclonic vortices. Statistically, a hit forecast has more nearby disturbance forecasts in the ensemble than a false alarm. Based on the above analysis, we grouped the nearby forecasts at each model initialization time to define ensemble genesis forecasts, and verified these forecasts to represent the performance of the ensemble system. The PODs are found to be more than twice that of the individual ensemble members at most lead times, which is about 59% and 38% at the 5-day lead time in UKMO-EPS and ECMWF-EPS, respectively; while the success ratios are smaller compared with that of the ensemble members. In addition, predictability differs in different basins, and genesis events in the North Atlantic basin are the most difficult to forecast in EPS, and its POD at the 5-day lead time is only 46% and 23% in UKMO-EPS and ECMWF-EPS, respectively. Significance Statement Operational forecasting of tropical cyclone (TC) genesis relies greatly on numerical models. Compared with deterministic forecasts, ensemble prediction systems (EPSs) can provide uncertainty information for forecasters. This study examined the predictability of TC genesis in two operational EPSs. We found that the forecasts of ensemble members complement each other, and the detection ratio of observed genesis will be doubled by considering the forecasts of all members, as multiple simulations conducted by the EPS partially reflect the inherent uncertainties of the genesis process. Successful forecasts are surrounded by more cyclonic vortices in the ensemble than false alarms, so the vortex information is used to group the nearby forecasts at each model initialization to define ensemble genesis forecasts when evaluating the ensemble performance. The results demonstrate that the global ensemble models can serve as a valuable reference for TC genesis forecasting.