Subseasonal tropical cyclone forecasts from two operational forecast models are verified for the 2017/18 and 2018/19 Southern Hemisphere cyclone seasons. The forecasts are generated using the ECMWF’s Medium- and Extended-Range Ensemble Integrated Forecasting System (IFS), and the Bureau of Meteorology’s seasonal forecasting system ACCESS-S1. Results show the IFS is more skillful than ACCESS-S1, which is attributed to the IFS’s greater ensemble size, increased spatial resolution, and data assimilation schemes. Applying a lagged ensemble with ACCESS-S1 increases forecast reliability, with the optimum number of lagged members being dependent on forecast lead time. To investigate the impacts of atmospheric assimilation at shorter lead times, comparisons were made between the Bureau of Meteorology’s ACCESS-S1 and ACCESS-GE2 systems, the latter a global Numerical Weather Prediction system running with the same resolution and model physics as ACCESS-S1 but using an ensemble Kalman filter for data assimilation. This comparison showed the data assimilation scheme used in the GE2 system gave improvements in forecast skill for days 8–10, despite the smaller ensemble size used in GE2 (24 members per forecast compared to 33). Finally, a multimodel ensemble was created by combining forecasts from both the IFS and ACCESS-S1. Using the multimodel ensemble gave improvements in forecast skill and reliability. This improvement is attributed to complementary spatial errors in both systems occurring across much of the Southern Hemisphere as well as an increase in the ensemble size.

Significance Statement

Advances in model development allow skillful forecasts of tropical cyclone activity beyond the normal limit of weather prediction (typically 14 days, or a two-week forecast) and into the “subseasonal” time frame. This is achieved by coupling high-resolution ensemble global forecast models to global ocean models. These subseasonal forecasts fill the gap between traditional weather forecasts and monthly climate outlooks. This study verifies two separate subseasonal cyclone forecasting system for the 2017/18 and 2018/19 cyclone seasons over the Southern Hemisphere. Both systems showed good skill in forecasting cyclone activity out to three weeks in advance. By combining the results of both models, forecast skill is further improved.

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