Abstract

Sub-seasonal 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 Forecast System (IFS), and the Bureau of Meteorology 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 leadtime. To investigate the impacts of atmospheric assimilation at shorter leadtimes, comparisons were made between the Bureau’s ACCESS-S1 and ACCESS-GE2 systems, the latter a global NumericalWeather 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 multi-model ensemble was created by combining forecasts from both the IFS and ACCESS-S1. Using the multi-model 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.

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