ACCESS-S2 seasonal forecasts of rainfall and the SAM–rainfall relationship during the grain growing season in south-west Western Australia

Abstract

South-west Western Australia (SWWA) is home to a world class grains industry that is significantly affected by periods of drought. Previous research has shown a link between the Southern Annular Mode (SAM) and rainfall in SWWA, especially during winter months. Hence, the predictability of the SAM and its relationship to SWWA rainfall can potentially improve forecasts of SWWA drought, which would provide valuable information for farmers. In this paper, focusing on the 0-month lead time forecast, we assess the bias and skill of ACCESS-S2, the Australian Bureau of Meteorology’s current operational sub-seasonal to seasonal forecasting system, in simulating seasonal rainfall for SWWA during the growing season (May–October). We then analyse the relationship between the SAM and SWWA precipitation and how well this is captured in ACCESS-S2 as well as how well ACCESS-S2 forecasts the monthly SAM index. Finally, ACCESS-S2 rainfall forecasts and the simulation of SAM are assessed for a case study of extreme drought in 2010. Our results show that forecasts tend to have greater skill in the earlier part of the season (May–July). ACCESS-S2 captures the significant inverse SAM–rainfall relationship but underestimates its strength. The model also shows overall skill in forecasting the monthly SAM index and simulating the MSLP and 850-hPa wind anomaly patterns associated with positive and negative SAM phases. However, for the 2010 drought case study, ACCESS-S2 does not indicate strong likelihoods of the upcoming dry conditions, particularly for later in the growing season, despite predicting a positive (although weaker than observed) SAM index. Although ACCESS-S2 is shown to skillfully depict the SAM–SWWA rainfall relationship and generally forecast the SAM index well, the seasonal rainfall forecasts still show limited skill. Hence it is likely that model errors unrelated to the SAM are contributing to limited skill in seasonal rainfall forecasts for SWWA, as well as the generally low seasonal-timescale predictability for the region.