Tropical forcing of Australian extreme low minimum temperatures in September 2019

We explore the causes and predictability of extreme low minimum temperatures (T-min) that occurred across northern and eastern Australia in September 2019. Historically, reduced T-min is related to the occurrence of a positive Indian Ocean Dipole (IOD) and central Pacific El Nino. Positive IOD events tend to locate an anomalous anticyclone over the Great Australian Bight, therefore inducing cold advection across eastern Australia. Positive IOD and central Pacific El Nino also reduce cloud cover over northern and eastern Australia, thus enhancing radiative cooling at night-time. During September 2019, the IOD and central Pacific El Nino were strongly positive, and so the observed T-min anomalies are well reconstructed based on their historical relationships with the IOD and central Pacific El Nino. This implies that September 2019 T-min anomalies should have been predictable at least 1-2 months in advance. However, even at zero lead time the Bureau of Metereorolgy ACCESS-S1 seasonal prediction model failed to predict the anomalous anticyclone in the Bight and the cold anomalies in the east. Analysis of hindcasts for 1990-2012 indicates that the model's teleconnections from the IOD are systematically weaker than the observed, which likely stems from mean state biases in sea surface temperature and rainfall in the tropical Indian and western Pacific Oceans. Together with this weak IOD teleconnection, forecasts for earlier-than-observed onset of the negative Southern Annular Mode following the strong polar stratospheric warming that occurred in late August 2019 may have contributed to the T-min forecast bust over Australia for September 2019.

Automated summary

The study explores the relationship between extreme low minimum temperatures in northern and eastern Australia in September 2019 and the positive Indian Ocean Dipole and central Pacific El Nino events. While historically there is a strong connection between these events and reduced minimum temperatures, the study found that forecasting such anomalies remains challenging due to uncertainties and model weaknesses, leading to inaccuracies in predicting anomalous weather events.