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The compound extreme weather event that impacted northern Queensland in February 2019 featured record-breaking rainfall, persistent high wind gusts and relatively cold day-time temperatures. This caused livestock losses numbering around 500,000 in the northwest Queensland Gulf region. In this study, we examine the livestock chill conditions associated with this week-long compound weather event and its potential for prediction from eleven world-leading sub-seasonal to seasonal (S2S) forecast systems. The livestock chill index combines daily rainfall, wind and surface temperature data. Averaged over the event week, the potential heat loss of livestock was in the moderate to high category, with severe conditions on the day of peak rainfall (5 February). Using calibrated forecasts from the Bureau of Meteorology's S2S forecast system, ACCESS-S1, a 1-week lead prediction showed a 20-30% probability of extreme livestock chill conditions over the northwest Queensland Gulf region, however the highest probabilities were located to the west of where the greatest livestock impacts were observed. Of the remaining ten S2S systems, around half predicted a more than 20% chance of extreme conditions, more than twice the climatological probability. It appears that the prediction accuracy arose from the skilful forecasts of extreme rainfall, as opposed to cold day-time temperature and strong wind forecasts. Despite a clear association between the observed extreme weather conditions and an active Madden-Julian Oscillation (MJO) event stalling in the western Pacific, the majority of 1-week lead S2S forecasts showed little indication of a slow-down in the MJO. As the livestock chill index was developed for southern Australian sheep, it may not be the best metric to represent the effects of exposure on tropical cattle breeds. Hence, this study draws attention to the need for tailored diagnostics that better represent the cold effects of summer tropical cyclones and tropical depressions on northern Australian livestock., (© 2022. The Author(s).)

The Indian Ocean Dipole (IOD) is the dominant mode of interannual variability over the tropical Indian Ocean (IO) and its future changes are projected to impact the climate and weather of Australia, East Africa, and Indonesia. Understanding the response of the IOD to a warmer climate has been largely limited to studies of individual coupled general circulation models or multi-model ensembles. This has provided valuable insight into the IOD's projected response to increasing greenhouse gases but has limitations in accounting for the role of internal climate variability. Using the Community Earth System Model Large Ensemble (CESM-LE), the IOD is examined in thirty-five present-day and future simulations to determine how internal variability influences properties of the IOD and their response to a warmer climate. Despite small perturbations in the initial conditions as the only difference between ensemble members, significant relationships between the mean state of the IO and the IOD arise, leading to a spread in the projected IOD responses to increasing greenhouse gases. This is driven by the positive Bjerknes feedback, where small differences in mean thermocline depth, which are caused by internal climate variability, generate significant variations in IOD amplitude, skewness, and the climatological zonal sea surface temperature gradient.

This paper highlights some caveats in using composite analyses to form physical hypotheses on the associations between environmental variables. This is illustrated using a specific example, namely the apparent links between heat waves (HWs) and sea surface temperatures (SSTs). In this case study, a composite analysis is performed to show the large-scale and regional SST conditions observed during summer HWs in Perth, southwest Australia. Composite results initially point to the importance of the subtropical South Indian Ocean, where physically coherent SST dipole anomalies appear to form a necessary condition for HWs to develop across southwest Australia. However, sensitivity tests based on pattern correlation analyses indicate that the vast majority of days when the identified SST pattern appears are overwhelmingly not associated with observed HWs, which suggests that this is definitely not a sufficient condition for HW development. Very similar findings are obtained from the analyses of 15 coupled climate model simulations. The results presented here have pertinent implications and applications for other climate case studies, and highlight the importance of applying comprehensive statistical approaches before making physical inferences on apparent climate associations.

In the late twentieth century, the sub-thermocline waters of the southern tropical and subtropical Indian Ocean experienced a sharp cooling. This cooling has been previously attributed to an anthropogenic aerosol-induced strengthening of the global ocean conveyor, which transfers heat from the subtropical gyre latitudes toward the North Atlantic. From the mid-1990s the sub-thermocline southern Indian Ocean experienced a rapid temperature trend reversal. Here we show, using climate models from phase 5 of the Coupled Model Intercomparison Project, that the late twentieth century sub-thermocline cooling of the southern Indian Ocean was primarily driven by increasing anthropogenic aerosols and greenhouse gases. The models simulate a slow-down in the sub-thermocline cooling followed by a rapid warming towards the mid twenty-first century. The simulated evolution of the Indian Ocean temperature trend is linked with the peak in aerosols and their subsequent decline in the twenty-first century, reinforcing the hypothesis that aerosols influence ocean circulation trends.

Since the late 1970s, Southern Hemisphere semi-arid regions such as southern-coastal Chile, southern Africa, and southeastern Australia have experienced a drying trend in austral autumn, predominantly during April and May. The rainfall reduction coincides with a poleward expansion of the tropical belt and subtropical dry zone by around 2°-3° in the same season. This has raised questions as to whether the regional rainfall reductions are attributable to this poleward expansion. Here we show that the impact of the poleward subtropical dry-zone shift is not longitudinally uniform: a clear shift occurs south of Africa and across southern Australia, but there is no evidence of a poleward shift in the southern Chilean sector. As such, a poleward shift of climatological April-May rainfall can explain most of the southeastern Australia rainfall decline, a small portion of the southern Africa rainfall trend, but not the autumn drying over southern Chile.