Kerryn Hawke

The Indian Ocean Dipole (IOD) and the El Niño Southern Oscillation (ENSO) are key modes of natural climate variability which co-occur and influence regional rainfall in Australia. This study evaluates the skill of 60 CMIP6 global climate models, including 16 pre-selected models for dynamical downscaling, in simulating the characteristics of IOD & ENSO, their inter-relationship, and their combined and independent influences on Australian rainfall. Focusing on the austral winter-spring season (JJASON) during 1950–2014, we use partial correlation & regression techniques to disentangle the influence of ENSO from the IOD-rainfall relationship and vice versa. Compared with observations, most CMIP6 models overestimate IOD & ENSO variability, frequencies of IOD & co-occurring IOD-ENSO events, and the influence of ENSO on IOD. More models reasonably capture the observed independent IOD-rainfall correlation in Southern (SA) and Southeastern (SEA) Australia than observed combined correlation, while in Eastern (EA) and Northern (NA) Australia, more models reasonably reproduce observed combined ENSO-rainfall correlation than observed independent one. A similar result emerges in regression analyses, but it is more pronounced for ENSO in EA and NA than for IOD in SA and SEA. The ranking of CMIP6 models based on four statistical skill metrics shows that each model demonstrates distinct skill variations, highlighting the importance of skill-specific analyses when evaluating relationships between IOD/ENSO and Australian rainfall. Our results emphasise the need to consider both combined and independent effects of IOD/ENSO on Australian rainfall, and our ranking of the pre-selected CMIP6 models for dynamical downscaling will be helpful to better understand biases in these regional projections for Australia.

Southwest Western Australia (SWWA), with its Mediterranean climate, has undergone a persistent drying trend since the 1970s. As such, it is often referred to as the “canary in the coal mine” of climate change. This review examines drivers of SWWA rainfall and rainfall decline, focusing on the cool season (April to October) when most rainfall occurs, and includes the influence of weather systems, modes of natural climate variability, and land‐use change. While paleo‐climate evidence shows that similar declines have occurred in the past, the current trend is at the upper end of natural climate variability, indicating an increasing influence from anthropogenic climate change. The reasons for this drying trend are complex, with research linking decreasing SWWA rainfall to a strengthening subtropical ridge and more frequent positive phases of the Southern Annular Mode resulting in fewer winter fronts reaching the region. Decreasing baroclinity has been associated with a decrease in cold front rainfall amounts and a possible shift toward increased post‐frontal showery activity. While the El Niño Southern Oscillation and Indian Ocean Dipole (IOD) have shown weak historical links to SWWA rainfall, recent trends toward more frequent positive IOD may change this association. Finally, the influence of 20th–21st century land use changes has also been identified as a contributing factor to the rainfall decline. Given the complex interplay of these drivers and the increasing influence of anthropogenic climate change on the region's rainfall, a holistic approach is becoming crucial. We provide multiple avenues for further research.

This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change

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.

Completing a PhD is difficult. Add a major earthquake sequence and general stress levels become much higher. Caring for some of the nonacademic needs of doctoral scholars in this environment becomes critical to their scholarly success. Yet academic supervisors, who are in the same challenging environment, may already be stretched to capacity. How then do we increase care for doctoral scholars? While it has been shown elsewhere that supportive and interactive department cultures reduce attrition rates, little work has been done on how exactly departments might create these supportive environments: the focus is generally on the individual actions of supervisors, or the individual quality of students admitted. We suggest that a range of actors and contingencies are involved in journeying toward a more caring collective culture. We direct attention to the hybridity of an emerging caring collective', in which the assembled actors are not only students' and staff', but also bodies, technologies, objects, institutions, and other nonhuman actors including tectonic plates and earthquakes. The concept of the hybrid caring collective is useful, we argue, as a way of understanding the distributed responsibility for the care of doctoral scholars, and as a way of stepping beyond the student/supervisor blame game.