Picture: Flooded village. Credit: Pok Rie (Pexels).

The newly formulated Attribution and Risk research program is by its very nature focused on the impacts of weather and climate on our society. A key piece of research on business risk and the emergence of climate risk perfectly highlighted this. Working with authors from business faculties, private industry, a consultant and climate scientists, CLEX researchers produced a paper in Nature Climate Change that outlined where climate model projections are useful, where their use can be misleading, and where use is well beyond what climate modellers would deem legitimate. Specifically, they separated the valuable and robust projections of average temperature at sub-continental scales from the projections of extremes, and in particular rainfall extremes at sub-regional scales, which have negligible value in assessing business risk. The paper prompted significant conversation in financial and corporate media outlets and saw Andy Pitman gave a briefing to World Business Council for Sustainability Development, the technical team of the US Senate Committee on Banking, Housing, and Urban Affairs, a presentation to Lazard Asset Management, New York and found its way into a letter to the US Federal Reserve by some conservative senators who seemed to misunderstand its implications. The researchers kindly corrected these misapprehensions.

Andy wasn’t the only person to engage closely with business and financial groups. Lisa Alexander gave a presentation to UNEP Finance Initiative on Using climate observations and models in assessments of risk: challenges and opportunities. There were more than 180 financial institutions and investors logged in for this talk.

Another piece of fascinating research led by associate investigator Negin Nazarian brought the risk component of our research down to the very personal level. Dr Nazarian and her team used Fitbit watches to estimate thermal comfort for individuals and recognise the changes to core body temperature that lead to heat stress. The research is part of Project Coolbit, an ongoing investigation that aims to create a personalised approach to assessing thermal comfort and preventing health complications during extreme heat events. It’s research that could not only save the lives of individuals but may also change the way we design future cities.

Understanding what causes those extreme heat events and how they might change, so that we can forecast them well in advance or adapt to future changes is an important part of understanding and responding to risk. However, much of this research has been done on extremes that may occur as frequently as every year, on average when it is usually rarer events that cause the most damage. CLEX researchers used statistical techniques to investigate changes in extreme climate events that currently occur, on average, only once every 20 years. These techniques are applied to data related to heat, rainfall, drought and conditions conducive to bushfires and thunderstorms from detailed climate modelling commissioned by NSW and ACT Governments. Overall, the results showed an increase in the frequency of extreme conditions across the majority of southeast Australia by the end of the 21st century. This was true for all types of extremes considered but was especially conclusive for heat extremes and conditions conducive to thunderstorms. The study is an exemplar of the use of detailed climate modelling to assess future changes in potentially damaging climate extremes and provides information relevant to planning for managing future climate risks.

In a study led by PhD student Roseanna McKay, we looked at what caused maximum temperatures in Australia during spring to have exceeded historic records on multiple occasions in recent years. Understanding what drives these high temperatures may lead to better forecasts of extreme heat in the future. Cyclonic circulation southwest of Australia and an atmospheric wave train with anticyclonic circulation over southern Australia were important features in these events. While the Indian Ocean Dipole was not active, the wave train appeared to come from the tropical Indian Ocean and was particularly important in two events. Interestingly, the model ensemble members in a seasonal prediction system that forecast the highest Australian maximum temperatures also were best at forecasting these atmospheric circulation features. The research also suggested that models might underestimate future extreme spring heat events, a factor that should be assessed in future seasonal prediction models.

Continuing the story of heat impacts, we worked with the Drought research program to examine the role of climate change and other factors in the 2019/2020 Black Summer bushfires. The study concluded that improving the methods used to adapt to the now inevitable increase in fire risk here in Australia, while also pursuing urgent global climate change mitigation efforts were the best strategy for limiting further increases in fire risk. The authors warned fire disasters like the Black Summer are made worse by human-caused climate change in multiple ways; some of which are very well understood and some where more research is needed. These combined climate change impacts mean that bushfires are expected to rapidly become even more severe in southeast Australia.

Another of the impacts of that black summer felt right along the east coast of Australia was the significant deterioration in air quality. CLEX researchers and colleagues quantified the air quality impact in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute a baseline time series of nitrogen dioxide (NO2), ozone (O3), carbon monoxide CO and particulate matter with diameter < 2.5μm (PM2.5), based on a 19 year, detrended training dataset. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6-343.) excess deaths and 3490.0 (95% CI 1325.9-5653.5) additional hospitalisations were likely as a result of PM2.5 and O3 exposure in Victoria and NSW.

The other side of climate extremes can be found in extreme rainfall events. Work led by PhD student Kim Reid for the Weather and Climate Interactions RP examining the impact of atmospheric rivers on extreme rainfall events also has implications for attribution and risk. She used an atmospheric river Identification algorithm developed at the University of Melbourne to study Atmospheric River impacts (Reid et al. 2020); station rainfall data provided as a part of a collaboration with the National Institute for Water and Atmospheric Research, New Zealand; and flooding impact estimates from the Insurance Council of New Zealand. Together this information revealed that nine out of ten of the most expensive floods in New Zealand (2007-2017) occurred during an Atmospheric River event, and seven to all ten of the top ten most extreme rainfall events at eleven different locations occurred during Atmospheric Rivers. Atmospheric river extreme rainfall is easier to predict than other types of extreme rainfall. Indeed, some researchers have speculated that because of the connection between Atmospheric Rivers and the Madden Julian Oscillation, in the future, useful multi-week predictions of heightened Atmospheric River rainfall risk could be possible.