This study illustrates how future uncertainty of climate models in predicting hot extremes is controlled by two factors, both related to amplification of hot extremes through land-atmosphere interactions
Overall, the inaugural Australian Countdown finds that Australia is vulnerable to the impacts of climate change on health, and that policy inaction in this regard threatens Australian lives. In a number of respects, Australia has gone backwards and now lags behind other high income countries such as Germany and the United Kingdom. Examples include the persistence of a very high carbon-intensive energy system in Australia, and a slow transition to renewables and low-carbon electricity generation.
Together with a recent paper estimating evaporation and transpiration from the land surface, this paper brings the community a step closer to observationally constrained estimates of the historical land surface energy and water budgets
In this review paper, researchers contextualise the broad and seemingly disparate range of attempts to define and address model dependence within climate model ensembles, and offer concrete advice on how best to avoid overconfidence.
Researchers develop a novel algorithm that should enable improved prediction of the function of global ecosystems in a warming climate.
By employing an atmosphere-only version of ACCESS, CLEX researchers generated multiple sea surface temperature patterns of the same El Nino and La Nina events, and assessed how this influenced heatwaves over various Australian regions.
New research in Nature Climate Change suggests droughts may not increase as a result of climate change. This finding resulted from researchers investigating an apparent climate model contradiction that saw climate change projections of the 21st Century produce increased droughts along with more run-off and a greening of the landscape
Urban Climate and Energy Model (UCLEM) is a new climate model focused on Australian conditions that integrates energy use and human behaviour to generate accurate representations of urban climates.
This paper shows that many models overestimate the interaction between hot and dry conditions in wet regions and therefore overamplify heat extremes. The study points to necessary model improvement to increase confidence in future projections of heat extremes.
The MAAT framework can be used to systematically run multiple model simulations to explore how different underlying model assumptions, hypotheses and parameters lead to predicted model behaviour and isolate the causes of model divergence.