This research has the potential to create RCM emulators that can efficiently downscale multiple variables simultaneously, while preserving the physical relationships between them.
Almost all catastrophic events are the consequence of multiple drivers acting together.
A multivariate event occurs when several hazards affect the same region at the same time.
A spatially compounding event occurs when several impacts occur at the same time but at different locations.
A temporally compounding event occurs when a series of hazards affects the same region, exacerbating the impact of any of the individual events.
A preconditioned compound event occurs when the impact of a hazard is exacerbated by pre-existing conditions.
We are conducting research to determine if we can forecast changes in the probability of extreme rainfall events associated with atmospheric rivers 2-6 weeks ahead.
Further understanding of the role of clouds may improve the knowledge of local atmosphere-ocean interactions, aiding the forecasting of coral bleaching events.
La Niña is an important cause of rainfall variability of Australia. A multi-year La Niña event can be particularly important for some climate risks. Some climate models are indicating that La Niña may continue for a third year through spring and summer 2022-23, increasing the chances of more rain and flooding.
By bringing together researchers focussed on the large-scale modes of climate variability with researchers investigating weather and land surface processes, our goal is to improve the regional predictions of how rainfall extremes will change in the future.