This year, perhaps more than ever before, decision-makers, emergency services, health providers and threatened communities have needed fast, reliable information to understand what鈥檚 happening. And beyond that, they have needed high-powered modelling to get a sense of what is yet to come.

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That鈥檚 where supercomputers come in. Australia鈥檚 high-performance research computing infrastructure is led by two centres: the (NCI Australia) in Canberra and the in Perth.

NCI Australia is home to Gadi, the most powerful supercomputer in the southern hemisphere, which can do in an hour what would take your average desktop PC around 35 years running flat out. The Pawsey centre hosts the Nimbus cloud, which is specially designed for data-intensive research work in cutting-edge fields such as space science.

Both centres operate around the clock every day of the year. Even without a crisis, they process unimaginable quantities of data to deliver analysis and forecasts for decision-makers across the nation. To take one example, NCI鈥檚 routine work for helps to identify soil and coastal erosion, crop growth, water quality and changes to cities and regions.

Supercomputing behind the scenes

By their nature, high-performance research computers operate mostly behind the scenes. They provide infrastructure that is less visible but no less important than a ship or a telescope, and the expertise to help researchers use it.

When Australian government agencies need to make decisions to respond to a crisis like the bushfires or COVID-19, they draw on backed by high-performance computing and data infrastructure.

Last summer, satellite images shocked the world with detailed and strangely beautiful views of the size of global weather patterns. Our Kiwi colleagues woke to apocalyptic skies, tipped off beforehand by Australian and NZ collaborations with Japan鈥檚 Himawari-8 and -9 weather satellite mission.

Research satellites like the European with a wider global view continued to track the plume as it circled the planet. NCI Australia hosts a to support Europe鈥檚 Copernicus Earth observation program.

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Data-driven models running on supercomputers can provide earlier and more accurate warning of firestorms, floods, hailstorms, cyclones and other extremes. Better warnings give emergency services crucial hours that save lives and property.

Both national facilities are to support researchers in Australia in the fight against COVID-19.

With the Gadi supercomputer, NCI is providing the equivalent of more than 4,500 years of computer time to support three research groups. Pawsey is providing access to more than 1,100 desktop鈥檚 worth of computing power on the newly deployed for researchers across five projects.

National infrastructure working at scale

The Australian Government鈥檚 National Collaborative Research Infrastructure Strategy () has invested A$70 million in each centre for upgrades to ensure the facilites can keep up with Australian research across all scientific domains. NCI鈥檚 Gadi supercomputer is about nine times more powerful than its predecessor, while the first phase of Pawsey鈥檚 upgrade has already delivered ten times more cloud storage and boosted network capabilities fivefold.

Reliable, collaborative facilities like NCI and Pawsey are essential to develop and improve immensely complex global and local models and prediction systems used by national and state governments.

The NCI and Pawsey systems support much more than climate and weather data and pandemic modelling. Other projects support gene sequencing, population mapping, transmission and containment modelling, and global economic predictions.

Scale, collaboration and speed

Scaling up our research computing capacity is important to meet the challenges of ever-growing amounts of research data. Collaboration makes it possible to access the best expertise. Speed is essential to meet the urgent demands of decision makers.

Supercomputers connected to massive data systems and supported by expert staff can yield crucial insights at scale, quickly enough to help our agencies identify and respond to crises. Faster processing also means researchers can identify and model trends that would otherwise go unnoticed, but which require early intervention.

Supercharging the relevant science can deliver real economic, environmental and public health outcomes. The need for informed crisis response does not look like it will go away any time soon.

, Professor and Director, NCI Australia, and , Executive Director, Pawsey Supercomputing Centre,

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But how does this work, and why do governments act upon such predictions?

Professors James McCaw and Jodie McVernon of the University of Melbourne / Doherty Institute provided an insight into their COVID-19 modelling to .

Professor McCaw said “they put some ‘very scary numbers’ to the Government early on, and they were not dismissed. We don’t have an overwhelmed hospital system yet, and we may well never have one if we continue to base our responses on the best available data.”

Professors McCaw and McVernon both feature in the 今日吃瓜 Maths Delivers video: providing an insight into the mathematical modelling of susceptibility, infection spread and recovery of disease in populations.

James McCaw is a mathematical biologist and infectious diseases epidemiologist with a PhD in theoretical physics from the University of Melbourne. 聽He holds a joint appointments at the University of Melbourne in Mathematics and Statistics within the Faculty of Science (alongside his role as Associate Dean – Research) and at the University’s School of Population and Global Health

Professor McCaw’s interests span from modelling host-pathogen-drug dynamics, focusing on influenza and malaria, to developing public health control strategies for emerging and re-emerging infectious diseases. One of his current projects is聽Household Transmission Investigation for Novel Coronavirus (COVID-19) Infection Aka Ffx Full Implementation.

Professor Jodie McVernon is a physician with subspecialty qualifications in public health and vaccinology based at the Doherty Institute. Jodie possesses extensive expertise in clinical vaccine trials, epidemiologic studies and mathematical modelling of infectious diseases. These focus on the application of a range of cross-disciplinary methodological approaches including mathematical and computational models, to synthesise insights from basic biology, epidemiological data and sociological research. Such models advance understanding of the observed epidemiology of infectious diseases and inform understanding of optimal interventions for disease control.