This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: A revolution in forecasting natural disasters is underway, say researchers in Switzerland who are training AI models using vast troves of NASA climate data to produce potentially lifesaving data at lightning speed. They are feeding the NASA data archive into one of the world's most powerful supercomputers so artificial intelligence can speed up and expand vital weather and climate forecasting, and spot patterns scientists could not have seen.
AI models are increasingly used in weather and climate forecasting and for early detection of natural hazards. As well as speed, they carry the promise of spotting previously imperceptible patterns in satellite and other data, potentially making it possible to flag disasters in advance, like Nepal's devastating flood, which last month left thousands dead or missing. But training such AI models requires vast amounts of high-quality climate and Earth observation data, and significant computing power.
Researchers at Switzerland's Federal Institute of Technology Zurich (ETH) say they now have both, after copying around 100 petabytes of publicly available NASA data onto servers adjacent to one of the world's most powerful supercomputers, known as Alps. "This is a huge scientific opportunity," said Thomas Schulthess, an ETH computational physics professor and head of the Swiss National Supercomputing Centre (CSCS) in the southern city of Lugano. Standing in front of rows of what look like giant filing cabinets that contain Alps, he told he was excited to have all of NASA's climate data plugged directly into the machine.
"It's really enabling scientists to do things we would not even have thought of before," he said. It took approximately a year to copy the roughly 6 billion NASA files onto servers connected to the supercomputer, said Reto Knutti, a climate physics professor who heads ETH's Center for Climate Systems Modeling (C2SM). That is equivalent to around 20 million feature-length films in terms of data volume, or around a million times the storage on a typical computer, he told AFP.
Now the researchers are using the mass of information to develop AI models that can speed up and expand vital weather and climate forecasting. "Data is essentially everything," Knutti said. "The next step will be making sense of the data." That is where the proximity to the massive computing power of Alps comes in, Schulthess said, nodding to the clusters of servers humming loudly just meters from the supercomputer.
"It matters whether you can move the data within a few seconds or whether you have to wait days for the data to come," he said. New AI-generated statistical models are far faster than the traditional process of using mathematical equations to simulate the complex processes taking place in the oceans and atmosphere. There is "a revolution in weather forecasting," Knutti said, describing the statistical models as "really, really powerful" and "incredibly fast." Discover the latest in science, tech, and space with over 100,000 subscribers who rely on Phys.org for daily insights. d research that matter—daily or weekly.
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