Researchers are developing artificial intelligence to evaluate climate change tipping points. The deep learning program might serve as an early warning system for climate change that has gotten out of hand.
Chris Bauch, an applied mathematics professor at the University of Waterloo, co-authors a recent research paper detailing the new deep-learning algorithm’s findings. According to Bauch, the research examines the points beyond which a system undergoes fast or irreversible change.
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“We discovered that the new algorithm could not only forecast tipping points more correctly than previous techniques, but it could also offer information about what sort of state exists beyond the tipping point,” Bauch said. “Many of these tipping moments are unwelcome, and we’d prefer to avoid them as much as possible.”
Melting Arctic permafrost, which could release massive amounts of methane and spur further rapid warming; breakdown of current oceanic systems, which could lead to almost immediate changes in weather patterns; or ice sheet disintegration, which could lead to rapid sea-level change are all examples of tipping points often associated with runaway climate change.
According to the researchers, the AI was trained to learn not just about one sort of tipping point but also about the features of tipping points in general.
Source: Nature News World
