Using machine learning to find such a signal is likely a long way off—if it’s even possible. In a study published late last year, Johnson and his team suggested there could be a previously disregarded seismic signal that might contain a pattern revealing when a major earthquake—like the infamous and long-awaited Cascadia quake in the Pacific Northwest—could strike. If the hypothesis pans out, it could change the way earthquakes are forecast from seconds in advance to, maybe one day, decades in advance.
The most recent improvements in earthquake forecasting have been those precious seconds. Seismologists are working on improving early-warning systems like those in Japan and the ShakeAlert system being rolled out along the U.S. West Coast. Those systems send out alerts only after an earthquake has already started—but in time to shut down things like elevators or gas lines and warn communities farther from the epicenter.
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