A sports car is crushed by earthquake debris in a Seattle parking lot on March 4, 2001. (FEMA photo by Kevin Galvin)

Artificial Intelligence Takes on Earthquake Prediction

In May of last year, after a 13-month slumber, the ground beneath Washington’s Puget Sound rumbled to life. The quake began more than 20 miles below the Olympic mountains and, over the course of a few weeks, drifted northwest, reaching Canada’s Vancouver Island. It then briefly reversed course, migrating back across the U.S. border before going silent again. All told, the monthlong earthquake likely released enough energy to register as a magnitude 6. By the time it was done, the southern tip of Vancouver Island had been thrust a centimeter or so closer to the Pacific Ocean.

Because the quake was so spread out in time and space, however, it’s likely that no one felt it. These kinds of phantom earthquakes, which occur deeper underground than conventional, fast earthquakes, are known as “slow slips.” They occur roughly once a year in the Pacific Northwest, along a stretch of fault where the Juan de Fuca plate is slowly wedging itself beneath the North American plate. More than a dozen slow slips have been detected by the region’s sprawling network of seismic stations since 2003.  And for the past year and a half, these events have been the focus of a new effort at earthquake prediction by the geophysicist Paul Johnson.

Read more at Quanta Magazine

The Government Technology & Services Coalition's Homeland Security Today (HSToday) is the premier news and information resource for the homeland security community, dedicated to elevating the discussions and insights that can support a safe and secure nation. A non-profit magazine and media platform, HSToday provides readers with the whole story, placing facts and comments in context to inform debate and drive realistic solutions to some of the nation’s most vexing security challenges.

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