- The Washington Times - Tuesday, April 23, 2019

Researchers have found that an earthquake occurs about every three minutes in Southern California, a surprising discovery credited to new technology that could help scientists predict when and where large tremors will happen.

Scientists scrutinized 10 years’ worth of seismic data — 1.81 million tremors — using a computer system that separates actual earthquakes from other background vibrations.

“It’s not that we didn’t know these small earthquakes were occurring, the problem is that they can be very difficult to spot amid all of the noise,” said the study’s lead author, Zachary Ross, a California Institute of Technology seismologist.

The research, published last week in a paper titled “Searching for Hidden Earthquakes in Southern California,” dove deeply into the region’s hidden quakes from 2008 to 2017.

Scientists examined tremors so small that they often were mistaken for non-quake vibrations, like those from tractor-trailer traffic, trains and construction.

The data Mr. Ross and his team investigated came from a network of about 400 seismic sensors scattered across Southern California down to the U.S.-Mexico border, which includes the volatile San Andreas Fault.

They employed a technique called “template matching” in which researchers determine the template, or unique wiggle, that a quake or tectonic plate slip registers on seismic sensors. The technique separates quake signals from noise.

Although template matching was pioneered about 15 years ago, the latest use of it is noteworthy, experts say. Past applications were limited, but Caltech tackled 10 years of information from an regional seismic database.

Seeking “near identical waveforms” across that data set required the assistance of new supercomputers and algorithms, Mr. Ross said in a Caltech blog.

Major strides in seismology have included the discovery of aftershocks in the 1940s and the theory of plate tectonics in the early 1960s. Scientists now can accurately map known fault lines in the earth’s crust and pinpoint hazard zones, but earthquake prediction is nothing anyone has ever done accurately, they say.

Caltech’s recent work has raised hopes, especially following two recent ground-breaking papers from the Los Alamos National Laboratory, the multidisciplinary research institution conducting strategic science on behalf of U.S. national security.

Those studies, both published in the journal Nature Geoscience, used artificial intelligence and machine learning tools to analyze massive data sets.

One analysis replied on laboratory research to study rocks under pressure, focusing on the “slow slip” vibrations that preceded major breaks in the rock. Researchers isolated “a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure,” the paper concluded.

The other Los Alamos research focused on identifying subtle seismic signals along the Cascadia subduction zone — where one tectonic plate slides grindingly beneath another — off the Pacific Northwest coast of California, Oregon, Washington state and British Columbia. The last major earthquake there occurred in 1700 and triggered a destructive tsunami.

In that analysis, researchers isolated the continuous seismic signal of slow slippage at the zone’s base, separating the “continuous chatter” of the slippage from the noise of the surrounding natural environment.

This “continuous chatter” the scientists argued, “may prove useful in determining if and how a slow slip may couple to or evolve into a major earthquake.”

Paul Johnson, a Los Alamos National Laboratory geophysicist who co-wrote the studies, said the work made him “much more hopeful now than I’ve ever been” about the future of earthquake prediction.

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