Ridgecrest earthquakes can cause the San Andreas chain reaction

Scientists have developed a new method for estimating the possibility of future earthquakes

Scientists have developed a method to estimate the probability of future earthquakes.

The Ridgecrest earthquake with a magnitude of 6.4 and a magnitude of 7.1 was largely unpredictable. They hit unmapped errors, and in a rare order of events, the biggest earthquake was followed 34 hours after the smaller earthquake. Fortunately, these major shocks occurred in the remote southern California desert, so they caused modest damage and no deaths.

But Ridgecrest’s rupture can have far-reaching implications because another error – Garlock error – links Ridgecrest errors with San Andreas error. What to expect now, if any? This is the question that was addressed in a study by the Templore Company supported by the National Science Foundation, which was published in the Bulletin of the American Seismic Society.

In the 150 years before the Ridgecrest earthquakes of 2019, four shocks greater than 7.0 struck over a distance of 90 miles. These earthquakes added to the pressure on the newly discovered Paxton Ranch ranch and the faults of the Salt Wales Valley that would eventually rip apart in 2019.

Now scientists at Temblor have developed a new way to predict future earthquakes, the occurrence or recurrence of earthquakes in the region. These predictions are not earthquake predictions, which have so far been proven impossible. Rather, it is a possibility, framed in the language of chance. Researchers use past earthquakes, pressure from recent large and medium earthquakes, and equations that govern how friction friction varies in time and space to estimate the probability of future earthquakes.

More accurate earthquake prediction methods allow societies and insurance companies to better understand and reduce risks. Tumblr scientists note that almost all of California’s premiums are related to earthquake rates estimated by an older model. The researchers say that this study indicates that these reference possibilities are very low, which affects how homeowners and insurance companies evaluate the risk and, consequently, the price of home insurance.

“Temblor will enable a more accurate assessment of earthquake risks and insurance prices using its new model that uses machine learning to predict the probability, location, and intensity of an earthquake,” said Andrea Bills, director of the Industrial Innovation and Partnerships division at NSF, which supports startups. Small businesses with research and development grants.

Public release. Full show here. .

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