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Sunday, April 7, 2024

An Elusive Gravity Signal Could Mean Faster Earthquake Warnings

For a brief period in 2011, just after two tectonic plates gave way off the eastern coast of Japan, gravity wobbled. The Earth’s gravitational field is the result of a distribution of matter—a slightly firmer tug where the world is denser; a looser grasp where it is not. When massive volumes of earth and water are suddenly displaced, like in an earthquake, that distribution changes. The forces that hold the moon close, keep the atmosphere thick, and tie our feet to the ground jerked into a new alignment. The whole world tripped, seconds before the seismic waves arrived and Japan really shook.

Not that anyone noticed. Even the very biggest tremors, like the 2011 Tohoku earthquake, have a subtle effect on gravity. But for seismologists accustomed to listening closely to the Earth’s rumblings, such changes have long offered a tantalizing possibility: an earthquake signal that is practically instantaneous, spreading through the globe at the speed of light. In recent years, scientists have scoured data from big quakes for signs of these gravity perturbations. They’re elusive, and still fairly controversial in seismology. But with the help of more sensitive instruments and better computer models, the hunters have started to find them.

Now they’re getting closer to putting that data to use. In a paper published in Nature, researchers describe an earthquake early warning system that relies on those gravity-derived signals alone. They tested their model on seismic data from the Tohoku earthquake, finding it could accurately detect the quake about eight seconds faster than previous methods and give a better estimate of its massive size. The work is a proof of concept, looking back on a single event. But it’s meant to test if the method could add precious seconds to early warning systems in the future. “We’re showing that this is actually a signal, and it can be used,” says Andrea Licciardi, a seismologist at Côte d'Azur University in France who led the research. “People weren’t even looking at this part of the data, but it is comparable, if not better than, existing signals.”

Those existing signals are primarily P-waves, seismic ripples that occur as rock compresses and vibrates from a sudden shock. When these waves reach seismic stations, software quickly pinpoints where the earthquake originated and estimates its size. The goal is to give people a heads-up, however brief, before the up-and-down motion of S-waves, a slower type of tremor that often causes the most damage. In recent years, better instruments and algorithms have resulted in faster and more reliable warning systems. But P-waves typically only travel at a few kilometers per second, putting a theoretical limit on the speed of detection.

Gravity perturbations are quicker—as in speed-of-light quicker. “It is faster than any other method we have today,” says Martin Vallée, a seismologist at the University of Paris who has worked on detecting the signals. But they’re also far less forceful than P-waves, making them tricky to pick out from seismologists’ greatest enemy: noise. The din of the earth is constant, a chorus of tiny events generated by people, seismic tremors, and air and ocean turbulence that makes the early hints of a major quake exceedingly difficult to hear. Seismologists want a clear signal of what’s coming. Mishear the noise and millions of city residents may end up flooding the streets or cowering in door frames for no reason at all.

For decades, seismologists have debated whether a clear detection is possible. There are tools to observe gravitational waves directly, like the massive LIGO facilities in Louisiana and Washington. But they’re mostly of use to astronomers and aren’t practical for picking up the tiny shifts caused by earthquakes. Instead, the fluctuations are observed indirectly by seismometers, which pick up the response of the Earth as it pushes and pulls away to counteract the shift in mass. Trouble is, the gravity changes and the elastic responses to them mostly cancel each other out. This leaves a remarkably faint signal, known as a “prompt elastogravity signal,” or PEGS, to observe.

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Seismic waves from a big quake are easy to see—think of the classic image of a seismograph, pencil scratching out telltale waves on a rotating paper as the tremor arrives. Even to highly trained eyes, PEGS are just squiggles, indistinguishable from the noise. It’s hard to prove they’re there. In 2017, early identifications of PEGS in Tohoku seismic data received pushback from other seismologists.

But over time, researchers have collected more observations from earthquakes around the world. “I’ve managed to convince myself that the theory is correct,” says Maarten de Hoop, a computational seismologist at Rice University who wasn’t involved in the research. Inspired in part by the controversy over the early detections, he set out to mathematically prove whether the gravitational fluctuations should be observable. The key, he says, is looking at data from the earliest moments of the quake, before P-waves arrive at sensors. At that point, the two forces “don’t totally cancel each other out,” meaning there’s theoretically a signal to be found in the noise. But the question of whether seismologists can actually separate the two has remained.

The new research offers initial validation that they can, de Hoop says. One thing that’s clear is that current instruments can only distinguish gravity signals from other noisy data during the biggest earthquakes—those larger than a magnitude 8.0, like the massive megathrust earthquakes that affect places like Japan, Alaska, and Chile. Since those big earthquakes are rare, Licciardi’s team created a data set of hypothetical earthquakes, sprinkling in real-world seismic noise observed at stations across Japan. This was used to train a machine-learning algorithm that would detect the start of a quake and estimate its size based on the gravity signal.

When the researchers applied the model to real-time data from sensors during the Tohoku quake, it took about 50 seconds of data to give an accurate detection, beating recent state-of-the-art approaches, including space-based GPS methods that measure the movement of the ground just after a quake. The eight-second difference may sound small, but it “is still a lot in the context of early warning,” Licciardi notes—especially in scenarios like the Tohoku quake, where coastal residents were given only minutes to evacuate in anticipation of the coming tsunami. In addition, the researchers note that the model was more accurate in estimating the size of the earthquake, which is vital in predicting a tsunami’s size. In Japan in 2011, initial estimates of a sub-8.0 earthquake suggested a much smaller wave.

The method is still a ways off from being practical. Thomas Heaton, a seismologist at CalTech, describes the continued hunt for gravity perturbations as “a hammer looking for a nail,” given advances in more traditional approaches to earthquake detection—including in Japan, where officials responded to Tohoku by adding more sensors along the offshore subduction zones and expanding their models to account for massive, 9.0-plus earthquakes. To him, the biggest task for early warning systems is making the warnings more practical: battle-testing existing methods so that if a warning is issued, people hear it and know how to react. “Our problem isn’t sensors. It's how to get data from the system and tell people what to do,” he says.

But de Hoop, who calls himself “enthusiastic” about the new work, notes that it provides a road map for improving the methods with better data and machine-learning techniques. The key to making this work for more common, smaller quakes will be figuring out how to lower the magnitude threshold for detecting the gravity signals—something that may require sensors that directly detect changes in the gravitational field. “I think there’s a wealth of information out there, and a wealth of work to be done,” he says.

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