Estimating the magnitude of large earthquakes in real time using gravitational waves

It is estimated that for a tsunami to be generated by an earthquake, the latter must be of a strong magnitude, at least 6.5 on the Richter scale. A team of researchers from IRD, CNRS, Université Côte d’Azur, Observatoire de la Côte d’Azur, Los Alamos National Laboratory and Kyoto University used artificial intelligence to estimate instantaneously the magnitude of large earthquakes from the “Prompt Elasto-Gravity Signals” (PEGS). Their study titled Instant tracking of earthquake growth with elastogravity signals » was published in the journal Nature on May 11.

Fortunately, tsunamis are rare natural disasters, but they can kill many people living in coastal areas or island states. Thus, the Tsunami which took place on December 26, 2004 in the Indian Ocean, following an earthquake of magnitude 9.1, affected 14 countries, including India, Indonesia, Sri Lanka and even Thailand, leaving an estimated 230,000 dead and missing.

Warning systems based on seismic waves have been put in place to limit the human and material losses of these disasters. The populations are only warned a few seconds before the tremors but as the tsunamis move more slowly, this leaves them a few tens of minutes to take refuge in a safe place.

However, these warning systems fail to quickly estimate the magnitude of very large earthquakes. Thus, the Japanese warning system estimated a magnitude of 8 instead of 9 during the earthquake on the Pacific coast of Tōhoku (commonly called the Fukushima earthquake) in 2011, predicting a wave of 3 meters instead of 15, an error with dramatic consequences (18,079 dead or missing). According to the research team, geodesy-based approaches allow for better estimates, but are also subject to large uncertainties and latency associated with slow seismic waves.

The study

The team demonstrated that it is possible to exploit gravitational signals (PEGS), which, although very weak, were discovered in 2017 in the 2011 earthquake data, to instantaneously estimate the magnitude of large earthquakes .

PEGS (Prompt Elasto-Gravity Signals) are gravitational waves generated by the movement of an immense mass of rock during large earthquakes. These signals propagate at the speed of light, much faster than seismic waves and can thus provide populations with additional time to protect themselves.

The very low amplitude of PEGS made it impossible until now to use them in warning systems. The researchers circumvented this problem using an AI algorithm. They developed PESGNet, a model of deep learning, the CNN, which exploits the information provided by the PEGS recorded by regional broadband seismometers in Japan before the arrival of the seismic waves. After training on a database of 500,000 synthetic waveform data augmented with empirical noise, the algorithm can instantly track a time function of an earthquake’s source on real data. According to the researchers, Our model unlocks “real-time” access to the rupture evolution of large earthquakes using a portion of seismograms that is routinely treated as noise and can be immediately transformative for tsunami early warning. »

Andrea Licciardi, geophysicist at GEOAZUR and first author of the study, says:

Tested in Japan, the algorithm proves capable of estimating the magnitude of the Fukushima earthquake faster and more reliably than all existing systems, without using seismic waves »

Quentin Bletery, at the initiative of the project, and in the same unit, adds:

Implementation in operational warning systems remains to be done, but our results indicate that PEGS could significantly improve tsunami warning systems. »

Sources of the article: Licciardi, A., Bletery, Q., Rouet-Leduc, B. et al. Instantaneous tracking of earthquake growth with elastogravity signals. Nature (2022).

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Estimating the magnitude of large earthquakes in real time using gravitational waves

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