Work

First implementation of a tsunami warning system based on prompt elastogravity signals in Peru

Year: 2025

Type: article

Abstract: SUMMARY Tsunami warning systems implemented worldwide rely on the fast characterization of earthquake sources, in particular on the estimation of the moment magnitude $\textit {M}_{\textrm {w}}$. Reliable estimation of $\textit {M}_{\textrm {w}}$ typically takes 10 to 20 min for large events based on conventional seismic signals. A promising alternative is the use of prompt elasto-gravity signals (PEGS), which are very low-amplitude gravitational perturbations induced by earthquakes that travel at the speed of light and can be recorded by broad-band seismometers at timescales of a few minutes after origin time. We propose here a first implementation of real-time PEGS analysis to enhance the Peruvian earthquake monitoring system by enabling rapid magnitude estimation for large and potentially tsunamigenic earthquakes. We train a graph neural network to recognize the space-time structure of PEGS over a large international set of broad-band seismic stations, even when their amplitudes are smaller than the noise level, and to rapidly estimate the magnitude and location of the source. Our results indicate that the PEGS-based system can estimate the magnitude of $\textit {M}_{\textrm {w}} \ge 8.2$ earthquakes, within 5 min after the event’s initiation, with sufficient accuracy for tsunami warning purposes. Simulated real-time tests confirm the viability of the PEGS-based approach for operational early warning, providing robust source estimations of large magnitude events to the Peruvian earthquake monitoring system that are valuable for tsunami warning.

Source: Geophysical Journal International

DOI: 10.1093/gji/ggaf419