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Published May 7, 2020 | Submitted
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Early earthquake detection capabilities of different types of future-generation gravity gradiometers

Abstract

Since gravity propagates at the speed of light, gravity perturbations induced by earthquake deformation have the potential to enable faster alerts than the current earthquake early warning systems based on seismic waves. Additionally, for large earthquakes (M_w > 8), gravity signals may allow for a more reliable magnitude estimation than seismic-based methods. Prompt elastogravity signals induced by earthquakes of magnitude larger than 7.9 have been previously detected with seismic arrays and superconducting gravimeters. For smaller earthquakes, down to M_w ≃ 7, it has been proposed that detection should be based on measurements of the gradient of the gravitational field, in order to mitigate seismic vibration noise and to avoid the canceling effect of the ground motions induced by gravity signals. Here we simulate the five independent components of the gravity gradient signals induced by earthquakes of different focal mechanisms. We study their spatial amplitude distribution to determine what kind of detectors is preferred (which components of the gravity gradient are more informative), how detectors should be arranged, and how earthquake source parameters can be estimated. The results show that early earthquake detections, within 10 seconds of the rupture onset, using only the horizontal gravity strain components are achievable up to about 140 km distance from the epicenter. Depending on the earthquake focal mechanism and on the detector location, additional measurement of the vertical gravity strain components can enhance the detectable range by 10–20 km. These results are essential for the design of gravity-based earthquake early warning systems.

Additional Information

License: GNU Lesser General Public License (LGPL) 2.1. Submitted: May 03, 2020; Last edited: May 06, 2020. We acknowledge the financial support from the UnivEarthS Labex program at Sorbonne Paris Cité (ANR-10-LABX-0023 and ANR- 11-IDEX-0005-02) and the financial support of the Agence Nationale de la Recherche (ANR) through the grant ANR-14-CE03- 0014-01. This study contributes to the IdEx Universit´e de Paris ANR-18-IDEX-0001. T. S. acknowledges the financial support of GRASP (Graduate Research Abroad in Science Program) managed by University of Tokyo. J.-P. M. acknowledges the financial support of Institut Universitaire de France. J. P. A. acknowledges funding by the French government through the "Investissements d'Avenir UCAJEDI" project managed by the ANR through grant ANR-15- IDEX-01. We are grateful to Jan Harms for sharing his code to compute gravity changes. Numerical computations were performed on the S-CAPAD platform, IPGP, France. Python routines used to compute the expected gravity strain signal (Harms, 2016) and the optimal signal-to-noise ratio are available at the GitHub repository https://github.com/kjuhel/gravity-eew.

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Created:
August 22, 2023
Modified:
October 20, 2023