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13 - Data Assimilation for Real-Time Shake-Mapping and Prediction of Ground Shaking in Earthquake Early Warning

from Part III - ‘Solid’ Earth Applications: From the Surface to the Core

Published online by Cambridge University Press:  20 June 2023

Alik Ismail-Zadeh
Affiliation:
Karlsruhe Institute of Technology, Germany
Fabio Castelli
Affiliation:
Università degli Studi, Florence
Dylan Jones
Affiliation:
University of Toronto
Sabrina Sanchez
Affiliation:
Max Planck Institute for Solar System Research, Germany
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Summary

Abstract: Earthquake early warning (EEW) systems aim to provide advance warning of impending strong ground shaking, in which earthquake ground shaking is predicted in real-time or near real-time. Many EEW systems are based on a strategy which first quickly determines the earthquake hypocentre and magnitude, and then predicts the strength of ground shaking at various locations using the hypocentre distance and magnitude. Recently, however, a new strategy was proposed in which the current seismic wavefield is rapidly estimated by using data assimilation, and then the future wavefield is predicted on the basis of the physics of wave propagation. This technique for real-time prediction of ground shaking in EEW does not necessarily require the earthquake hypocentre and magnitude. In this paper, I review real-time shake-mapping and data assimilation for precise estimation of ongoing ground shaking, and prediction of future shaking in EEW.

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Publisher: Cambridge University Press
Print publication year: 2023

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References

References

Asano, K., and Iwata, T. (2012). Source model for strong ground motion generation in the frequency range 0.1–10 Hz during the 2011 Tohoku earthquake. Earth Planets Space, 64, 1111–23. https://doi.org/10.5047/eps.2012.05.003.CrossRefGoogle Scholar
Awaji, T., Kamachi, M., Ikeda, M., and Ishikawa, Y. (2009). Data Assimilation: Innovation Combining Observation and Model (in Japanese). Kyoto: Kyoto University Press.Google Scholar
Böse, M., Smith, D. E., Felizardo, C. et al. (2018). FinDer v.2: Improved real-time ground-motion predictions forM2–M9 with seismic finite-source characterization. Geophysical Journal International, 212, 725–42. https://doi.org/10.1093/gji/ggx430.Google Scholar
Chen, D. Y., Hsiao, N. C., and Wu, Y. M. (2015). The earthworm-based earthquake alarm reporting system in Taiwan. Bulletin of the Seismological Society of America, 105, 568–79. https://doi.org/10.1785/0120140147.CrossRefGoogle Scholar
Cochran, E. S., Bunn, J., Minson, S. E. et al. (2019). Event detection performance of the PLUM earthquake early warning algorithm in southern California. Bulletin of the Seismological Society of America, 109, 1524–41. https://doi.org/10.1785/0120180326.Google Scholar
Cuellar, A., Espinosa-Aranda, J. M., Suárez, G. (2014). The Mexican Seismic Alert System (SASMEX): Its alert signals, broadcast results and performance during the M 7.4 Punta Maldonado earthquake of March 20th, 2012. In Wenzel, F. and Zschau, J., eds., Early Warning for Geological Disasters. Berlin: Springer, pp. 7187.CrossRefGoogle Scholar
Erdik, M., Fahjan, Y., Ozel, O. et al. (2003). Istanbul earthquake rapid response and the early warning system, Bulletin of Earthquake Engineering, 1, 157–63. https://doi.org/10.1023/A:1024813612271.CrossRefGoogle Scholar
Furumura, T., and Maeda, T. (2021). High-resolution source imaging based on time-reversal wave propagation simulations using assimilated dense seismic records. Geophysical Journal International, 225, 140–57. https://doi.org/10.1093/gji/ggaa586.CrossRefGoogle Scholar
Furumura, T., Maeda, T., and Oba, A. (2019). Early forecast of long‐period ground motions via data assimilation of observed ground motions and wave propagation simulations. Geophysical Research Letters, 46(1), 139–47. https://doi.org/10.1029/2018GL081163.Google Scholar
Gasparini, P., and Manfredi, G. (2014). Development of earthquake early warning systems in the European Union. In Zschau, J. and Wenzel, F., eds., Early Warning for Geological Disasters: Scientific Methods and Current Practice, Berlin: Springer, pp. 89101. https://doi.org/10.1007/978-3-642-12233-0_5.Google Scholar
Gusev, A. A., and Abubakirov, I. R. (1987). Monte-Carlo simulation of record envelope of a near earthquake. Physics of the Earth and Planetary Interiors, 49, 30–6.Google Scholar
Hoshiba, M. (1991). Simulation of multiple scattered coda wave excitation based on the energy conservation law. Physics of the Earth and Planetary Interiors, 67, 123–6.CrossRefGoogle Scholar
Hoshiba, M. (2013a). Real-time prediction of ground motion by Kirchhoff–Fresnel boundary integral equation method: Extended front detection method for earthquake early warning. Journal of Geophysical Research: Solid Earth, 118, 1038–50. https://doi.org/10.1002/jgrb.50119.Google Scholar
Hoshiba, M. (2013b). Real-time correction of frequency-dependent site amplification factors for application to earthquake early warning. Bulletin of the Seismological Society of America, 103, 3179–88. https://doi.org/10.1785/0120130060.CrossRefGoogle Scholar
Hoshiba, M. (2020). Too-late warnings by estimating Mw: earthquake early warning in the near-fault region. Bulletin of the Seismological Society of America, 110, 1276–88. https://doi.org/10.1785/0120190306.Google Scholar
Hoshiba, M. (2021), Real-time prediction of impending ground shaking: Review of wavefield-based (ground-motion-based) method for earthquake early warning. Frontier in Earth Sciences, 22. https://doi.org/10.3389/feart.2021.722784.Google Scholar
Hoshiba, M., and Aoki, S. (2015). Numerical shake prediction for earthquake early warning: Data assimilation, real‐time shake mapping, and simulation of wave propagation. Bulletin of the Seismological Society of America, 105, 1324–38. https://doi.org/10.1785/0120140280.Google Scholar
Hoshiba, M., and Ozaki, T. (2014). Earthquake early warning and tsunami warning of the Japan Meteorological Agency, and their performance in the 2011 off the Pacific Coast of Tohoku Earthquake (Mw9.0). In Wenzel, F. and Zschau, J., eds., Early Warning for Geological Disasters: Scientific Methods and Current Practice. Berlin: Springer, pp. 128. https://doi.org/10.1007/978-3-642-12233-0_1.Google Scholar
Hoshiba, M., Iwakiri, K., Hayashimoto, N. et al. (2011). Outline of the 2011 off the Pacific Coast of Tohoku Earthquake (Mw 9.0): Earthquake Early Warning and observed seismic intensity. Earth Planets Space, 63, 547–51. https://doi.org/10.5047/eps.2011.05.031.Google Scholar
Hoshiba, M., Kamigaichi, O., Saito, M., Tsukada, S. Y., and Hamada, N. (2008). Earthquake early warning starts nationwide in Japan. Eos, Transactions, American Geophysical Union, 89, 73–4. https://doi.org/10.1029/2008EO080001.CrossRefGoogle Scholar
Japan Meteorological Agency. (2012). Report of the 2011 off the Pacific Coast of Tohoku earthquake by Japan Meteorological Agency (in Japanese), Japan Meteorological Agency.Google Scholar
Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability. Cambridge: Cambridge University Press.Google Scholar
Kurahashi, S. and Irikura, K. (2013). Short-period source model of the 2011 Mw 9.0 Off the Pacific Coast of Tohoku earthquake. Bulletin of the Seismological Society of America, 103, 1373–93. https://doi.org/10.1785/0120120157.Google Scholar
Kurzon, I., Nof, R. N., Laporte, M. et al. (2020). The ‘TRUAA’ seismic network: Upgrading the Israel seismic network – Toward national earthquake early warning system. Seismological Research Letters, 91, 32363255. https://doi.org/10.1785/0220200169.Google Scholar
Oba, A., Furumura, T., and Maeda, T. (2020). Data assimilation‐based early forecasting of long‐period ground motions for large earthquakes along the Nankai Trough. Journal of Geophysical Research: Solid Earth, 125(6), e2019JB019047. https://doi.org/10.1029/2019JB019047.Google Scholar
Ogiso, M., Aoki, S., and Hoshiba, M. (2016). Real-time seismic intensity prediction using frequency-dependent site amplification factors. Earth Planets Space 68, 83. https://doi.org/10.1186/s40623-016-0467-4.Google Scholar
Ogiso, M., Hoshiba, M., Shito, A., and Matsumoto, S.(2018). Numerical shake prediction for earthquake early warning incorporating heterogeneous attenuation structure: The case of the 2016 Kumamoto earthquake. Bulletin of the Seismological Society of America, 108, 3457–68. https://doi.org/10.1785/0120180063.Google Scholar
Peng, H., Wu, Z., Wu, Y. M. et al. (2011). Developing a prototype earthquake early warning system in the Beijing Capital Region. Seismological Research Letters, 82, 394403. https://doi.org/10.1785/gssrl.82.3.394.CrossRefGoogle Scholar
Sato, H., Fehler, M. C., and Maeda, T. (2012). Seismic Wave Propagation and Scattering in the Heterogeneous Earth, 2nd ed. Berlin: Springer. https://doi.org/10.1007/978-3-642-23029-5.CrossRefGoogle Scholar
Sheen, D. H., Park, J. H., Chi, H. C. et al. (2017). The first stage of an earthquake early warning system in South Korea. Seismological Research Letters, 88, 1491–98. https://doi.org/10.1785/0220170062Google Scholar
Suzuki, W., Aoi, S., Kunugi, T. et al. (2017). Strong motions observed by K-NET and KiK-net during the 2016 Kumamoto earthquake sequence. Earth Planets Space, 69, 19. https://doi.org/10.1186/s40623-017-0604-8.Google Scholar
Tamaribuchi, K., Yamada, M., and Wu, S. (2014). A new approach to identify multiple concurrent events for improvements of earthquake early warning. Zisin, 67(2), 4155. https://doi.org/10.4294/zisin67.41 (in Japanese with English abstract).CrossRefGoogle Scholar
Wald, D. J., Worden, B. C., Quitoriano, V., and Pankow, K. L. (2005). ShakeMap manual: Technical manual, user’s guide, and software guide, Techniques and Methods 12-A1. https://doi.org/10.3133/tm12A1.Google Scholar
Wang, T., Jin, X., Wei, Y. and Huang, Y. (2017a). Real-time numerical shake prediction and updating for earthquake early warning. Earthquake Science, 30, 251–67. https://doi.org/10.1007/s11589-017-0195-2Google Scholar
Wang, T., Jin, X., Huang, Y. and Wei, Y. (2017b). Real-time three-dimensional space numerical shake prediction for earthquake early warning. Earthquake Science, 30, 269–81. https://doi.org/10.1007/s11589-017-0196-1.Google Scholar
Wessel, P., and Smith, W. H. F. (1995). New version of the generic mapping tool released. Eos, Transactions, American Geophysical Union, 76, 329.Google Scholar
Yoshimoto, K. (2000). Monte Carlo simulation of seismogram envelopes in scattering medium. Journal of Geophysical Research: Solid Earth, 105, 6153–61. https://doi.org/10.1029/1999JB900437.CrossRefGoogle Scholar

Specific Terms

EEW: Earthquake early warning. Warning of strong shaking before its arrival.Google Scholar
GMPE: Ground-motion prediction equation. Strength of ground motion is empirically estimated from the equation, in which earthquake magnitude and distance (hypocentral distance, epicentral distance, or fault distance) are usually used.Google Scholar
JMA: Japan Meteorological Agency. A national governmental organization in Japan.Google Scholar
K-NET, KiK-net: Observation networks of strong ground motion operated by National Research Institute for Earth Science and Disaster Resilience (NIED) in Japan.Google Scholar
RTT: Radiative transfer theory. A model of wave propagation based on ray theoretical approach, in which scattering and attenuation are included.Google Scholar

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