Accounting for uncertain fault geometry in earthquake source inversions – II: application to the M_w 6.2 Amatrice earthquake, central Italy
- Creators
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Ragon, Théa
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Sladen, Anthony
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Simons, Mark
Abstract
Our understanding of earthquake sources is limited by the availability and the quality of observations and the fidelity of our physical models. Uncertainties in our physical models will naturally bias our inferences of subsurface fault slip. These uncertainties will always persist to some level as we will never have a perfect knowledge of the Earth's interior. The choice of the forward physics is thus ambiguous, with the frequent need to fix the value of several parameters such as crustal properties or fault geometry. Here, we explore the impact of uncertainties related to the choice of both fault geometry and elastic structure, as applied to the 2016 M_w 6.2 Amatrice earthquake, central Italy. This event, well instrumented and characterized by a relatively simple fault morphology, allows us to explore the role of uncertainty in basic fault parameters, such as fault dip and position. We show that introducing uncertainties in fault geometry in a static inversion reduces the sensitivity of inferred models to different geometric assumptions. Accounting for uncertainties thus helps infer more realistic and robust slip models. We also show that uncertainties in fault geometry and Earth's elastic structure significantly impact estimated source models, particularly if near-fault observations are available.
Additional Information
© The Author(s) 2019. Published by Oxford University Press on behalf of The Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Accepted 2019 April 12. Received 2019 April 3; in original form 2018 November 22. We thank Q. Bletery, B. Gombert and Z. Duputel for helpful discussions. We thank C. Liang, M.H. Huang and E. Fielding for providing us their processed ALOS-2 interferograms, original ALOS-2 data being copyright by Japan Aerospace Exploration Agency (JAXA) and provided under JAXA ALOS RA-4 projects (S.H. Yun) and P1372 (E. Fielding). The Sentinel-1 original images contain modified Copernicus data, and have been processed within the ARIA project, NASA/JPL-Caltech. We thank Claudio Chiarraba and Pasquale De Gori for provinding their catalogue of aftershocks (Chiarabba et al.2018). The Bayesian simulations were performed on the HPC-Regional Center ROMEO (https://romeo.univ-reims.fr) of the University of Reims Champagne-Ardenne (France). The Classic Slip Inversion Python library created by Romain Jolivet (Jolivet et al.2015) was used to build inputs for the Bayesian algorithm and to perform the optimization of the inverse problem. Figures were generated with the Matplotlib and Seaborn Python libraries. This study was partly supported by the French National Research Agency (ANR) EPOST project ANR-14-CE03-0002. TR is supported by a fellowship from the French Ministry of Research and Higher Education. MS was supported by U.S. National Science Foundation grant 1447107. A simple version of the code used to calculate the uncertainties in assumed fault dip, strike and position can be freely downloaded at github.com/thearagon/epistemic_uncertainties.Attached Files
Published - ggz180.pdf
Supplemental Material - ggz180_supplemental_files.zip
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Additional details
- Alternative title
- Accounting for uncertain fault geometry in earthquake source inversions – II: application to the Mw 6.2 Amatrice earthquake, central Italy
- Eprint ID
- 96591
- Resolver ID
- CaltechAUTHORS:20190620-093004278
- Agence Nationale pour la Recherche (ANR)
- ANR-14-CE03-0002
- NSF
- EAR-1447107
- Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation
- Created
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2019-06-20Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field
- Caltech groups
- Seismological Laboratory, Division of Geological and Planetary Sciences (GPS)