Jia, Zhe and Zhan, Zhongwen and Helmberger, Donald (2022) Bayesian differential moment tensor inversion: theory and application to the North Korea nuclear tests. Geophysical Journal International, 229 (3). pp. 2034-2046. ISSN 0956-540X. doi:10.1093/gji/ggac053. https://resolver.caltech.edu/CaltechAUTHORS:20220503-182318528
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Abstract
Moment tensors are key to seismic discrimination but often require accurate Green's functions for estimation. This limits the regions, frequency bands and wave types in moment tensor inversions. In this study, we propose a differential moment tensor inversion (diffMT) method that uses relative measurements to remove the path effects shared by clustered events, thereby improving the accuracy of source parameters. Using results from regular inversions as a priori distribution, we apply Bayesian Markov Chain Monte Carlo to invert the body- and surface wave amplitude ratios of an event pair for refined moment tensors of both events. Applications to three North Korea nuclear tests from 2013 to 2016 demonstrate that diffMT reduces the uncertainties substantially compared with the traditional waveform-based moment tensor inversion. Our results suggest high percentages of explosive components with similar double-couple components for the North Korea nuclear tests.
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| Additional Information: | © The Author(s) 2022. 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 2022 February 7. Received 2022 January 19; in original form 2021 July 8. Published: 10 February 2022. ZJ and ZZ thank and commemorate Don Helmberger for his advising and assistance. We thank the Global Seismic Network (GSN), the International Federation of Digital Seismograph Networks (FDSN), the French Global Network (G), and the Japan Meteorological Agency Seismic Network (JP) for collecting the seismic data, and thank the Incorporated Research Institutions for Seismology (IRIS) for providing public access to them. We thank editor Carl Tape, assistant editor Fern Storey, reviewer Alexandre Plourde and two other anonymous reviewers for their valuable comments. We thank Jack Muir for helpful discussions. This work was supported by Air Force Research Laboratory (AFRL) Grant FA9453-18-C-0058. Data Availability: All the data used in our study can be downloaded from the IRIS Data Management Center (http://ds.iris.edu/wilber3/find_event). | |||||||||
| Group: | Seismological Laboratory | |||||||||
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| Subject Keywords: | Inverse theory, Earthquake monitoring and test-ban treaty verification, Earthquake source observations | |||||||||
| Issue or Number: | 3 | |||||||||
| DOI: | 10.1093/gji/ggac053 | |||||||||
| Record Number: | CaltechAUTHORS:20220503-182318528 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20220503-182318528 | |||||||||
| Official Citation: | Zhe Jia, Zhongwen Zhan, Donald Helmberger, Bayesian differential moment tensor inversion: theory and application to the North Korea nuclear tests, Geophysical Journal International, Volume 229, Issue 3, June 2022, Pages 2034–2046, https://doi.org/10.1093/gji/ggac053 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 114552 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Tony Diaz | |||||||||
| Deposited On: | 03 May 2022 19:09 | |||||||||
| Last Modified: | 03 May 2022 19:09 |
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