Autocorrelation R2 on Mars

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dc.citation.articleNumbere2022GL099580
dc.citation.issueNumber17
dc.citation.journalTitleGeophysical Research Letters
dc.citation.volumeNumber49
dc.contributor.authorDeng, Sizhuang
dc.contributor.authorLevander, Alan
dc.date.accessioned2022-10-28T17:42:57Z
dc.date.available2022-10-28T17:42:57Z
dc.date.issued2022
dc.description.abstractA purpose of the Interior Exploration Using Seismic Investigations, Geodesy and Heat Transport (InSight) mission is to reveal the Martian interior structure with seismic data. In this work, ambient noise autocorrelation of the continuously recorded vertical-component seismic signals has extracted the Rayleigh waves that propagate around Mars for one cycle, R2. The Mars orbiting surface waves are observed at a lag time of ∼6,000 s in the stacked autocorrelation series filtered between 0.005 and 0.01 Hz. Synthetic seismograms from a set of radially concentric velocity models were computed to find the best-fitting one as the starting model for a Monte Carlo inversion. The starting model was randomly perturbed iteratively to increase the correlation coefficients and reduce the absolute time shifts between the synthetic and observed R2. An S-wave low-velocity layer in the inverted velocity model extends to ∼400 km depth, consistent with Marsquake observations, geophysical inversion, and high-pressure experiments.
dc.identifier.citationDeng, Sizhuang and Levander, Alan. "Autocorrelation R2 on Mars." <i>Geophysical Research Letters,</i> 49, no. 17 (2022) Wiley: https://doi.org/10.1029/2022GL099580.
dc.identifier.digitalDeng-Autocorrelation-R2-on-Mars
dc.identifier.doihttps://doi.org/10.1029/2022GL099580
dc.identifier.urihttps://hdl.handle.net/1911/113756
dc.language.isoeng
dc.publisherWiley
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleAutocorrelation R2 on Mars
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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