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    Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

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    Geophys. J. Int.-2015-Razafindrakoto-17-40.pdf
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    Type
    Article
    Authors
    Razafindrakoto, Hoby cc
    Mai, Paul Martin cc
    Genton, Marc G. cc
    Zhang, Ling
    Thingbaijam, Kiran Kumar cc
    KAUST Department
    Computational Earthquake Seismology (CES) Research Group
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Spatio-Temporal Statistics and Data Analysis Group
    Statistics Program
    Date
    2015-04-22
    Online Publication Date
    2015-04-22
    Print Publication Date
    2015-07-01
    Permanent link to this record
    http://hdl.handle.net/10754/550794
    
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    Abstract
    Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for both the random field and the case studies.
    Citation
    Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake 2015, 202 (1):17 Geophysical Journal International
    Publisher
    Oxford University Press (OUP)
    Journal
    Geophysical Journal International
    DOI
    10.1093/gji/ggv088
    Additional Links
    http://gji.oxfordjournals.org/cgi/doi/10.1093/gji/ggv088
    ae974a485f413a2113503eed53cd6c53
    10.1093/gji/ggv088
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program; Statistics Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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