A statistical assessment of seismic models of the U.S. continental crust using Bayesian inversion of ambient noise surface wave dispersion data

T. M. Olugboji, V. Lekic, W. McDonough

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

We present a new approach for evaluating existing crustal models using ambient noise data sets and its associated uncertainties. We use a transdimensional hierarchical Bayesian inversion approach to invert ambient noise surface wave phase dispersion maps for Love and Rayleigh waves using measurements obtained from Ekström (2014). Spatiospectral analysis shows that our results are comparable to a linear least squares inverse approach (except at higher harmonic degrees), but the procedure has additional advantages: (1) it yields an autoadaptive parameterization that follows Earth structure without making restricting assumptions on model resolution (regularization or damping) and data errors; (2) it can recover non-Gaussian phase velocity probability distributions while quantifying the sources of uncertainties in the data measurements and modeling procedure; and (3) it enables statistical assessments of different crustal models (e.g., CRUST1.0, LITHO1.0, and NACr14) using variable resolution residual and standard deviation maps estimated from the ensemble. These assessments show that in the stable old crust of the Archean, the misfits are statistically negligible, requiring no significant update to crustal models from the ambient noise data set. In other regions of the U.S., significant updates to regionalization and crustal structure are expected especially in the shallow sedimentary basins and the tectonically active regions, where the differences between model predictions and data are statistically significant.

Original languageEnglish
Pages (from-to)1232-1253
Number of pages22
JournalTectonics
Volume36
Issue number7
DOIs
Publication statusPublished - 2017 Jul

Keywords

  • Bayesian inference
  • ambient noise surface waves
  • crustal structure

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

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