GLAD-M35: a joint P and S global tomographic model with uncertainty quantification

Congyue Cui, Wenjie Lei, Qiancheng Liu, Daniel Peter, Ebru Bozdag, Jeroen Tromp, Judith Hill, Norbert Podhorszki, David Pugmire

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We present our third and final generation joint P and S global adjoint tomography (GLAD) model, GLAD-M35, and quantify its uncertainty based on a low-rank approximation of the inverse Hessian. Starting from our second-generation model, GLAD-M25, we added 680 new earthquakes to the database for a total of 2160 events. New P-wave categories are included to compensate for the imbalance between P- and S-wave measurements, and we enhanced the window selection algorithm to include more major-arc phases, providing better constraints on the structure of the deep mantle and more than doubling the number of measurement windows to 40 million. Two stages of a Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton inversion were performed, each comprising five iterations. With this BFGS update history, we determine the model’s standard deviation and resolution length through randomized singular value decomposition.

Original languageEnglish (US)
Pages (from-to)478-502
Number of pages25
JournalGeophysical Journal International
Volume239
Issue number1
DOIs
StatePublished - Oct 1 2024

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Geochemistry and Petrology

Keywords

  • Computational seismology
  • Seismic tomography
  • Wave propagation
  • Waveform inversion

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