LLNL-G3Dv3: Global P wave tomography model for improved regional and teleseismic travel time prediction

Simmons, N. A.; Myers, S. C.; Johannesson, G.; Matzel, E.

doi:10.1029/2012JB009525

Title: LLNL-G3Dv3: Global P wave tomography model for improved regional and teleseismic travel time prediction

Journal Article · Sat Oct 06 00:00:00 EDT 2012 · Journal of Geophysical Research

DOI:https://doi.org/10.1029/2012JB009525· OSTI ID:1090031

Simmons, N. A. ^[1]; Myers, S. C. ^[1]; Johannesson, G. ^[1]; Matzel, E. ^[1]

Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

[1] We develop a global-scale P wave velocity model (LLNL-G3Dv3) designed to accurately predict seismic travel times at regional and teleseismic distances simultaneously. The model provides a new image of Earth's interior, but the underlying practical purpose of the model is to provide enhanced seismic event location capabilities. The LLNL-G3Dv3 model is based on ~2.8 millionP and Pnarrivals that are re-processed using our global multiple-event locator called Bayesloc. We construct LLNL-G3Dv3 within a spherical tessellation based framework, allowing for explicit representation of undulating and discontinuous layers including the crust and transition zone layers. Using a multiscale inversion technique, regional trends as well as fine details are captured where the data allow. LLNL-G3Dv3 exhibits large-scale structures including cratons and superplumes as well numerous complex details in the upper mantle including within the transition zone. Particularly, the model reveals new details of a vast network of subducted slabs trapped within the transition beneath much of Eurasia, including beneath the Tibetan Plateau. We demonstrate the impact of Bayesloc multiple-event location on the resulting tomographic images through comparison with images produced without the benefit of multiple-event constraints (single-event locations). We find that the multiple-event locations allow for better reconciliation of the large set of direct P phases recorded at 0–97° distance and yield a smoother and more continuous image relative to the single-event locations. Travel times predicted from a 3-D model are also found to be strongly influenced by the initial locations of the input data, even when an iterative inversion/relocation technique is employed.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: W-7405-ENG-48

OSTI ID:: 1090031

Report Number(s):: LLNL-JRNL-560513

Journal Information:: Journal of Geophysical Research, Vol. 117, Issue B10; ISSN 0148-0227

Publisher:: American Geophysical Union

Country of Publication:: United States

Language:: English

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