Global-scale P wave tomography optimized for prediction of teleseismic and regional travel times for Middle East events: 2. Tomographic inversion

We construct a model of three-dimensional P wave velocity structure in the crust and mantle that is global in extent, but with detailed upper mantle heterogeneities throughout the greater Middle East region. Fully three-dimensional ray tracing is employed to achieve accurate travel time predictions of P and P-n arrivals, requiring the characterization of irregular and discontinuous boundaries. Therefore, we explicitly represent undulating seismic discontinuities in the crust and upper mantle within a spherical tessellation modeling framework. The tessellation-based model architecture is hierarchical in that fine node sampling is achieved by recursively subdividing a base level tessellation. Determining the required node spacing to effectively model a given set of data is problematic, given the uneven sampling of seismic data and the differing wavelengths of actual seismic heterogeneity. To address this problem, we have developed an inversion process called Progressive Multilevel Tessellation Inversion (PMTI) that exploits the hierarchical nature of the tessellation-based design and allows the data to determine the level of model complexity. PMTI serves as an alternative to existing multiresolution approaches and robustly images regional trends while allowing localized details to emerge where resolution is sufficient. To demonstrate our complete modeling concept, we construct a velocity model based on teleseismic P travel time data for global events and regional P-n travel time data for events occurring throughout the Middle East. Input data are a product of the statistical procedure called Bayesloc that simultaneously models all components of a multievent system including event locations, origin times, and arrival times (described in the Myers et al. (2011) companion paper). The initial tomographic image provides a new glimpse of the complex upper mantle velocity anomalies associated with the convergence of the Arabian and Indian plates with Eurasia. More important for event monitoring, the model accurately predicts both teleseismic and regional travel times for events occurring within the Middle East region.