Methodology improvements

We invert seismic long period waveform data simultaneously for perturbations in the isotropic S-velocity structure and anisotropic parameter $\xi=\frac{v_{SH}^2}{v_{SV}^2}$, in the framework of normal mode asymptotic coupling theory (NACT - Li and Romanowicz, 1996). The resulting broad band sensitivity kernels allow us to exploit the information contained in long period seismograms for body, fundamental and higher mode surface waves at the same time.

This approach was being applied at the global scale with lateral parametrization in terms of spherical harmonics (e.g. Li and Romanowicz, 1996). Here, we have adapted the procedure to the regional case by implementing a lateral parametrization in terms of spherical splines on an inhomogeneous triangular grid of knots (e.g. Wang and Dahlen, 1995), with the finest mesh for the region of interest, where the data coverage is densest, and a coarser grid outside the study region. This flexible parametrization approach permits the perturbation of only a subset of the model parameters, for instance the ones falling within the target area, while using the entire set to correct the data for the global 3D heterogeneous structure, in this case using the radial anisotropic global model SAW24AN16 (Panning and Romanowicz, 2005).

Body and surface wave datasets used in mantle seismic tomography are sensitive to crustal structure, but cannot resolve details within the crust. Accurate crustal corrections are therefore essential for the quality of high resolution regional tomographic studies. The effect of shallow-layer features is often removed from the data by assuming an a priori crustal model (e.g. CRUST5.1) and applying linear perturbation corrections. However, lateral variations in Moho depth can be fairly large even over short distances, as for instance at ocean/continent transitions and the adequacy of linear corrections is questionable. In fact, Montagner and Jobert (1988) showed that the non-linearity of shallow-layer corrections is often non negligible even at long periods. In high resolution upper mantle regional tomographic studies, it is therefore important to take the crustal structure into account in a more accurate way. Going beyond the linear perturbation approximation, we follow the approach proposed by Montagner and Jobert (1988) and split the correction into a linear and non-linear part. At each point along a path, we assign a 1D reference model according to the local crustal structure (e.g. extended crust, orogen, ocean, ...). We then correct for the difference between the discontinuities in the chosen a priori crustal model (e.g. CRUST5.1) and the selected 1D local reference model assuming a linear perturbation, and exactly for the difference, if any, between the local reference model and PREM (our global reference model).

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