Wave Propagation in Non-Stationary Statistical Mantle Models at the Global Scale

Abstract:

We study the effect of statistically distributed heterogeneities that are smaller than the resolution of current tomographic models on seismic waves that propagate through the Earth's mantle at teleseismic distances. Current global tomographic models are missing small-scale structure as evidenced by the failure of even accurate numerical synthetics to explain enhanced coda in observed body and surface waveforms. One way to characterize small scale heterogeneity is to construct random models and confront observed coda waveforms with predictions from these models. Statistical studies of the coda typically rely on models with simplified isotropic and stationary correlation functions in Cartesian geometries.

We show how to construct more complex random models for the mantle that can account for arbitrary non-stationary and anisotropic correlation functions as well as for complex geometries. Although this method is computationally heavy, model characteristics such as translational, cylindrical or spherical symmetries can be used to greatly reduce the complexity such that this method becomes practical. With this approach, we can create 3D models of the full spherical Earth that can be radially anisotropic, i.e. with different horizontal and radial correlation functions, and radially non-stationary, i.e. with radially varying model power and correlation functions. Both of these features are crucial for a statistical description of the mantle in which structure depends to first order on the spherical geometry of the Earth. We combine different random model realizations of S velocity with current global tomographic models that are robust at long wavelengths (e.g. Meschede and Romanowicz, 2014, GJI submitted), and compute the effects of these hybrid models on the wavefield with a spectral element code (SPECFEM3D_GLOBE). We finally analyze the resulting coda waves for our model selection and compare our computations with observations. Based on these observations, we make predictions about the strength of unresolved small-scale structure and extrinsic attenuation.