The rocks of the Indian subcontinent are last seen south of the Ganges before they plunge beneath the Himalaya and the Tibetan plateau. They are next glimpsed in seismic reflection profiles deep beneath southern Tibet, yet the surface seen there has been modified by processes within the Himalaya that have consumed parts of the upper Indian crust and converted them into Himalayan rocks. The geometry of the partly dismantled Indian plate as it passes through the Himalayan process zone has hitherto eluded imaging. Here we report seismic images both of the decollement at the base of the Himalaya and of the Moho (the boundary between crust and mantle) at the base of the Indian crust. A significant finding is that strong seismic anisotropy develops above the decollement in response to shear processes that are taken up as slip in great earthquakes at shallower depths. North of the Himalaya, the lower Indian crust is characterized by a high-velocity region consistent with the formation of eclogite, a high-density material whose presence affects the dynamics of the Tibetan plateau.

[1] Rayleigh wave phase velocity maps from ambient noise and earthquake data are inverted jointly with receiver functions observed at 828 stations from the USArray Transportable Array west of 100 W longitude for data recorded in the years 2005 through 2010 to produce a 3-D model of shear wave speeds beneath the central and Western US to a depth of 150 km. Eikonal tomography is applied to ambient noise data to produce about 300,000 Rayleigh wave phase speed curves, and Helmholtz tomography is applied to data following 1550 (Ms > 5.0) earthquakes so that Rayleigh wave dispersion maps are constructed from 8 to 80 s period with associated uncertainties across the region. Harmonic stripping generates back-azimuth independent receiver functions with uncertainty estimates for each of the stations. A nonlinear Bayesian Monte Carlo method is used to estimate a distribution of shear wave speed (Vs) models beneath each station by jointly interpreting surface wave dispersion and receiver functions and their uncertainties. The assimilation of receiver functions improves the vertical resolution of the model by reducing the range of estimated Moho depths, improving the determination of the shear velocity jump across Moho, and improving the resolution of the depth of anomalies in the uppermost mantle. A great variety of geological and tectonic features are revealed in the 3-D model that form the basis for future detailed local to regional scale analysis and interpretation.

A non-linear Bayesian Monte-Carlo method is presented to estimate a Vs model beneath stations by jointly interpreting surface wave dispersion and receiver functions and associated uncertainties, which is designed for automated application to large arrays of broadband seismometers. As a proving ground for the method, 185 stations from the USArray Transportable Array are used in the Intermountain West, a region that is geologically diverse and structurally complex. Ambient noise and earthquake tomography are updated by applying eikonal and Helmholtz tomography, respectively, to construct Rayleigh wave dispersion maps from 8 sec to 80 sec across the study region. A harmonic stripping method is applied as a basis for quality control and to generate back-azimuth independent receiver functions with uncertainty estimates for each station. A smooth parameterization between (as well as above and below) discontinuities at the base of the sediments and crust suffices to fit most features of both data types jointly across most of the study region. The effect of introducing receiver functions to surface wave dispersion data is quantified through improvements in the posterior marginal distribution of model variables. Assimilation of receiver functions quantitatively improves the accuracy of estimates of Moho depth, improves the determination of the Vsv contrast across Moho, and improves uppermost mantle structure because of the ability to relax a priori constraints. The method presented here is robust and can be applied systematically to construct a 3-D model of the crust and uppermost mantle across the large networks of seismometers that are developing globally, but also provides a framework for further refinements.

Earthquakes beneath the Himalayan collision zone occur at depths between near surface and around 100 km below sea level. After relocating earthquakes with two one‐dimensional (1‐D) velocity models, we found a clear bimodal depth distribution for earthquakes in the Himalayas of eastern Nepal and the southern Tibetan Plateau and evidence that some earthquakes originate at upper mantle depths. Seismicity in Nepal shows an accumulation of earthquakes along the front of the Himalayan arc, with a seismic gap between longitudes 87.3°E and 87.7°E. Although upper crustal seismicity along the topographic front of the High Himalaya is consistent with a region of high strain accumulation associated with convergence on the Main Himalayan thrust fault, microearthquakes do not necessarily occur on this fault. Instead, they concentrate in the hanging wall. Seismic activity in the sub‐Himalaya and the Terai Plains is almost exclusively limited to the vicinity of the location of the magnitude 6.5 20 August 1988 Udayapur earthquake, with most of the earthquakes in the lower crust and the upper mantle. Clusters of earthquakes in the Lesser and High Himalayas and south Tibet (Tethyan Himalayas) mark very well defined zones of seismicity at depths between 50 and 100 km, confirming the presence of earthquakes in the upper mantle in the region of continental collision. The occurrence of earthquakes at sub‐Moho depths favors the idea that the continental upper mantle deforms by brittle processes.

[1] We study how numerically predicted seismic anisotropy in the upper mantle is affected by several common assumptions about the rheology of the convecting mantle and deformation-induced lattice preferred orientations (LPO) of minerals. We also use these global circulation and texturing models to investigate what bias may be introduced by assumptions about the symmetry of the elastic tensor for anisotropic mineral assemblages. Maps of elasticity tensor statistics are computed to evaluate symmetry simplifications commonly employed in seismological and geodynamic models. We show that most of the anisotropy predicted by our convection-LPO models is captured by estimates based on a best fitting hexagonal symmetry tensor derived from the full elastic tensors for the computed olivine:enstatite LPOs. However, the commonly employed elliptical approximation does not hold in general. The orientations of the best fitting hexagonal symmetry axes are generally very close to those predicted for finite strain axes. Correlations between hexagonal anisotropy parameters for P and S waves show simple, bilinear relationships. Such relationships can reduce the number of free parameters for seismic inversions if this information is included a priori. The match between our model predictions and observed patterns of anisotropy supports earlier, more idealized studies that assumed laboratory-derived mineral physics theories and seismic measurements of anisotropy could be applied to study mantle dynamics. The match is evident both in agreement between predicted LPO at selected model sites and that measured in natural samples, and in the global pattern of fast seismic wave propagation directions.Citation: Becker, T. W., S. Chevrot, V. Schulte-Pelkum, and D. K. Blackman (2006), Statistical properties of seismic anisotropy predicted by upper mantle geodynamic models,

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