High-resolution models of seismic velocity variations constructed using body-wave tomography inform the study of the origin, fate and thermochemical state of mantle domains. In order to reliably relate these variations to material properties including temperature, composition and volatile content, we must accurately retrieve both the patterns and amplitudes of variations and quantify the uncertainty associated with the estimates of each. For these reasons, we image the mantle beneath North America with P-wave traveltimes from USArray using a novel method for 3-D probabilistic body-wave tomography. The method uses a Transdimensional Hierarchical Bayesian framework with a reversible-jump Markov Chain Monte Carlo algorithm in order to generate an ensemble of possible velocity models. We analyse this ensemble solution to obtain the posterior probability distribution of velocities, thereby yielding error bars and enabling rigorous hypothesis testing. Overall, we determine that the average uncertainty (1σ) of compressional wave velocity estimates beneath North America is ∼0.25 per cent dVP/VP, increasing with proximity to complex structure and decreasing with depth. The addition of USArray data reduces the uncertainty beneath the Eastern US by over 50 per cent in the upper mantle and 25–40 per cent below the transition zone and ∼30 per cent throughout the mantle beneath the Western US. In the absence of damping and smoothing, we recover amplitudes of variations 10–80 per cent higher than a standard inversion approach. Accounting for differences in data coverage, we infer that the length scale of heterogeneity is ∼50 per cent longer at shallow depths beneath the continental platform than beneath tectonically active regions. We illustrate the model trade-off analysis for the Cascadia slab and the New Madrid Seismic Zone, where we find that smearing due to the limitations of the illumination is relatively minor.
We present the current status of geo-neutrino measurements and their implications for radiogenic heating in the mantle. Earth models predict different levels of radiogenic heating and, therefore, different geo-neutrino fluxes from the mantle. Seismic tomography reveals features in the deep mantle possibly correlated with radiogenic heating and causing spatial variations in the mantle geo-neutrino flux at the Earth surface. An ocean-based observatory offers the greatest sensitivity to the mantle flux and potential for resolving Earth models and mantle features. Refinements to estimates of the geo-neutrino flux from continental crust reduce uncertainty in measurements of the mantle flux, especially measurements from land-based observatories. These refinements enable the resolution of Earth models using the combined measurements from multiple continental observatories.
Seismological constraints obtained from receiver function (RF) analysis provide important information about the crust and mantle structure. Here, we explore the utility of the free-surface multiple of the P-wave (PP) and the corresponding conversions in RF analysis. Using earthquake records, we demonstrate the efficacy of PPs-RFs before illustrating how they become especially useful when limited data is available in typical planetary missions. Using a transdimensional hierarchical Bayesian deconvolution approach, we compute robust P-to-S (Ps)- and PPs-RFs with
