Seismology provides important constraints on the structure and dynamics of the deep mantle. Computational and methodological advances in the past two decades improved tomographic imaging of the mantle and revealed the fine-scale structure of plumes ascending from the core-mantle boundary region and slabs of oceanic lithosphere sinking into the lower mantle. We discuss the modeling aspects of global tomography including theoretical approximations, data selection, and model fidelity and resolution. Using spectral, principal component, and cluster analyses, we highlight the robust patterns of seismic heterogeneity, which inform us of flow in the mantle, the history of plate motions, and potential compositionally distinct reservoirs. In closing, we emphasize that data mining of vast collections of seismic waveforms and new data from distributed acoustic sensing, autonomous hydrophones, ocean-bottom seismometers, and correlation-based techniques will boost the development of the next generation of global models of density, seismic velocity, and attenuation. ▪  Seismic tomography reveals the 100-km to 1,000-km scale variation of seismic velocity heterogeneity in the mantle. ▪  Tomographic images are the most important geophysical constraints on mantle circulation and evolution.

Thickness and seismic velocities of sedimentary sequences strongly affect their response during earthquakes, which can prolong and amplify groundmotions. We characterize shallow structure of Atlantic Coastal Plain (ACP) sediments using a passive-seismic approach based on high-frequency P-to-S receiver functions. We map the site-specific fundamental frequency for 64 USArray Transportable Array stations and confirm that the method yields results similar to those from traditional spectral ratio techniques, with fundamental frequencies between 0.1 and 1 Hz. In addition, using sediment S-wave reverberations and P-to-S phase arrival times measured directly from the receiver functions, we invert for average Sand P-wave velocity profiles of the ACP sedimentary strata. We find that VS increases with depth following a power-law relationship (VS ∝ z p ) whereas the increase of VP with depth is more difficult to constrain using converted wave methods; therefore, we choose to use the Brocher (2005) relationship to obtain VP through a VP= VS relationship. Finally, we use the variation of measured S-reverberation amplitudes with depth to validate these velocity profiles. These results have implications for seismic shaking across the ACP, which covers large portions of the eastern United States.

The shape and location of density anomalies inside the Moon provide insights into processes that produced them and their subsequent evolution. Gravity measurements provide the most complete data set to infer these anomalies on the Moon [1]. However, gravity inversions suffer from inherent non-uniqueness. To circumvent this issue, it is often assumed that the Bouguer gravity anomalies are produced by the relief of the crust-mantle or other internal interface [2]. This approach limits the recovery of 3D density anomalies or any anomaly at different depths. In this work, we develop an algorithm that provides a set of likely three-dimensional models consistent with the observed gravity data with no need to constrain the depth of anomalies a priori.

S U M M A R Y Inversions of planetary gravity are aimed at constraining the mass distribution within a planet or moon. In many cases, constraints on the interior structure of the planet, such as the depth of density anomalies, must be assumed a priori, to reduce the non-uniqueness inherent in gravity inversions. Here, we propose an alternative approach that embraces the non-uniqueness of gravity inversions and provides a more complete view of related uncertainties. We developed a Transdimensional Hierarchical Bayesian (THB) inversion algorithm that provides an ensemble of mass distribution models compatible with the gravitational field of the body. Using this ensemble of models instead of only one, it is possible to quantify the range of interior parameters that produce a good fit to the gravity acceleration data. To represent the interior structure of the planet or moon, we parametrize mass excess or deficits with point masses. We test this method with synthetic data and, in each test, the algorithm is able to find models that fit the gravity data of the body very well. Three of the target or test models used contain only point mass anomalies. When all the point mass anomalies in the target model produce gravity anomalies of similar magnitudes and the signals from each anomaly are well separated, the algorithm recovers the correct location, number and magnitude of the point mass anomalies. When the gravity acceleration data of a model is produced mostly by a subset of the point mass anomalies in the target model, the algorithm only recovers the dominant anomalies. The fourth target model is composed of spherical caps representing lunar mass concentration (mascons) under major impact basins. The algorithm finds the correct location of the centre of the mascons but fails to find their correct outline or shape. Although the inversion results appear less sharp than the ones obtained by classical inversion methods, our THB algorithm provides an objective way to analyse the interior of planetary bodies that includes epistemic uncertainty.