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Ultralow‐velocity zones (ULVZs) have been studied using a variety of seismic phases; however, their physical origin is still poorly understood. Short period ScP waveforms are extensively used to infer ULVZ properties because they may be sensitive to all ULVZ elastic moduli and thickness. However, ScP waveforms are additionally complicated by the effects of path attenuation, coherent noise, and source complexity. To address these complications, we developed a hierarchical Bayesian inversion method that allows us to invert ScP waveforms from multiple events simultaneously and accounts for path attenuation and correlated noise. The inversion method is tested with synthetic predictions which show that the inclusion of attenuation is imperative to recover ULVZ parameters accurately and that the ULVZ thickness and S‐wave velocity decrease are most reliably recovered. Utilizing multiple events simultaneously reduces the effects of coherent noise and source time function complexity, which in turn allows for the inclusion of more data to be used in the analyses. We next applied the method to ScP data recorded in Australia for 291 events that sample the core‐mantle boundary beneath the Coral Sea. Our results indicate, on average, ∼12‐km thick ULVZ with ∼14% reduction in S‐wave velocity across the region, but there is a greater variability in ULVZ properties in the south than that in the north of the sampled region. P‐wave velocity reductions and density perturbations are mostly below 10%. These ScP data show more than one ScP post‐cursor in some areas which may indicate complex 3‐D ULVZ structures.

 

Continent‐scale observations of seismic phenomena have provided multi‐scale constraints of the Earth's interior. Of those analyzed, array‐based observations of slowness vector properties (backazimuth and horizontal slowness) and multipathing have yet to be made on a continental scale. Slowness vector measurements give inferences on mantle heterogeneity properties such as velocity perturbation and velocity gradient strength and quantify their effect on the wavefield. Multipathing is a consequence of waves interacting with strong velocity gradients resulting in two arrivals with different slowness vector properties and times. The mantle structure beneath the contiguous Unites States has been thoroughly analyzed by previous seismic studies and is data‐rich, making it an excellent testing ground to both analyze mantle structure with our approach and compare with other imaging techniques. We apply an automated array‐analysis technique to an SKS data set to create the first continent‐scale data set of multipathing and slowness vector measurements. We analyze the divergence of the slowness vector deviation field to highlight seismically slow and fast regions. Our results resolve several slow mantle anomalies beneath Yellowstone, the Appalachian mountains and fast anomalies throughout the mantle. Many of the anomalies cause multipathing in frequency bands 0.15–0.30 and 0.20–0.40 Hz which suggests velocity transitions over at most 500 km exist. Comparing our observations to synthetics created from tomography models, we find model NA13 (Bedle et al., 2021,https://doi.org/10.1029/2021GC009674) fits our data best but differences still remain. We therefore suggest slowness vector measurements should be used as an additional constraint in tomographic inversions and will lead to better resolved models of the mantle.

 

The locations of ultralow‐velocity zones (ULVZs) at the core‐mantle boundary (CMB) have been linked to a variety of features including hot spot volcanoes and large low‐velocity province (LLVP) boundaries, yet only a small portion of the CMB region has been probed for ULVZ existence. Here we present a new map of lower mantle heterogeneity locations using a global collection of highly anomalous SPdKS recordings based on a dataset of more than 58,000 radial component seismograms, which sample 56.9% of the CMB by surface area. The inference of heterogeneity location using the SPdKS seismic phase is challenging due to source‐versus receiver‐side ambiguity. Due to this ambiguity, we conducted an inversion using the principle of parsimony. The inversion is conducted using a genetic algorithm which is repeated several thousand times in order to construct heterogeneity probability maps. This analysis reveals that at probabilities0.5, 0.25, and 0.125 up to 1.3%, 8.2%, or 19.7% of the CMB may contain ULVZ‐like heterogeneities. These heterogeneities exist in all lower mantle settings, including both high‐ and low‐velocity regions. Additionally, we present evidence that the Samoan ULVZ may be twice as large as previously estimated, and also present evidence for the existence of additional mega‐sized ULVZs, such as a newly discovered ULVZ located to the east of the Philippines. We provide new evidence for the ULVZ east of the Philippines through an analysis of ScP records.

 

We analyzed 4,754 broadband seismic recordings of the SKS, SKKS, and SPdKS wavefield from 13 high quality events sampling the Samoa ultralow‐velocity zone (ULVZ). We measured differential travel‐times and amplitudes between the SKKS and SKS arrivals, which are highly sensitive to the emergence of the SPdKS seismic phase, which is in turn highly sensitive to lowermost mantle velocity perturbations such as generated by ULVZs. We modeled these data using a 2‐D axi‐symmetric waveform modeling approach and are able to explain these data with a single ULVZ. In order to predict both travel‐time and amplitude perturbations we found that a large ULVZ length in the great circle arc direction on the order of 10° or larger is required. The large ULVZ length limits acceptable ULVZ elastic parameters. Here we find that δV_Sand δV_Preductions from 20% to 22% and 15% to 17% respectively gives us the best fit, with a thickness of 26 km. Initial 3‐D modeling efforts do not recover the extremes in the differential measurements, demonstrating that 3‐D effects are important and must be considered in the future. However, the 3‐D modeling is generally consistent with the velocity reductions recovered with the 2‐D modeling. These velocity reductions are compatible with a compositional component to the ULVZ. Furthermore, geodynamic predictions for a compositional ULVZ that is moving predict a long linear shape similar to the shape of the Samoa ULVZ we confirm in this study.

 

We analyzed new recordings ofSPdKSseismic waveforms from a global set of broadband seismograms and horizontal tiltmeters from the Hi‐net array in Japan from 26 earthquakes in the Central American region. The anomalous waveforms are consistent with the presence of at least three ultralow‐velocity zones (ULVZs), on the core‐mantle boundary beneath northern Mexico and the southeastern United States. These ULVZs ring an area of high seismic wave speeds observed in tomographic models that has long been associated with past subduction. Waveform modeling using the PSVaxi method suggests that the ULVZs haveSandPwave velocity decreases of 40% and 10%, respectively. These velocity decreases are likely best explained by a partially molten origin where the melt is generated through melting of mid‐ocean ridge basalt atop the subducted slab.

 

Qualitative and quantitative analysis of seismic waveforms sensitive to the core–mantle boundary (CMB) region reveal the presence of ultralow-velocity zones (ULVZs) that have a strong decrease in compressional (P) and shear (S) wave velocity, and an increase in density within thin structures. However, understanding their physical origin and relation to the other large-scale structures in the lowermost mantle are limited due to an incomplete mapping of ULVZs at the CMB. The SKS and SPdKS seismic waveforms is routinely used to infer ULVZ presence, but has thus far only been used in a limited epicentral distance range. As the SKS/SPdKS wavefield interacts with a ULVZ it generates additional seismic arrivals, thus increasing the complexity of the recorded wavefield. Here, we explore utilization of the multi-scale sample entropy method to search for ULVZ structures. We investigate the feasibility of this approach through analysis of synthetic seismograms computed for PREM, 1-, 2.5-, and 3-D ULVZs as well as heterogeneous structures with a strong increase in velocity in the lowermost mantle in 1- and 2.5-D. We find that the sample entropy technique may be useful across a wide range of epicentral distances from 100° to 130°. Such an analysis, when applied to real waveforms, could provide coverage of roughly 85% by surface area of the CMB. 

SUMMARY Horizontal slowness vector measurements using array techniques have been used to analyse many Earth phenomena from lower mantle heterogeneity to meteorological event location. While providing observations essential for studying much of the Earth, slowness vector analysis is limited by the necessary and subjective visual inspection of observations. Furthermore, it is challenging to determine the uncertainties caused by limitations of array processing such as array geometry, local structure, noise and their effect on slowness vector measurements. To address these issues, we present a method to automatically identify seismic arrivals and measure their slowness vector properties with uncertainty bounds. We do this by bootstrap sampling waveforms, therefore also creating random sub arrays, then use linear beamforming to measure the coherent power at a range of slowness vectors. For each bootstrap sample, we take the top N peaks from each power distribution as the slowness vectors of possible arrivals. The slowness vectors of all bootstrap samples are gathered and the clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is used to identify arrivals as clusters of slowness vectors. The mean of slowness vectors in each cluster gives the slowness vector measurement for that arrival and the distribution of slowness vectors in each cluster gives the uncertainty estimate. We tuned the parameters of DBSCAN using a data set of 2489 SKS and SKKS observations at a range of frequency bands from 0.1 to 1 Hz. We then present examples at higher frequencies (0.5–2.0 Hz) than the tuning data set, identifying PKP precursors, and lower frequency by identifying multipathing in surface waves (0.04–0.06 Hz). While we use a linear beamforming process, this method can be implemented with any beamforming process such as cross correlation beamforming or phase weighted stacking. This method allows for much larger data sets to be analysed without visual inspection of data. Phenomena such as multipathing, reflections or scattering can be identified automatically in body or surface waves and their properties analysed with uncertainties. 

Ultralow-velocity zones (ULVZs) at the core–mantle boundary (CMB) represent some of the most preternatural features in Earth’s mantle. These zones most likely contain partial melt, extremely high iron content ferropericlase, or combinations of both. We analyzed a new collection of 58,155 carefully processed and quality-controlled broadband recordings of the seismic phase SPdKS in the epicentral distance range from 106° to 115°. These data sample 56.9% of the CMB by surface area. From these recordings we searched for the most anomalous seismic waveforms that are indicative of ULVZ presence. We used a Bayesian approach to identify the regions of the CMB that have the highest probability of containing ULVZs, thereby identifying sixteen regions of interest. Of these regions, we corroborate well-known ULVZ existence beneath the South China Sea, southwest Pacific, the Samoa hotspot, the southwestern US/northern Mexico, and Iceland. We find good evidence for new ULVZs beneath North Africa, East Asia, and north of Papua New Guinea. We provide further evidence for ULVZs in regions where some evidence has been hinted at before beneath the Philippine Sea, the Pacific Northwest, and the Amazon Basin. Additional evidence is shown for potential ULVZs at the base of the Caroline, San Felix and Galapagos hotspots.