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SUMMARY Ultra-low velocity zones (ULVZs) have been identified as regions of extremely low velocity anomalies in the Earth's lowermost mantle using seismic observations from reflected, refracted and diffracted arrivals along the mantle side of the core–mantle boundary. Estimation of ULVZ geometrical (i.e. shape and size) and elastic (i.e. velocity and density) parameters with uncertainties is crucial in understanding the role of ULVZs in the ongoing dynamic processes within the Earth's mantle; however, these parameters are still poorly known due to uncertainties and tradeoffs of the seismically resolved ULVZ geometries and elastic parameters. Computation of synthetic waveforms for 2-D and 3-D ULVZs shapes is currently computationally feasible, but past studies utilize higher dimensional waveform modelling of mostly only low-frequency diffracted waves. Most studies focusing on high-frequency core-reflected waveforms (e.g. ScP) still use 1-D modelling approaches to determine ULVZ properties. This approach might lead to wrong results if the imaged structures have inherently 3-D geometries. This study investigates high-frequency synthetic ScP waveforms for various 2.5-D ULVZ geometries showing that additional seismic arrivals are generated even when the ScP geometrical ray path does not directly strike the location of the ULVZ. The largest amplitude additional phases in the 2.5-D models are post-cursor arrivals that are generated at the edges of the finite-length ULVZs. These newly identified ScP post-cursors can arrive within the ScsP post-cursor time window traditionally analysed in 1-D ULVZ studies. These post-cursors might then be misidentified or constructively/destructively interfere with the ScsP post-cursor, leading to incorrect estimation of ULVZ parameters. In this study we investigate the bias introduced by the 2.5-D morphologies on the 1-D estimated ULVZ elastic properties in a Bayesian waveform inversion scheme. We further expand the Bayesian method by including the data noise covariance matrix in the inversion and compare it to an autoregressive noise model that was utilized in previous studies. From the application to the observed ScP data, we find that the new approach converges faster, particularly for the inversion of data from multiple events, and the new algorithm retrieves ULVZ parameters with more realistic uncertainties. The inversion of 2.5-D synthetic ScP waveforms suggests that the retrieved ULVZ parameters can be misleading with unrealistically high confidence if we do not consider the data noise covariance matrix in the inversion. Our new approach can also retrieve the shape of a multidimensional Gaussian ULVZ if its length is 12° or longer in the great circle arc direction. However, 2.5-D synthetic waveforms show additional waveform complexity which can constructively interfere with the ScP wavefield. Hence, in many cases the estimation of ULVZ properties using 1-D forward modelling can provide incorrect ULVZ parameters. Hence previous ULVZ modelling efforts using 1-D parameter estimation methods may be incorrect.
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Improved Characterization of Ultralow‐Velocity Zones Through Advances in Bayesian Inversion of ScP Waveforms
Abstract 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.
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- Award ID(s):
- 1723081
- PAR ID:
- 10426663
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 128
- Issue:
- 6
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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