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SUMMARY Long-period underside SS wave reflections have been widely used to furnish global constraints on the presence and depth of mantle discontinuities and to document evidence for their origins, for example, mineral phase-transformations in the transition zone, compositional changes in the mid-mantle and dehydration-induced melting above and below the transition zone. For higher-resolution imaging, it is necessary to separate the signature of the source wavelet (SS arrival) from that of the distortion caused by the mantle reflectivity (SS precursors). Classical solutions to the general deconvolution problem include frequency-domain or time-domain deconvolution. However, these algorithms do not easily generalize when (1) the reflectivity series is of a much shorter period compared to the source wavelet, (2) the bounce point sampling is sparse or (3) the source wavelet is noisy or hard to estimate. To address these problems, we propose a new technique called SHARP-SS: Sparse High-Resolution Algorithm for Reflection Profiling with SS waves. SHARP-SS is a Bayesian deconvolution algorithm that makes minimal a-priori assumptions on the noise model, source signature and reflectivity structure. We test SHARP-SS using real data examples beneath the NoMelt Pacific Ocean region. We recover a low-velocity discontinuity at a depth of $$\sim 69 \pm 4$$ km which marks the base of the oceanic lithosphere, consistent with previous work derived from surface waves, body wave conversions, and ScS reverberations. We anticipate high-resolution fine mantle stratification imaging using SHARP-SS at locations where seismic stations are sparsely distributed.
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A global SS precursor method for imaging discontinuities: the Moho and beyond
SUMMARY Imaging seismic velocity discontinuities within the Earth's interior offers important insight into our understanding of the tectonic plate, associated mantle dynamics, and the evolution of the planet. However, imaging velocity discontinuities in locations where station coverage is sparse, is sometimes challenging. Here we demonstrate the effectiveness of a new imaging approach using deconvolved SS precursor phases. We demonstrate its effectiveness by applying it to synthetic seismograms. We also apply it to ∼1.6 M SS precursor waveforms from the global seismic database (1990–2018) for comparison with CRUST1.0. We migrate to depth and stack the data in circular 6° bins. The synthetic tests demonstrate that we can recover Moho depths as shallow as 20 km. Globally, the Moho is resolved at 21–67 km depth beneath continental regions. The Moho increases in depth from 21 km ± 4 km beneath the continental shelf to 45–50 km beneath the continental interiors and is as deep as 67 ± 4 km beneath Tibet. We resolve the Moho in 77 percent of all continental bins, within 10 km of CRUST1.0, with all outliers located in coastal regions. We also demonstrate the feasibility of using this method to image discontinuities associated with the mantle transition zone with both synthetic and real data. Overall, the approach shows broad promise for imaging mantle discontinuities.
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- PAR ID:
- 10568700
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Geophysical Journal International
- Volume:
- 238
- Issue:
- 2
- ISSN:
- 0956-540X
- Page Range / eLocation ID:
- 756 to 763
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/gji/ggae145
