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Internal structure of ultralow-velocity zones consistent with origin from a basal magma ocean


Seismological observations reveal patches of low-velocity anomalies at the core–mantle boundary known as ultralow-velocity zones. Despite recent advances, their origin and dynamic link to the lowermost mantle remain unclear. Here we employ seismic data analysis and high-resolution geodynamic modelling to study the origin of ultralow-velocity zones beneath the Coral Sea between Australia and New Zealand. The analysis of core-reflected waveforms with rigorous estimation of Bayesian uncertainties shows strong evidence of stratified density increases (~30%) and shear-wave velocity decreases (~50%) within the ultralow-velocity zones. These zones thin on two sides and occur at the edge of the Pacific large low-shear-velocity province. Geodynamic modelling demonstrates that these features are consistent with the presence of compositional heterogeneities within the ultralow-velocity zones that may be caused by the remnants of Earth’s early differentiation. We conclude that small-scale structures that are compositionally distinct from their surroundings reside at the bottom of the mantle without full homogenization, throughout Earth’s history.

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Fig. 1: Illustration of data type and study region.
Fig. 2: Inversion results in terms of S-wave velocity and density.
Fig. 3: High-resolution geodynamic modelling results.
Fig. 4: Schematic representation of the ULVZ, its evolution and the dynamic processes in the mantle.

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Data availability

All the data used in this study are freely available in the GitHub repository: Source data are provided with this paper.

Code availability

Bayesian inversion code is available from S.P. 2D forward computation code can be obtained from M.S.T. The 2D geodynamic modelling code CITCOM is publicly available49,50.


  1. Li, X. D. & Romanowicz, B. Global mantle shear-velocity model developed using nonlinear asymptotic coupling theory. J. Geophys. Res. 101, 22245–22272 (1996).

    Article  Google Scholar 

  2. Ritsema, J., Deuss, A., van Heijst, H. J. & Woodhouse, J. H. S40RTS: a degree-40 shear-velocity model for the mantle from new Rayleigh wave dispersion, teleseismic traveltime and normal-mode splitting function measurements. Geophys. J. Int. 184, 1223–1236 (2011).

    Article  Google Scholar 

  3. Yu, S. & Garnero, E. J. Ultralow velocity zone locations: a global assessment. Geochem. Geophys. Geosyst. 19, 396–414 (2018).

    Article  Google Scholar 

  4. Garnero, E. J. & Helmberger, D. A very slow basal layer underlying large-scale low velocity anomalies in the lower mantle beneath the Pacific: evidence from core phases. Geophys. J. Int. 178, 503–512 (1995).

    Google Scholar 

  5. Garnero, E. J. & Helmberger, D. Seismic detection of a thin laterally varying boundary layer at the base of the mantle beneath the central-Pacific. Geophys. Res. Lett. 23, 977–980 (1996).

    Article  Google Scholar 

  6. Thorne, M. & Garnero, E. J. Inferences on ultralow-velocity zone structure from a global analysis of SPdKS waves. J. Geophys. Res. 109, B08301 (2004).

    Google Scholar 

  7. Williams, Q. & Garnero, E. J. Seismic evidence for partial melt at the base of Earth’s mantle. Science 273, 1528–1530 (1996).

    Article  Google Scholar 

  8. Revenaugh, J. & Meyer, R. Seismic evidence of partial melt within a possibly ubiquitous low-velocity layer at the base of the mantle. Science 277, 670–674 (1997).

    Article  Google Scholar 

  9. Williams, Q., Revenaugh, J. & Garnero, E. J. A correlation between ultra-low basal velocities in the mantle and hot spots. Science 281, 546–549 (1998).

    Article  Google Scholar 

  10. Yuan, K. & Romanowicz, B. Seismic evidence for partial melting at the root of major hot spot plumes. Science 357, 393–397 (2017).

    Article  Google Scholar 

  11. Ross, A., Thybo, H. & Solidilov, L. Reflection seismic profiles of the core-mantle boundary. J. Geophys. Res. 109, B08303 (2004).

    Google Scholar 

  12. Thorne, M. S., Takeuchi, N. & Shiomi, K. Melting at the edge of a slab in the deepest mantle. Geophys. Res. Lett. 46, 8000–8008 (2019).

    Article  Google Scholar 

  13. Idehara, K. Structural heterogeneity of an ultra-low velocity zones beneath the Philippine Islands: implications for core-mantle chemical interactions induced by massive partial melting at the bottom of the mantle. Phys. Earth Planet. Inter. 184, 80–90 (2011).

    Article  Google Scholar 

  14. Brown, S. P., Thorne, M. S., Miyagi, L. & Rost, S. Compositional origins to ultralow-velocity zones. Geophys. Res. Lett. 42, 1039–1045 (2015).

    Article  Google Scholar 

  15. McNamara, A. K., Garnero, E. J. & Rost, S. Tracking deep mantle reservoirs with ultra-low velocity zones. Earth Planet. Sci. Lett. 299, 1–9 (2010).

    Article  Google Scholar 

  16. Li, M., McNamara, A. K., Garnero, E. J. & Yu, S. Compositionally-distinct ultra-low velocity zones on Earth’s core–mantle boundary. Nat. Commun. 8, 177 (2017).

    Article  Google Scholar 

  17. Labrosse, S., Hernlund, J. W. & Coltice, N. A crystallizing dense magma ocean at the base of the Earth’s mantle. Nature 450, 866–869 (2007).

    Article  Google Scholar 

  18. Buffett, B. A., Garnero, E. J. & Jeanloz, R. Sediments at the top of Earth’s core. Science 290, 1338–1342 (2000).

    Article  Google Scholar 

  19. O’Rourke, J. G. & Stevenson, D. J. Powering Earth’s dynamo with magnesium precipitation from the core. Nature 529, 387–389 (2016).

    Article  Google Scholar 

  20. Christensen, U. R. & Hofmann, A. W. Segregation of subducted oceanic crust in the convecting mantle. J. Geophys. Res. 99, 19867–19884 (1994).

    Article  Google Scholar 

  21. Dobson, D. P. & Brodholt, J. P. Subducted banded iron formations as a source of ultralow-velocity zones at the core–mantle boundary. Nature 434, 371–374 (2005).

    Article  Google Scholar 

  22. Rost, S., Garnero, E. J., Williams, Q. & Manga, M. Seismological constraints on a possible plume root at the core–mantle boundary. Nature 435, 666–669 (2005).

    Article  Google Scholar 

  23. Rost, S. & Revenaugh, J. Seismic detection of rigid zones at the top of the core. Science 294, 1911–1914 (2001).

    Article  Google Scholar 

  24. Pachhai, S., Tkalčić, H. & Dettmer, J. Bayesian inference for ultralow velocity zones in the Earth’s lowermost mantle: complex ULVZ beneath the east of Philippines. J. Geophys. Res. 119, 8346–8365 (2014).

    Article  Google Scholar 

  25. Pachhai, S., Dettmer, J. & Tkalčić, H. Ultra-low velocity zones beneath the Philippine and Tasman Seas revealed by a trans-dimensional Bayesian waveform inversion. Geophys. J. Int. 203, 1302–1318 (2015).

    Article  Google Scholar 

  26. Chapman, C. H. & Orcutt, J. A. The computation of body wave seismogram in laterally homogeneous media. Rev. Geophys. 23, 105–163 (1985).

    Article  Google Scholar 

  27. Ballmer, M. D., Lourenco, D. L., Hirose, K., Caracas, R. & Nomura, R. Reconciling magma–ocean crystallization models with the present-day structure of the Earth’s mantle. Geochem. Geophys. Geosyst. 18, 2785–2806 (2017).

    Article  Google Scholar 

  28. Li, M., McNamara, A. K. & Garnero, E. J. Chemical complexity of hotspots caused by cycling oceanic crust through mantle reservoirs. Nat. Geosci. 7, 366–370 (2014).

    Article  Google Scholar 

  29. Kanda, R. V. S. & Stevenson, D. J. Suction mechanism for iron entrainment into the lower mantle. Geophys. Res. Lett. 33, L02310 (2006).

    Article  Google Scholar 

  30. Solomatov, V. S. & Stevenson, D. J. Nonfractional crystallization of a terrestrial magma ocean. J. Geophys. Res. Atmos. 98, 5391–5406 (1993).

    Article  Google Scholar 

  31. Abe, Y. Thermal and chemical evolution of the terrestrial magma ocean. Phys. Earth Planet. Int. 100, 27–39 (1997).

    Article  Google Scholar 

  32. Rawlinson, N. & Kennett, B. L. N. Rapid estimation of relative and absolute delay times across a network by adaptive stacking. Geophys. J. Int. 157, 332–340 (2004).

    Article  Google Scholar 

  33. Dettmer, J. & Dosso, S. E. Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains. J. Acoust. Soc. Am. 132, 2239–2250 (2012).

    Article  Google Scholar 

  34. Green, P. J. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711–732 (1995).

    Article  Google Scholar 

  35. Geyer, C. J. & Moller, J. Simulation procedures and likelihood inference for spatial point processes. Scand. J. Stat. 21, 359–373 (1994).

    Google Scholar 

  36. Coltice, N. & Schmalzl, J. Mixing times in the mantle of the early Earth derived from 2-D and 3-D numerical simulations of convection. Geophys. Res. Lett. (2006).

  37. O’Neill, C. J. & Zhang, S. Lateral mixing processes in the Hadean. J. Geophys. Res. Solid Earth 123, 7074–7089 (2018).

    Google Scholar 

  38. Tackley, P. J. & King, S. D. Testing the tracer ratio method for modeling active compositional fields in mantle convection simulations. Geochem. Geophys. Geosyst. 4, 8302 (2003).

    Article  Google Scholar 

  39. Hall, S. A., Kendall, J.-M. & van der Baan, M. Some comments on the effects of lower-mantle anisotropy on SKS and SKKS phases. Phys. Earth Planet. Int. 146, 469–481 (2004).

    Article  Google Scholar 

  40. Garnero, E. J., Maupin, V., Lay, T. & Fouch, M. J. Variable azimuthal anisotropy in Earth’s lowermost mantle. Science 306, 259–261 (2004).

    Article  Google Scholar 

  41. Wookey, J., Kendall, J.-M. & Rumpker, G. Lowermost mantle anisotropy beneath the north Pacific from differential S-ScS splitting. Geophys. J. Int. 161, 829–838 (2005).

    Article  Google Scholar 

  42. Nowacki, A., Wookey, J. & Kendall, J.-M. New advances in using seismic anisotropy, mineral physics and geodynamics to understand deformation in the lowermost mantle. J. Geodyn. 52, 205–228 (2011).

    Article  Google Scholar 

  43. Konishi, K., Fuji, N. & Deschamps, F. Elastic and anelastic structure of the lowermost mantle beneath the Western Pacific from waveform inversion. Geophys. J. Int. 208, 1290–1304 (2017).

    Article  Google Scholar 

  44. Lassak, T. M., McNamara, A. K., Garnero, E. J. & Zhong, S. Core–mantle boundary topography as a possible constraint on lower mantle chemistry and dynamics. Earth Planet. Sci. Lett. 289, 232–241 (2010).

    Article  Google Scholar 

  45. Deschamps, F., Rogister, Y. & Tackley, P. J. Constraints on core–mantle boundary topography from models of thermal and thermochemical convection. Geophys. J. Int. 212, 164–188 (2018).

    Article  Google Scholar 

  46. Tanaka, S. Constraints on the core-mantle boundary topography from P4KP-PcP differential travel times. J. Geophys. Res. 115, B04310 (2010).

    Google Scholar 

  47. Heyn, B. H., Conard, C. P. & Tronnes, R. G. Core–mantle boundary topography and its relation to the viscosity structure of the lowermost mantle. Earth Planet. Sci. Lett. 543, 116358 (2020).

    Article  Google Scholar 

  48. Vidale, J. E. & Benz, H. A sharp and flat section of the core–mantle boundary. Nature 359, 627–629 (1992).

    Article  Google Scholar 

  49. Garnero, E. J. & Vidale, J. E. A probe of ultralow velocity zones at the base of the mantle. J. Geophys. Res. 26, 277–380 (1999).

    Google Scholar 

  50. Castle, J. & der Hilst, V. The core–mantle boundary under the Gulf of Alaska: no ULVZ for shear waves. Earth Planet. Sci. Lett. 176, 311–321 (2000).

    Article  Google Scholar 

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We would like to acknowledge members of the Seismology and Mathematical Group of the Research School of Earth Sciences (RSES), The Australian National University (ANU), for maintaining the seismic networks considered in this study. We would also like to acknowledge the University of Utah Center for High Performance Computing, the Argo cluster at ICTP, and ANU Terrawulf cluster at RSES for computing resources. S.P. would like to acknowledge partial support from an ANU PhD scholarship and NSF grant no. EAR-1723081. M.S.T. acknowledges partial support from NSF grant no. EAR-1723081. M.L. was supported by NSF grants nos. EAR-1849949 and EAR-1855624. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations



S.P. conceived this study during his PhD under the supervision of H.T. and J.D., performed all the data processing, analysis, waveform inversions and figures preparation, and wrote the first version of the manuscript. M.L. performed the geodynamical computation, prepared Fig. 3, Extended Data Fig. 8 and Supplementary Videos 13, and wrote the geodynamical method part. All authors discussed the results and shaped the manuscript to its final stage. M.S.T. and S.P. designed the 2D models. M.S.T. implemented the finite-difference PSVaxi code to compute the synthetic ScP waveforms for various 2D geometries.

Corresponding author

Correspondence to Surya Pachhai.

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The authors declare no competing interests.

Peer review information

Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work.Primary Handling editors: Simon Harold, Stefan Lachowycz

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Extended data

Extended Data Fig. 1 Observed ScP waveforms.

Individual ScP waveforms, after removing the source and path effects, sorted as a function of distance from the center of their respective geographical bins. Cross-correlation coefficients between stacked waveform (cyan color on the bottom panels) and individual waveforms are also shown.

Source data

Extended Data Fig. 2 Stacked ScP-waveforms.

(a) Stack of deconvolved ScP-waveforms (black lines) with stacked P-waveforms (blue line) for different geographical bins analyzed in this study. (b) Example waveforms resulting from the effect of earthquake source complexity.

Source data

Extended Data Fig. 3 Inversion results for bins 1 and 2.

Posterior probability density of interfaces, and P-wave velocity, S-wave velocity and density as a function of depth, and observed and ensemble model predictions in the case of bin (top) 1 and (bottom) 2. The color represents the probability density with each depth interval normalized to unit probability. Dark color represents high probability density with the scale clipped at unity.

Source data

Extended Data Fig. 4 Inversion results for bins 5 and 7.

Same as Extended Data Fig. 3 but in the case of bins 5 (top) and 7 (bottom).

Source data

Extended Data Fig. 5 Inversion results for bins 8 and 10.

Same as Extended Data Fig. 3 but in the case of bins 8 (top) and 10 (bottom).

Source data

Extended Data Fig. 6 Inversion results for bins 3 and 4.

Same as Extended Data Fig. 3 but in the case of bin 3 (top) and 4 (bottom).

Source data

Extended Data Fig. 7 Inversion results for bins 6 and 9.

Same as Extended Data Fig. 3 but in the case of bin 6 (top) and 9 (bottom).

Source data

Extended Data Fig. 8 High-resolution geodynamic modeling results.

Snapshots of the temperature field (left column) and the residual buoyancy field (right column) for the case 1 (A, B), case 2 (C, D) and case 3 (E, F) after 1.4 Gyr. Case 1 is the reference case in which the initial density anomaly of the ULVZ layer ranges from 1.5 to 15%. Case 2 is the same as Case 1, expect that the initial density anomaly of the ULVZ layer ranges from 1.5 to 10%. Case 3 is the same as case 1 except that the ULVZ materials are intrinsically 100 times less viscous than the surrounding mantle. In the residual buoyancy panels, the inserted figures are zoomed in from the locations marked by the black box near the bottom of the model domain. Note that the density anomalies (represented by the residual buoyancy) with the ULVZ patches (zoomed in by the rectangle boxes) are more homogenized in case 2 (D) and case 3 (F) than in case 1 (B), whereas the large-scale structure are more similar in all cases.

Source data

Supplementary information

Supplementary Information

Validity of 1D forward modelling, Supplementary Figs. 1–17 and Tables 1 and 2.

Supplementary Video 1

Movie for case 1: time evolution of (bottom) temperature field, (middle) chemical field and (top) thermochemical field in the case of density increases from 1.5% (top of ULVZ) to 15% (at the CMB).

Supplementary Video 2

Movie for case 2: time evolution of (bottom) temperature field, (middle) chemical field and (top) thermochemical field in the case of density increases from 1.5% (top of ULVZ) to 10% (at the CMB).

Supplementary Video 3

Movie for case 3: time evolution of (bottom) temperature field, (middle) chemical field and (top) thermochemical field in terms of residual buoyancy in the case of density increases from 1.5% (top of ULVZ) to 5% (at the CMB).

Source data

Source Data Fig. 1

Earthquake source parameters including focal mechanisms and S-velocity model for the lowermost mantle (Ritsema et al. 2011).

Source Data Fig. 2

Output of the Bayesian inversions for the data from bins #1 to 10.

Source Data Fig. 3

Geodynamic modelling results for three different cases.

Source Data Extended Data Fig. 1

Individual waveforms for all the events considered in this study.

Source Data Extended Data Fig. 2

Stacked ScP and P wavelets for all the events that are considered in the inversion.

Source Data Extended Data Fig. 3

Bayesian inversion output for bins #1 and 2.

Source Data Extended Data Fig. 4

Bayesian inversion output for bins #5 and 7.

Source Data Extended Data Fig. 5

Bayesian inversion output for bins #8 and 10.

Source Data Extended Data Fig. 6

Bayesian inversion output for bins #3 and 4.

Source Data Extended Data Fig. 7

Bayesian inversion output for bins #6 and 9.

Source Data Extended Data Fig. 8

Geodynamic modelling results for three different cases.

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Pachhai, S., Li, M., Thorne, M.S. et al. Internal structure of ultralow-velocity zones consistent with origin from a basal magma ocean. Nat. Geosci. 15, 79–84 (2022).

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