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Scanning for planetary cores with single-receiver intersource correlations

Nature Astronomy volume 6, pages 1272–1279 (2022)Cite this article

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Abstract

The network of seismographs on Earth allows us to gather enough data to reveal the properties of the metallic core hidden in the centre of the planet’s mantle envelope. In contrast, the small number of seismographs deployed on the Moon or Mars limits the sampling of their interiors and makes inferences challenging. Here we show that a single seismograph and global-scale waveform cross-correlations between seismic events can be used to scan planetary cores. We demonstrate that this technique allows us to constrain the sizes of the cores of Earth and Mars and we confirm that the Martian core is large. This technique provides an opportunity to investigate the structure of planetary interiors with currently realizable resources.

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Fig. 1: Diagram of illumination of planetary interiors with global single-station intersource correlations.
Fig. 2: Scanning for the presence of the Earth’s core and constraining its radius (Rcore) with a single-station intersource correlogram.
Fig. 3: Synthetic marsquake correlograms at the InSight station.
Fig. 4: Marsquake correlation features and a qualitative data fit for constraining the radius of the Martian core (Rcore) with observations from the InSight mission.

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Data availability

The facilities of IRIS-DMC, NEIC, NASA-PDS, the SEIS-InSight data portal and the IPGP Data Center were used for access to seismic-event catalogue, waveforms and related metadata used in this study. Marsquake catalogue and waveform data used in this study are available from ref. 30,34. The earthquake catalogue and waveform data are available from the NEIC catalog (available at https://earthquake.usgs.gov/earthquakes/search/) and IRIS-DMC (available at http://ds.iris.edu/ds/nodes/dmc/data/types/waveform-data/).

Code availability

Codes are publicly available in the Supplementary Information.

References

  1. Wood, B. J., Walter, M. J. & Wade, J. Accretion of the Earth and segregation of its core. Nature 441, 825–833 (2006).

    Article  ADS  Google Scholar 

  2. Olson, P., Sharp, Z. & Garai, S. Core segregation during pebble accretion. Earth Planet. Sci. Lett. 587, 117537 (2022).

    Article  Google Scholar 

  3. Braginsky, S. I. Structure of the F layer and reasons for convection in the Earth’s core. Sov. Phys. Dokl. 149, 8–10 (1963).

    Google Scholar 

  4. Buffett, B. A., Huppert, H. E., Lister, J. R. & Woods, A. W. On the thermal evolution of the Earth’s core. J. Geophys. Res.: Solid Earth 101, 7989–8006 (1996).

    Article  Google Scholar 

  5. Aubert, J., Amit, H., Hulot, G. & Olson, P. Thermochemical flows couple the Earth’s inner core growth to mantle heterogeneity. Nature 454, 758–761 (2008).

    Article  ADS  Google Scholar 

  6. Biggin, A. J. et al. Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation. Nature 526, 245–248 (2015).

    Article  ADS  Google Scholar 

  7. Yoder, C. F., Konopliv, A. S., Yuan, D. N., Standish, E. M. & Folkner, W. M. Fluid core size of Mars from detection of the solar tide. Science 300, 299–303 (2003).

    Article  ADS  Google Scholar 

  8. Taylor, G. J. The bulk composition of Mars. Geochemistry 73, 401–420 (2013).

    Article  Google Scholar 

  9. Oldham, R. D. The constitution of the interior of the Earth, as revealed by earthquakes. Q. J. Geol. Soc. 62, 456–475 (1906).

    Article  Google Scholar 

  10. Lehmann, I. P’. Publications du Bureau Central Seismologique International, Série A, Travaux Scientifique 14, 87–115 (1936).

  11. Birch, A. F. The alpha-gamma transformation of iron at high pressures, and the problem of the earth’s magnetism. Am. J. Sci. 238, 192–211 (1940).

    Article  Google Scholar 

  12. Ishii, M. & Dziewoński, A. M. The innermost inner core of the earth: evidence for a change in anisotropic behavior at the radius of about 300 km. PNAS 99, 14026–14030 (2002).

    Article  ADS  Google Scholar 

  13. Debayle, E., Dubuffet, F. & Durand, S. An automatically updated S-wave model of the upper mantle and the depth extent of azimuthal anisotropy. Geophys. Res. Lett. 43, 674–682 (2016).

    Article  ADS  Google Scholar 

  14. Fichtner, A. et al. The Collaborative Seismic Earth Model: Generation 1. Geophys. Res. Lett. 45, 4007–4016 (2018).

    Article  ADS  Google Scholar 

  15. Banerdt, W. B. et al. Initial results from the InSight mission on Mars. Nat. Geosci. 13, 183–189 (2020).

    Article  ADS  Google Scholar 

  16. Giardini, D. et al. The seismicity of Mars. Nat. Geosci. 13, 205–212 (2020).

    Article  ADS  Google Scholar 

  17. Stähler, S. C. et al. Seismic detection of the martian core. Science 373, 443–448 (2021).

    Article  ADS  Google Scholar 

  18. Nunn, C. et al. Lunar seismology: a data and instrumentation review. Space Sci. Rev. 216, 89 (2020).

    Article  ADS  Google Scholar 

  19. Tkalčić, H., Phạm, T.-S. & Wang, S. The Earth’s coda correlation wavefield: rise of the new paradigm and recent advances. Earth Sci. Rev. 208, 103285 (2020).

    Article  Google Scholar 

  20. Phạm, T.-S., Tkalčić, H., Sambridge, M. & Kennett, B. L. N. Earth’s correlation wavefield: late coda correlation. Geophys. Res. Lett. 45, 3035–3042 (2018).

    Article  ADS  Google Scholar 

  21. Wang, S. & Tkalčić, H. Seismic event coda-correlation’s formation: implications for global seismology. Geophys. J. Int. 222, 1283–1294 (2020).

    Article  ADS  Google Scholar 

  22. Tkalčić, H. & Phạm, T.-S. Excitation of the global correlation wavefield by large earthquakes. Geophys. J. Int. 223, 1769–1779 (2020).

    Article  ADS  Google Scholar 

  23. Aki, K. & Richards, P. G. Quantitative Seismology (Univ. Science Books, 2009).

  24. Doornbos, D. J. & Hilton, T. Models of the core-mantle boundary and the travel times of internally reflected core phases. J. Geophys. Res.: Solid Earth 94, 15741–15751 (1989).

    Article  Google Scholar 

  25. Lay, T., Williams, Q. & Garnero, E. J. The core–mantle boundary layer and deep Earth dynamics. Nature 392, 461–468 (1998).

    Article  ADS  Google Scholar 

  26. Ma, X. & Tkalčić, H. CCREM: new reference Earth model from the global coda-correlation wavefield. J. Geophys. Res. Solid Earth 126, e2021JB02251 (2021).

    Article  Google Scholar 

  27. Plesa, A.-C. et al. Present-day Mars’ Seismicity predicted from 3-D thermal evolution models of interior dynamics. Geophys. Res. Lett. 45, 2580–2589 (2018).

    Article  ADS  Google Scholar 

  28. Khan, A. et al. A geophysical perspective on the bulk composition of Mars. J. Geophys. Res.: Planets 123, 575–611 (2018).

    Article  ADS  Google Scholar 

  29. Golombek, M. P., Banerdt, W. B., Tanaka, K. L. & Tralli, D. M. A prediction of Mars seismicity from surface faulting. Science 258, 979–981 (1992).

    Article  ADS  Google Scholar 

  30. Mars Seismic Catalogue, InSight Mission; V10 2022-04-01. 25 MB (InSight Marsquake Service, 2022); https://doi.org/10.12686/A16

  31. Taylor, J., Teanby, N. A. & Wookey, J. Estimates of seismic activity in the Cerberus Fossae region of Mars. J. Geophys. Res.: Planets 118, 2570–2581 (2013).

    Article  ADS  Google Scholar 

  32. Vaucher, J. et al. The morphologies of volcanic landforms at Central Elysium Planitia: evidence for recent and fluid lavas on Mars. Icarus 200, 39–51 (2009).

    Article  ADS  Google Scholar 

  33. Anderson, R. C. et al. Primary centers and secondary concentrations of tectonic activity through time in the western hemisphere of Mars. J. Geophys. Res. Planets 106, 20563–20585 (2001).

    Article  ADS  Google Scholar 

  34. SEIS raw data, Insight Mission. IPGP, JPL, CNES, ETHZ, ICL, MPS, ISAE-Supaero, LPG, MFSC (InSight Mars SEIS Data Service, 2019).

  35. Brinkman, N. et al. First focal mechanisms of marsquakes. J. Geophys. Res. Planets 126, e2020JE006546 (2021).

    Article  ADS  Google Scholar 

  36. Fernando, B. et al. Seismic constraints from a Mars impact experiment using InSight and Perseverance. Nat. Astron. 6, 59–64 (2022).

    Article  ADS  Google Scholar 

  37. Suemoto, Y., Ikeda, T. & Tsuji, T. Temporal variation and frequency dependence of seismic ambient noise on Mars from polarization analysis. Geophys. Res. Lett. 47, e2020GL087123 (2020).

    Article  ADS  Google Scholar 

  38. Kim, D. et al. Potential pitfalls in the analysis and structural interpretation of seismic data from the Mars InSight Mission. Bull. Seismol. Soc. Am. 111, 2982–3002 (2021).

    Article  Google Scholar 

  39. Bertka, C. M. & Fei, Y. Density profile of an SNC model Martian interior and the moment-of-inertia factor of Mars. Earth Planet. Sci. Lett. 157, 79–88 (1998).

    Article  ADS  Google Scholar 

  40. Clinton, J. et al. The Marsquake Service: securing daily analysis of SEIS data and building the Martian Seismicity Catalogue for InSight. Space Sci. Rev. 214, 133 (2018).

    Article  ADS  Google Scholar 

  41. Lognonné, P. et al. SEIS: Insight’s Seismic Experiment for Internal Structure of Mars. Space Sci. Rev. 215, 12 (2019).

    Article  ADS  Google Scholar 

  42. Sun, W. & Tkalčić, H. Repetitive marsquakes in Martian upper mantle. Nat. Commun. 13, 1695 (2022).

    Article  ADS  Google Scholar 

  43. Lammlein, D. R., Latham, G. V., Dorman, J., Nakamura, Y. & Ewing, M. Lunar seismicity, structure, and tectonics. Rev. Geophys. 12, 1–21 (1974).

    Article  ADS  Google Scholar 

  44. Lognonné, P. et al. Constraints on the shallow elastic and anelastic structure of Mars from InSight seismic data. Nat. Geosci. 13, 213–220 (2020).

    Article  ADS  Google Scholar 

  45. Storchak, D. A. et al. Rebuild of the Bulletin of the International Seismological Centre (ISC)—part 2: 1980–2010. Geosci. Lett. 7, 18 (2020).

    Article  ADS  Google Scholar 

  46. Lin, F.-C. & Tsai, V. C. Seismic interferometry with antipodal station pairs. Geophys. Res. Lett. 40, 4609–4613 (2013).

    Article  ADS  Google Scholar 

  47. Scholz, J.-R. et al. Detection, analysis, and removal of glitches from InSight’s seismic data from Mars. Earth Space Sci. 7, e2020EA001317 (2020).

    Article  ADS  Google Scholar 

  48. Smith, D. E. et al. Mars Orbiter Laser Altimeter: experiment summary after the first year of global mapping of Mars. J. Geophys. Res. Planets 106, 23689–23722 (2001).

    Article  ADS  Google Scholar 

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Acknowledgements

We acknowledge NASA (National Aeronautics and Space Administration), CNES (Centre National D’Etudes Spatiales), their partner agencies and Institutions UKSA (United Kingdom Sailing Academy), SSO (Swiss Space Office), DLR (Deutsches Zentrum für Luft- und Raumfahrt), JPL (Jet Propulsion Laboratory), IPGP-CNRS (Institut de Physique du Globe de Paris, Centre National de la Recherche Scientifique), ETHZ (Eidgenössische Technische Hochschule Zürich), IC (Imperial College), MPS-MPG (Max Planck Institute for Solar System Research), the flight operations team at JPL, SISMOC (SEIS on Mars Operations Center), MSDS (Mars SEIS Data Service), IRIS-DMC and PDS (Planetary Data System, NASA) for the development of SEIS and for providing SEED (Standard for the Exchange of Earthquake Data) SEIS data. This study is supported by computational resources provided by the Australian Government through the National Computational Infrastructure facility under the ANU (Australian National University) Merit Allocation Scheme. We would like to acknowledge the ANU PhD Scholarship supporting S.W. through his degree. H.T.’s time on this project is supported through a combination of grants administrated by the ANU.

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Authors and Affiliations

  1. Research School of Earth Sciences, The Australian National University, Canberra, Australian Capital Territory, Australia

    Sheng Wang & Hrvoje Tkalčić

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Contributions

Both authors contributed to the results and determined the course of the study based on methodological developments in S.W.’s PhD work under the supervision and guidance of H.T. S.W. processed the seismic data. Both authors contributed to the analyses, interpretation of the results and manuscript writing.

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Correspondence to Sheng Wang or Hrvoje Tkalčić.

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Nature Astronomy thanks Steven Gibbons, Christine Houser and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Selections of source mechanisms and source pairs for constructing global inter-source correlograms.

(a) We select thrust events (red beach balls) and exclude events of other source mechanisms (black beach balls). We extract Mw6.5+ earthquakes in 2000–2020 and their source mechanism solutions from the NEIC catalog. The stations (triangles) originate from the Global Seismographic Networks (network codes II and IU). We use two single stations, II.PFO and II.NNA (blue triangles) to showcase single-station inter-source correlograms in Fig. 1. (b) Source pairs selection based on source-receiver geometry. Each source pair is represented by a great-circle path passing through two sources. We select source pairs for which the great-circle paths are <20° spherical distance away from the receiver (II.NNA). Red lines represent the selected source pairs, while the black lines represent the excluded source pairs for the distance ≥20°. We plot randomly downsampled great-circle paths by 10% to avoid intense overlapping.

Supplementary information

Supplementary Information

Supplementary materials and method details, Figs. 1–38 and Table 1.

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Wang, S., Tkalčić, H. Scanning for planetary cores with single-receiver intersource correlations. Nat Astron 6, 1272–1279 (2022). https://doi.org/10.1038/s41550-022-01796-8

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