Letter | Published:

Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation

Nature volume 526, pages 245248 (08 October 2015) | Download Citation


The Earth’s inner core grows by the freezing of liquid iron at its surface. The point in history at which this process initiated marks a step-change in the thermal evolution of the planet. Recent computational and experimental studies1,2,3,4,5 have presented radically differing estimates of the thermal conductivity of the Earth’s core, resulting in estimates of the timing of inner-core nucleation ranging from less than half a billion to nearly two billion years ago. Recent inner-core nucleation (high thermal conductivity) requires high outer-core temperatures in the early Earth that complicate models of thermal evolution. The nucleation of the core leads to a different convective regime6 and potentially different magnetic field structures that produce an observable signal in the palaeomagnetic record and allow the date of inner-core nucleation to be estimated directly. Previous studies searching for this signature have been hampered by the paucity of palaeomagnetic intensity measurements, by the lack of an effective means of assessing their reliability, and by shorter-timescale geomagnetic variations. Here we examine results from an expanded Precambrian database of palaeomagnetic intensity measurements7 selected using a new set of reliability criteria8. Our analysis provides intensity-based support for the dominant dipolarity of the time-averaged Precambrian field, a crucial requirement for palaeomagnetic reconstructions of continents. We also present firm evidence for the existence of very long-term variations in geomagnetic strength. The most prominent and robust transition in the record is an increase in both average field strength and variability that is observed to occur between a billion and 1.5 billion years ago. This observation is most readily explained by the nucleation of the inner core occurring during this interval9; the timing would tend to favour a modest value of core thermal conductivity and supports a simple thermal evolution model for the Earth.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    , , & Thermal and electrical conductivity of iron at Earth’s core conditions. Nature 485, 355–358 (2012)

  2. 2.

    , , , & Electrical and thermal transport properties of iron and iron-silicon alloy at high pressure. Geophys. Res. Lett. 40, 5377–5381 (2013)

  3. 3.

    et al. The high conductivity of iron and thermal evolution of the Earth’s core. Phys. Earth Planet. Inter. 224, 88–103 (2013)

  4. 4.

    , & Electrical resistivity and thermal conductivity of liquid Fe alloys at high P and T, and heat flux in Earth's core. Proc. Natl Acad. Sci. USA 109, 4070–4073 (2012)

  5. 5.

    , & Effects of electron correlations on transport properties of iron at Earth’s core conditions. Nature 517, 605–607 (2015)

  6. 6.

    , & Observations and models of the long-term evolution of Earth's magnetic field. Space Sci. Rev. 155, 337–370 (2010)

  7. 7.

    , & The intensity of the geomagnetic field in the late-Archaean: new measurements and an analysis of the updated IAGA palaeointensity database. Earth Planets Space 61, 9–22 (2009)

  8. 8.

    & A new set of qualitative reliability criteria to aid inferences on palaeomagnetic dipole moment variations through geological time. Frontiers Earth Sci. 2, 21–29 (2014)

  9. 9.

    , & Modelling the palaeo-evolution of the geodynamo. Geophys. J. Int. 179, 1414–1428 (2009)

  10. 10.

    & in Timescales of the Internal Geomagnetic Field Vol. 145 of Geophysical Monograph Series (ed. ) 85–100 (AGU, 2004)

  11. 11.

    & Intensity of the Earth’s magnetic-field since precambrian from Thellier-type paleointensity data and inferences on the thermal history of the core. Geophys. J. Int. 108, 613–620 (1992)

  12. 12.

    & Analysis of long-term variations in the geomagnetic poloidal field intensity and evaluation of their relationship with global geodynamics. Geophys. J. Int. 152, 392–415 (2003)

  13. 13.

    Time variations in geomagnetic intensity. Rev. Geophys. 41, 1004, (2003)

  14. 14.

    , & Evidence for a very-long-term trend in geomagnetic secular variation. Nature Geosci. 1, 395–398 (2008)

  15. 15.

    , & Long-term evolution of the geomagnetic dipole moment. Phys. Earth Planet. Inter. 147, 239–246 (2004)

  16. 16.

    & in Geomagnetism Vol. 5 of Treatise on Geophysics (ed. ) Ch. 13, 510–563 (Elsevier, 2007)

  17. 17.

    , , , & The intensity of the geomagnetic field from 2.4 Ga old Indian dykes. Geochem. Geophys. Geosyst. 15, 2426–2437 (2014)

  18. 18.

    Proterozoic low orbital obliquity and axial-dipolar geomagnetic field from evaporite palaeolatitudes. Nature 444, 51–55 (2006)

  19. 19.

    , , & On the low-inclination bias of the Precambrian geomagnetic field. Precambr. Res. 244, 23–32 (2014)

  20. 20.

    , , & PADM2M: a penalized maximum likelihood model of the 0–2 Ma palaeomagnetic axial dipole moment. Geophys. J. Int. 184, 1069–1089 (2011)

  21. 21.

    , & Geomagnetic dipole strength and reversal rate over the past two million years. Nature 435, 802–805 (2005)

  22. 22.

    , , & Paleointensity results from the Jurassic: new constraints from submarine basaltic glasses of ODP Site 801C. Geochem. Geophys. Geosyst. 14, 4718–4733 (2013)

  23. 23.

    , , & Magnetic force microscopy reveals meta-stable magnetic domain states that prevent reliable absolute palaeointensity experiments. Nature Commun. 5, 4548, (2014)

  24. 24.

    & Thermochemical remanent magnetization in Precambrian rocks: are we sure the geomagnetic field was weak? J. Geophys. Res. 110, B06103 (2005)

  25. 25.

    & in Timescales of the Paleomagnetic Field Vol. 145 Geophysical Monograph Series (eds , , & ) 328 (AGU, 2004)

  26. 26.

    et al. Possible links between long-term geomagnetic variations and whole-mantle convection processes. Nature Geosci. 5, 526–533 (2012)

  27. 27.

    , & Absolute geomagnetic paleointensity as recorded by similar to 1.09 Ga Lake Shore Traps (Keweenaw Peninsula, Michigan). Stud. Geophys. Geodaet. 57, 565–584 (2013)

  28. 28.

    An integrated rock magnetic approach to the selection or rejection of ancient basalt samples for paleointensity experiments. Phys. Earth Planet. Inter. 75, 329–342 (1993)

  29. 29.

    & Palaeosecular variation, field reversals and the stability of the geodynamo in the Precambrian. Geophys. J. Int. 199, 1515–1526 (2014)

  30. 30.

    et al. On the increase in thermal diffusivity caused by the perovskite to post-perovskite phase transition and its implications for mantle dynamics. Earth Planet. Sci. Lett. 319–320, 96–103 (2012)

  31. 31.

    The reliability of paleomagnetic data. Tectonophysics 184, 1–9 (1990)

  32. 32.

    & Instability of thermoremanence and the problem of estimating the ancient geomagnetic field strength from non-single-domain recorders. Proc. Natl Acad. Sci. USA 112, 36, (2015)

Download references


We thank T. Torsvik for organising the 7th Nordic Supercontinents Meeting and acknowledge financial support for this from the European Research Council (ERC Advanced Grant 267631) and the Research Council of Norway through its Centres of Excellence funding scheme (CEED 223272). We also thank J. Rees and L. Waszek for discussions. A.J.B. acknowledges funding from a NERC standard grant (NE/H021043/1). G.A.P. acknowledges funding from an NSFC grant (41374072). L.T. acknowledges funding from an NSF grant (EAR 1345003).

Author information


  1. Department of Earth, Ocean and Ecological Sciences, University of Liverpool, Liverpool L69 7ZE, UK

    • A. J. Biggin
    •  & R. Holme
  2. Department of Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, 1400 Townsend Drive, Michigan 49931, USA

    • E. J. Piispa
  3. Department of Physics, Division of Materials Physics, PB 64, FI-00014 University of Helsinki, Helsinki, Finland

    • L. J. Pesonen
    •  & T. Veikkolainen
  4. Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China

    • G. A. Paterson
  5. Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0220 USA

    • L. Tauxe


  1. Search for A. J. Biggin in:

  2. Search for E. J. Piispa in:

  3. Search for L. J. Pesonen in:

  4. Search for R. Holme in:

  5. Search for G. A. Paterson in:

  6. Search for T. Veikkolainen in:

  7. Search for L. Tauxe in:


A.J.B. designed the study. A.J.B., E.J.P., L.J.P. and T.V. assigned the QPI values. A.J.B., R.H., G.A.P., L.J.P., T.V. and L.T. wrote the paper. A.J.B., G.A.P. and T.V. analysed the data.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to A. J. Biggin.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    Supplementary Table 1 shows the raw dataset used in this study. The format is identical to the PINT database (see http://earth.liv.ac.uk/pint/ for full details) with QPI criteria and values appended in the final column.

  2. 2.

    Supplementary Table 2

    Supplementary Table 2 contains a TAA summary of data with QPI values of at least 3 showing the Mantle Groups and Secular Variation (SV) Groups used in the new likelihood test (see Methods for details). For definition of Interval, refer to the main text. Ref No. refers to the Reference Number within the PINT database (http://earth.liv.ac.uk/pint/); NData refers to the number of site mean V(A)DM estimates; V(A)DMMed and V(A)DMIQR refer to the median and interquartile range of the V(A)DM estimates respectively.

  3. 3.

    Supplementary Table 3

    Supplementary Table 3 contains summary data for time intervals referred to in the main text and Figure 3 using minimum QPI values in the range 1-5. AgeMin and AgeMax refer to the minimum and maximum age estimates of the data within each interval. V(A)DMMed and V(A)DMIQR V(A)DMMed and V(A)DMIQR refer, respectively, to the median and interquartile range of the V(A)DM estimates within each interval and V(A)DM+95 and V(A)DM-95 refer to the 95% confidence limits on the median calculated using 10,000 bootstraps. NData refers to the number of V(A)DM estimates in each interval and NRef refers to the number of published studies that these are drawn from. In the final column, the P values produced by a series of Kolmogorv-Smirnov tests for equality of probability distribution are shown. The results are colour-coded according to the confidence with which the null hypothesis of identical distributions can be rejected as follows: red >99% confidence, orange >95% confidence, yellow > 90% confidence, green < 90% confidence. *Data in the RECENT interval were not assigned QPI values but rather selected on the basis of passing the criteria described in the Methods section.

About this article

Publication history






Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.