Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Months-long thousand-kilometre-scale wobbling before great subduction earthquakes

Abstract

Megathrust earthquakes are responsible for some of the most devastating natural disasters1. To better understand the physical mechanisms of earthquake generation, subduction zones worldwide are continuously monitored with geophysical instrumentation. One key strategy is to install stations that record signals from Global Navigation Satellite Systems2,3 (GNSS), enabling us to track the non-steady surface motion of the subducting and overriding plates before, during and after the largest events4,5,6. Here we use a recently developed trajectory modelling approach7 that is designed to isolate secular tectonic motions from the daily GNSS time series to show that the 2010 Maule, Chile (moment magnitude 8.8) and 2011 Tohoku-oki, Japan (moment magnitude 9.0) earthquakes were preceded by reversals of 4–8 millimetres in surface displacement that lasted several months and spanned thousands of kilometres. Modelling of the surface displacement reversal that occurred before the Tohoku-oki earthquake suggests an initial slow slip followed by a sudden pulldown of the Philippine Sea slab so rapid that it caused a viscoelastic rebound across the whole of Japan. Therefore, to understand better when large earthquakes are imminent, we must consider not only the evolution of plate interface frictional processes but also the dynamic boundary conditions from deeper subduction processes, such as sudden densification of metastable slab.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Locations of the great earthquakes and of the continuous GNSS stations that capture the preceding transient motions.
Fig. 2: Time series before Tohoku-oki and Maule and the effect of noise removal with GrAtSiD.
Fig. 3: Visualizing the along-strike signal migration and reversal of Japan in the years and months preceding the Tohoku-oki earthquake.
Fig. 4: Visualizing the reversals motions in South America in the months preceding the Maule earthquake.
Fig. 5: Surface velocities and kinematic models of apparent slip or backslip for three daily time windows during the unstable period preceding the Tohoku-oki earthquake.
Fig. 6: Cartoon (not to scale) to illustrate the possible processes explaining the deformation recorded in the unstable period captured before the Tohoku-oki earthquake.

Similar content being viewed by others

Data availability

The daily GNSS displacement time series and the predicted displacements from fluid loading models are available in a data supplement to this paper66.

Code availability

To create the maps in the figures and Supplementary videos, we used Python package Matplotlib67 and Generic Mapping Tools68. The GrAtSiD code used for the trajectory modelling in this study can be provided upon request from the corresponding author.

References

  1. Kajitani, Y., Chang, S. E. & Tatano, H. Economic impacts of the 2011 Tohoku-Oki earthquake and tsunami. Earthq. Spectra 29, 457–478 (2013).

    Google Scholar 

  2. Sagiya, T., Miyazaki, S. I. & Tada, T. Continuous GPS array and present-day crustal deformation of Japan. Pure Appl. Geophys. 157, 2303–2322 (2000).

    ADS  Google Scholar 

  3. Báez, J. C. et al. The Chilean GNSS network: current status and progress toward early warning applications. Seismol. Res. Lett. 89, 1546–1554 (2018).

    Google Scholar 

  4. Heki, K. & Mitsui, Y. Accelerated Pacific plate subduction following interplate thrust earthquakes at the Japan trench. Earth Planet. Sci. Lett. 363, 44–49 (2013).

    CAS  ADS  Google Scholar 

  5. Loveless, J. P. & Meade, B. J. Two decades of spatiotemporal variations in subduction zone coupling offshore Japan. Earth Planet. Sci. Lett. 436, 19–30 (2016).

    CAS  ADS  Google Scholar 

  6. Melnick, D. et al. The super-interseismic phase of the megathrust earthquake cycle in Chile. Geophys. Res. Lett. 44, 784–791 (2017).

    ADS  Google Scholar 

  7. Bedford, J. & Bevis, M. Greedy automatic signal decomposition and its application to daily GPS time series. J. Geophys. Res. Solid Earth 123, 6992–7003 (2018).

    ADS  Google Scholar 

  8. Reid, H. F. The Mechanics of the Earthquake, The California Earthquake of April 18, 1906, Report of the State Investigation Commission Vol. 2, 16–28 (Carnegie Institution of Washington, 1910).

  9. Schurr, B. et al. Gradual unlocking of plate boundary controlled initiation of the 2014 Iquique earthquake. Nature 512, 299–302 (2014).

    CAS  PubMed  ADS  Google Scholar 

  10. Mavrommatis, A. P., Segall, P. & Johnson, K. M. A decadal-scale deformation transient prior to the 2011 Mw 9.0 Tohoku-oki earthquake. Geophys. Res. Lett. 41, 4486–4494 (2014).

    ADS  Google Scholar 

  11. Wang, K. et al. Learning from crustal deformation associated with the M9 2011 Tohoku-oki earthquake. Geosphere 14, 552–571 (2018).

    ADS  Google Scholar 

  12. Kato, A. et al. Propagation of slow slip leading up to the 2011 Mw 9.0 Tohoku-Oki earthquake. Science 335, 705–708 (2012).

    CAS  PubMed  ADS  Google Scholar 

  13. Johnson, P. A. et al. Acoustic emission and microslip precursors to stick-slip failure in sheared granular material. Geophys. Res. Lett. 40, 5627–5631 (2013).

    ADS  Google Scholar 

  14. Kaproth, B. M. & Marone, C. Slow earthquakes, preseismic velocity changes, and the origin of slow frictional stick-slip. Science 341, 1229–1232 (2013).

    CAS  PubMed  ADS  Google Scholar 

  15. Lohman, R. B. & Murray, J. R. The SCEC geodetic transient detection validation exercise. Seismol. Res. Lett. 84, 419–425 (2013).

    Google Scholar 

  16. Dill, R. & Dobslaw, H. Numerical simulations of global-scale high-resolution hydrological crustal deformations. J. Geophys. Res. Solid Earth 118, 5008–5017 (2013).

    ADS  Google Scholar 

  17. van Dam, T. et al. Crustal displacements due to continental water loading. Geophys. Res. Lett. 28, 651–654 (2001).

    ADS  Google Scholar 

  18. Heki, K. Snow load and seasonal variation of earthquake occurrence in Japan. Earth Planet. Sci. Lett. 207, 159–164 (2003).

    CAS  ADS  Google Scholar 

  19. Wdowinski, S., Bock, Y., Zhang, J., Fang, P. & Genrich, J. Southern California permanent GPS geodetic array: spatial filtering of daily positions for estimating coseismic and postseismic displacements induced by the 1992 Landers earthquake. J. Geophys. Res. Solid Earth 102, 18057–18070 (1997).

    Google Scholar 

  20. Bouchon, M. et al. Potential slab deformation and plunge prior to the Tohoku, Iquique and Maule earthquakes. Nat. Geosci. 9, 380–383 (2016).

    CAS  ADS  Google Scholar 

  21. Gardonio, B. et al. Seismic activity preceding the 2011 M w 9.0 Tohoku earthquake, Japan, analyzed with multidimensional template matching. J. Geophys. Res. Solid Earth 124, 6815–6831 (2019).

    Google Scholar 

  22. Ito, Y. et al. Episodic slow slip events in the Japan subduction zone before the 2011 Tohoku-Oki earthquake. Tectonophysics 600, 14–26 (2013).

    ADS  Google Scholar 

  23. Ito, Y., Hino, R., Suzuki, S. & Kaneda, Y. Episodic tremor and slip near the Japan Trench prior to the 2011 Tohoku-Oki earthquake. Geophys. Res. Lett. 42, 1725–1731 (2015).

    ADS  Google Scholar 

  24. Katakami, S. et al. Spatiotemporal variation of tectonic tremor activity before the Tohoku-Oki earthquake. J. Geophys. Res. Solid Earth 123, 9676–9688 (2018).

    ADS  Google Scholar 

  25. Becker, T. W., Hashima, A., Freed, A. M. & Sato, H. Stress change before and after the 2011 M9 Tohoku-oki earthquake. Earth Planet. Sci. Lett. 504, 174–184 (2018).

    CAS  ADS  Google Scholar 

  26. Yokota, Y. & Koketsu, K. A very long-term transient event preceding the 2011 Tohoku earthquake. Nat. Commun. 6, 5934 (2015).

    CAS  PubMed  ADS  Google Scholar 

  27. Pollitz, F. F. Coseismic deformation from earthquake faulting on a layered spherical Earth. Geophys. J. Int. 125, 1–14 (1996).

    Google Scholar 

  28. Hayes, G. P. et al. Slab2, a comprehensive subduction zone geometry model. Science 362, 58–61 (2018).

    CAS  PubMed  ADS  Google Scholar 

  29. Rogers, G. & Dragert, H. Episodic tremor and slip on the Cascadia subduction zone: the chatter of silent slip. Science 300, 1942–1943 (2003).

    CAS  PubMed  ADS  Google Scholar 

  30. Yamashita, Y. et al. Migrating tremor off southern Kyushu as evidence for slow slip of a shallow subduction interface. Science 348, 676–679 (2015).

    CAS  PubMed  ADS  Google Scholar 

  31. Ide, S., Beroza, G. C., Shelly, D. R. & Uchide, T. A scaling law for slow earthquakes. Nature 447, 76–79 (2007).

    CAS  PubMed  ADS  Google Scholar 

  32. Savage, J. C. A dislocation model of strain accumulation and release at a subduction zone. J. Geophys. Res. Solid Earth 88, 4984–4996 (1983).

    Google Scholar 

  33. Kodaira, S. et al. High pore fluid pressure may cause silent slip in the Nankai Trough. Science 304, 1295–1298 (2004).

    CAS  PubMed  ADS  Google Scholar 

  34. Tsuji, Y., Nakajima, J. & Hasegawa, A. Tomographic evidence for hydrated oceanic crust of the Pacific slab beneath northeastern Japan: implications for water transportation in subduction zones. Geophys. Res. Lett. 35, L14308 (2008).

  35. Liu, X., Zhao, D. & Li, S. Seismic attenuation tomography of the Northeast Japan arc: insight into the 2011 Tohoku earthquake (Mw 9.0) and subduction dynamics. J. Geophys. Res. Solid Earth 119, 1094–1118 (2014).

    ADS  Google Scholar 

  36. Taetz, S., John, T., Bröcker, M., Spandler, C. & Stracke, A. Fast intraslab fluid-flow events linked to pulses of high pore fluid pressure at the subducted plate interface. Earth Planet. Sci. Lett. 482, 33–43 (2018).

    CAS  ADS  Google Scholar 

  37. Ujiie, K. Chemical origin of tectonic tremor. Nat. Geosci. 12, 962–963 (2019).

  38. Incel, S. et al. Reaction-induced embrittlement of the lower continental crust. Geology 47, 235–238 (2019).

    CAS  ADS  Google Scholar 

  39. Austrheim, H. Eclogitization of lower crustal granulites by fluid migration through shear zones. Earth Planet. Sci. Lett. 81, 221–232 (1987).

    CAS  ADS  Google Scholar 

  40. John, T. & Schenk, V. Partial eclogitisation of gabbroic rocks in a late Precambrian subduction zone (Zambia): prograde metamorphism triggered by fluid infiltration. Contrib. Mineral. Petrol. 146, 174–191 (2003).

    CAS  ADS  Google Scholar 

  41. Seno, T. & Maruyama, S. Paleogeographic reconstruction and origin of the Philippine Sea. Tectonophysics 102, 53–84 (1984).

    ADS  Google Scholar 

  42. Bach, W. & Früh-Green, G. L. Alteration of the oceanic lithosphere and implications for seafloor processes. Elements 6, 173–178 (2010).

    CAS  Google Scholar 

  43. Burnley, P. C., Green, H. W. & Prior, D. J. Faulting associated with the olivine to spinel transformation in Mg2GeO4 and its implications for deep-focus earthquakes. J. Geophys. Res. Solid Earth 96, 425–443 (1991).

    Google Scholar 

  44. Thielmann, M., Rozel, A., Kaus, B. J. P. & Ricard, Y. Intermediate-depth earthquake generation and shear zone formation caused by grain size reduction and shear heating. Geology 43, 791–794 (2015).

    ADS  Google Scholar 

  45. Fukao, Y. & Obayashi, M. Subducted slabs stagnant above, penetrating through, and trapped below the 660 km discontinuity. J. Geophys. Res. Solid Earth 118, 5920–5938 (2013).

    ADS  Google Scholar 

  46. Kawakatsu, H. & Yoshioka, S. Metastable olivine wedge and deep dry cold slab beneath southwest Japan. Earth Planet. Sci. Lett. 303, 1–10 (2011).

    CAS  ADS  Google Scholar 

  47. Panet, I., Bonvalot, S., Narteau, C., Remy, D. & Lemoine, J. M. Migrating pattern of deformation prior to the Tohoku-Oki earthquake revealed by GRACE data. Nat. Geosci. 11, 367–373 (2018).

    CAS  ADS  Google Scholar 

  48. Wang, L. & Burgmann, R. Statistical significance of precursory gravity changes before the 2011 M w 9.0 Tohoku-Oki earthquake. Geophys. Res. Lett. 46, 7323–7332 (2019).

    ADS  Google Scholar 

  49. Blewitt, G., Hammond, W. C. & Kreemer, C. Harnessing the GPS data explosion for interdisciplinary science. Eos 99, https://doi.org/10.1029/2018EO104623 (2018).

  50. Gendt, G. et al. GFZ Analysis Center of IGS. Annual Report for 2013 1–10 (GFZ German Research Centre for Geosciences, 2013); ftp://ftp.gfz-potsdam.de/GNSS/DOCS/IGS_repro2/GFZ_igs_annual_report_2013_iss1-0.pdf.

  51. Deng, Z., Fritsche, M., Nischan, T. & Bradke, M. Multi-GNSS Ultra Rapid Orbit-, Clock- & EOP-Product Series (GFZ Data Services, 2016); https://doi.org/10.5880/GFZ.1.1.2016.003.

  52. Rebischung, P., Altamimi, Z., Ray, J. & Garayt, B. The IGS contribution to ITRF2014. J. Geodyn. 90, 611–630 (2016).

    ADS  Google Scholar 

  53. Altamimi, Z., Rebischung, P., Métivier, L. & Collilieux, X. ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions. J. Geophys. Res. Solid Earth 121, 6109–6131 (2016).

    ADS  Google Scholar 

  54. Nakagawa, H., et al. Development and validation of GEONET New Analysis Strategy (Version 4) [in Japanese] Annual Report of the Geographical Survey Institute Vol. 118, 1–8 (GSI, 2009); https://www.gsi.go.jp/common/000054716.pdf.

  55. Needell, D., Tropp, J. & Vershynin, R. Greedy signal recovery review. In 2008 42nd Asilomar Conf. on Signals, Systems and Computers 1048–1050, https://core.ac.uk/reader/23798095 (IEEE, 2008).

  56. Bevis, M. & Brown, A. Trajectory models and reference frames for crustal motion geodesy. J. Geod. 88, 283–311 (2014).

    ADS  Google Scholar 

  57. Rebischung, P. et al. IGS08: the IGS realization of ITRF2008. GPS Solutions 16(4), 483–494 (2012).

    Google Scholar 

  58. Zumberge, J. F., Heflin, M. B., Jefferson, D. C., Watkins, M. M. & Webb, F. H. Precise point positioning for the efficient and robust analysis of GPS data from large networks. J. Geophys. Res. Solid Earth 102, 5005–5017 (1997).

    Google Scholar 

  59. Liu, L., Khan, S. A., van Dam, T., Ma, J. H. Y. & Bevis, M. Annual variations in GPS-measured vertical displacements near Upernavik Isstrøm (Greenland) and contributions from surface mass loading. J. Geophys. Res. Solid Earth 122, 677–691 (2017).

    ADS  Google Scholar 

  60. Kusche, J. E. J. O. & Schrama, E. J. O. Surface mass redistribution inversion from global GPS deformation and Gravity Recovery and Climate Experiment (GRACE) gravity data. J. Geophys. Res. Solid Earth 110, B09409 (2005).

  61. Borsa, A. A., Agnew, D. C. & Cayan, D. R. Ongoing drought-induced uplift in the western United States. Science 345, 1587–1590 (2014).

    CAS  PubMed  ADS  Google Scholar 

  62. Bevis, M. et al. Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing. Proc. Natl Acad. Sci. USA 116, 1934–1939 (2019).

    CAS  PubMed  ADS  Google Scholar 

  63. Grant, M. & Boyd, S. CVX: Matlab software for disciplined convex programming. Version 2.1, http://cvxr.com/cvx/citing/ (2014).

  64. Moreno, M. et al. Locking of the Chile subduction zone controlled by fluid pressure before the 2010 earthquake. Nat. Geosci. 7, 292–296 (2014).

    CAS  ADS  Google Scholar 

  65. Chen, Y. W., Wu, J. & Suppe, J. Southward propagation of Nazca subduction along the Andes. Nature 565, 441–447 (2019).

    CAS  PubMed  ADS  Google Scholar 

  66. Bedford, J. et al. Trajectory models for daily displacement time series in the five years preceding the 2010 Maule Mw 8.8, Chile, and 2011 Tohoku-oki Mw 9.0, Japan earthquakes (GFZ Data Services, 2020); https://doi.org/10.5880/GFZ.4.1.2020.001.

  67. Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).

    Google Scholar 

  68. Wessel, P., Smith, W. H., Scharroo, R., Luis, J. & Wobbe, F. Generic mapping tools: improved version released. Eos 94, 409–410 (2013).

    ADS  Google Scholar 

Download references

Acknowledgements

We thank the Geospatial Information Authority of Japan (GSI) and the Nevada Geodetic Laboratory (NGL), University of Nevada, for their assistance and for providing time series for this study. We thank Y. Bock and K. Heki for comments. J.R.B. thanks S. Sobolev for his comments. J.R.B. thanks the German Science Foundation (DFG) for grant MO-2310/3. M.M. acknowledges support from FONDECYT 1181479, the Millennium Nucleus “The Seismic Cycle Along Subduction Zones” grant NC160025, and the Research Center for Integrated Disaster Risk Management (CIGIDEN), CONICYT/FONDAP 15110017. J.C.B. acknowledges support from FONDECYT projects 1170430 and 1181479.

Author information

Authors and Affiliations

Authors

Contributions

Z.D. and J.C.B. processed the South American network solutions. J.R.B., M.M. and B.S. performed postprocessing (analysis of daily GNSS time series). M.B., J.C.B., Z.D. and J.R.B. investigated the processing artefacts and non-tectonic signals. T.J., O.O. and J.R.B. performed the geophysical and geological interpretation. J.R.B. did the kinematic modelling. All authors assisted in editing the manuscript.

Corresponding author

Correspondence to Jonathan R. Bedford.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Yehuda Bock, Kosuke Heki and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Stations used in the processing and analysis of the pre-Maule-earthquake GNSS data.

Locations of IGS stations used to define the reference frame of the network solutions are shown in gold. Black dots are the stations where network solutions are used in the time series analysis of the pre-Maule signals. Coloured triangles indicate locations of time series shown in Fig. 2 and Extended Data Fig. 3. There are some stations used to define the reference frame that are not used in the time series analysis owing to lack of data in the desired window (1 January 2005 until 25 February 2010).

Source Data

Extended Data Fig. 2 Time series before the Tohoku-oki earthquake and the effect of noise removal with GrAtSiD in all three directional components.

Left panels show the pre-Tohoku-oki F3 time series. Right panels show these time series after the removal of background seasonal and common-mode noise (with the GrAtSiD routine). The transient behaviour in the months before Tohoku-oki is heavily obscured by seasonal and common-mode noise. Colours correspond to locations on Fig. 1. For clarity, steps have been removed from all time series. Time series in these plots extend until three days before the mainshock.

Source Data

Extended Data Fig. 3 Time series before the Maule earthquake and the effect of noise removal with GrAtSiD in all three directional components.

Left panels show the pre-Maule time series. Right panels show these time series after the removal of background seasonal and common mode noise (with the GrAtSiD routine). The transient behaviour in the months before Maule event is heavily obscured by seasonal and common-mode noise. Colours correspond to locations on Fig. 1. For clarity, steps have been removed from all time series. Time series in these plots extend until two days before the mainshock.

Source Data

Extended Data Fig. 4 Visualizing the along-strike signal migration and reversal of Japan in the years and months preceding the Tohoku-oki earthquake for all three directional components.

Velocities within non-overlapping rectangular regions before the Tohoku-oki earthquake. The velocity for each region is detrended relative to the median velocity of that region between 1 January 2006 and 8 March 2011. Green lines indicate the along-strike locations and times of earthquakes of moment magnitude exceeding 6. Panels df are zoom-ins of panels ac between the beginning of September 2010 and the beginning of February 2011. The dashed line on panel d indicates the velocity front that migrates across Japan from the southwest (shown in Supplementary Videos 3 and 4 and Fig. 3).

Source Data

Extended Data Fig. 5 The corrections to the time series made possible after application of the regression model solved by GrAtSiD.

a, The example time series is for the East component of station Ooamishirasato in Japan. Blue dots show the time series input into the GrAtSiD routine. This time series has been corrected for the common-mode error. The red line shows the complete fit of the regression model solved by GrAtSiD. This includes steps, oscillation terms, the first-order polynomial and the multi-transients. The time series has been optimally tilted (detrended) for clarity of presentation. b, The time series (blue dots) and trajectory model (red line) after removal of the modelled step offsets. c, The time series and the regression model following the removal of the modelled seasonal and step terms. The remaining terms in the model are the first-order polynomial and multi-transients. It is these detrended modelled trajectories following seasonal and step removal (shown in panel c in red) that are represented in Supplementary Videos 38 and Figs. 3 and 4 and Extended Data Fig. 4.

Source Data

Extended Data Fig. 6 Investigating spatial extents of the pre-Maule-earthquake wobbling in the network solutions.

The map shows the locations of two groups of stations used in the investigation into spatial extent of the unstable period observed before the Maule earthquake. The time series show the average (median) deviation from median velocity at each station of the two groups in the above map for each directional component, where the median velocity of each station is determined between 1 January 2005 and 25 February 2010.

Source Data

Extended Data Fig. 7 Investigating spatial extents of the pre-Tohoku-oki-earthquake wobbling using the Nevada Geodetic Laboratory’s IGS08 PPP solutions.

The map shows the locations of two groups of stations used in the investigation into spatial extent of the unstable period observed before the Tohoku-oki earthquake. The time series show the average (median) deviation from median velocity at each station of the two groups in the above map for each directional component, where the median velocity of each station is determined between 1 January 2006 and 8 March 2011.

Source Data

Extended Data Fig. 8 Comparison of GSI’s F3 solutions with NGL’s IGS08 PPP solutions for selected stations across Japan before the Tohoku-oki earthquake.

All time series shown are in the East component. Circles show the F3 and crosses show the PPP solutions. Colours correspond to the stations located on the inset map.

Source Data

Extended Data Fig. 9 Comparing the transient surface motions recorded by GNSS and predicted by fluid-loading models before the Tohoku-oki earthquake.

The map shows the GNSS station locations used in the analysis comparing fluid-loading displacement predictions to GNSS displacement measurements for the pre-Tohoku-oki case. The time series show a comparison of the median velocity variations for GNSS-measured (GSI’s F3 solutions) and fluid-loading-predicted displacements at the locations in the map. Velocities are taken from the trends estimated by GrAtSiD. In the horizontal components, the prediction from fluid loading produces much lower velocities than those observed. In the vertical component, there is considerable deviation from steady-state velocity in both the GNSS observation and fluid-loading prediction but with visibly low agreement in sense of motion.

Source Data

Extended Data Fig. 10 Comparing the transient surface motions recorded by GNSS and predicted by fluid-loading models before the Maule earthquake.

The map shows the GNSS station locations used in the analysis comparing fluid-loading displacement predictions to GNSS displacement measurements for the pre-Maule case. The time series show a comparison of the median velocity variations for GNSS-measured and fluid-loading-predicted displacements at the locations in the map. Velocities are taken from the trends estimated by GrAtSiD. In the East component (in which the pre-Maule unstable motion is most pronounced) the prediction from fluid loading produces much lower deviation from steady-state velocities than those observed by GNSS.

Source Data

Supplementary information

Supplementary Information

This file contains detailed descriptions of the supplementary videos.

41586_2020_2212_MOESM2_ESM.mp4

A video showing the effect of removing common mode errors and seasonal oscillations from the Japanese daily GNSS time series.

41586_2020_2212_MOESM3_ESM.mp4

A video showing the effect of removing common mode errors and seasonal oscillations from the South American daily GNSS time series.

41586_2020_2212_MOESM4_ESM.mp4

A video showing the daily detrended velocities estimated from network GNSS displacement time series in Japan between 2006-01-01 and 2011-03-08.

41586_2020_2212_MOESM5_ESM.mp4

A video showing the daily detrended velocities estimated from network GNSS displacement time series in Japan between 2010-09-01 and 2011-03-08.

41586_2020_2212_MOESM6_ESM.mp4

A video showing the daily detrended velocities estimated from network GNSS displacement time series in South America between 2005-01-01 and 2010-02-25.

41586_2020_2212_MOESM7_ESM.mp4

A video showing the daily detrended velocities estimated from network GNSS displacement time series in South America between 2009-04-01 and 2010-02-25.

A video showing modelled kinematics of the subduction plate interfaces in Japan between 2010-09-01 and 2011-03-08.

41586_2020_2212_MOESM9_ESM.mp4

A video showing the daily detrended velocities estimated from PPP GNSS displacement time series in Japan and surrounding countries between 2010-01-01 and 2011-03-08.

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bedford, J.R., Moreno, M., Deng, Z. et al. Months-long thousand-kilometre-scale wobbling before great subduction earthquakes. Nature 580, 628–635 (2020). https://doi.org/10.1038/s41586-020-2212-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-020-2212-1

This article is cited by

Comments

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.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing