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:

Dynamics, interactions and delays of the 2019 Ridgecrest rupture sequence

Abstract

The observational difficulties and the complexity of earthquake physics have rendered seismic hazard assessment largely empirical. Despite increasingly high-quality geodetic, seismic and field observations, data-driven earthquake imaging yields stark differences and physics-based models explaining all observed dynamic complexities are elusive. Here we present data-assimilated three-dimensional dynamic rupture models of California’s biggest earthquakes in more than 20 years: the moment magnitude (Mw) 6.4 Searles Valley and Mw 7.1 Ridgecrest sequence, which ruptured multiple segments of a non-vertical quasi-orthogonal conjugate fault system1. Our models use supercomputing to find the link between the two earthquakes. We explain strong-motion, teleseismic, field mapping, high-rate global positioning system and space geodetic datasets with earthquake physics. We find that regional structure, ambient long- and short-term stress, and dynamic and static fault system interactions driven by overpressurized fluids and low dynamic friction are conjointly crucial to understand the dynamics and delays of the sequence. We demonstrate that a joint physics-based and data-driven approach can be used to determine the mechanics of complex fault systems and earthquake sequences when reconciling dense earthquake recordings, three-dimensional regional structure and stress models. We foresee that physics-based interpretation of big observational datasets will have a transformative impact on future geohazard mitigation.

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: Observational constraints for 3D dynamic rupture modelling of the Ridgecrest earthquake sequence.
Fig. 2: Dynamic rupture scenario of the Searles Valley foreshock and comparison with observations.
Fig. 3: Dynamic rupture scenario of the Ridgecrest mainshock and comparison with observations.
Fig. 4: Coseismic and postseismic stress changes.
Fig. 5: Off-fault surface deformation and shallow slip deficit.

Similar content being viewed by others

Data availability

All data required to reproduce the earthquake sequence scenarios can be downloaded from https://zenodo.org/record/6842773. We provide a detailed README file summarizing the data and data formats provided. Our 3D fault model is available at https://skfb.ly/oDVGw. The static GPS data related to the coseismic rupture of both the foreshock and mainshock are available from UNAVCO (https://www.unavco.org/highlights/2019/ridgecrest.html). The continuous GPS dataset35 is available at https://zenodo.org/record/3366342. The Instaseis Green’s function database that we use to compute teleseismic synthetics is hosted by IRIS at https://ds.iris.edu/ds/products/syngine/Source data are provided with this paper.

Code availability

All dynamic rupture simulations were performed using SeisSol (www.seissol.org), an open-source software freely available to download from https://github.com/SeisSol/SeisSol/. The used SeisSol code branch and commit are archived at https://zenodo.org/record/7642533. The SeisSol Ridgecrest sequence branch is also available on GitHub (https://github.com/SeisSol/SeisSol/tree/2019_Ridgecrest_sequence). Instructions for downloading, installing and running the code are available in the SeisSol documentation at https://seissol.readthedocs.io/. Downloading and compiling instructions are at https://seissol.readthedocs.io/en/latest/compiling-seissol.html. Instructions for setting up and running simulations are at https://seissol.readthedocs.io/en/latest/configuration.html. Quickstart containerized installations and introductory materials are provided in the docker container and jupyter notebooks at https://github.com/SeisSol/Training. Example problems and model configuration files are provided at https://github.com/SeisSol/Examples, many of which reproduce the SCEC 3D Dynamic Rupture benchmark problems described at https://strike.scec.org/cvws/benchmark_descriptions.html. We use the software SKUA-GOCAD (https://www.aspentech.com/en/resources/brochure/aspen-skua) as the modelling environment to produce all 3D fault models and the open-source software ParaView (https://www.paraview.org/) for visualization.

References

  1. Ross, Z. E. et al. Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence. Science 366, 346–351 (2019).

    CAS  PubMed  ADS  Google Scholar 

  2. Hauksson, E., Jones, L. M., Hutton, K. & Eberhart-Phillips, D. The 1992 Landers earthquake sequence: seismological observations. J. Geophys. Res. Solid Earth 98, 19835–19858 (1993).

    Google Scholar 

  3. Hamling, I. J. et al. Complex multifault rupture during the 2016 Mw 7.8 Kaikoura earthquake, New Zealand. Science 356, eaam7194 (2017).

    PubMed  Google Scholar 

  4. DuRoss, C. B. et al. Surface displacement distributions for the July 2019 Ridgecrest, California, earthquake ruptures. Bull. Seismol. Soc. Am. 110, 1400–1418 (2020).

    Google Scholar 

  5. Zeng, Y. & Shen, Z. A fault-based model for crustal deformation, fault slip rates, and off-fault strain rate in California. Bull. Seismol. Soc. Am. 106, 766–784 (2016).

    Google Scholar 

  6. Fukuyama, E. Dynamic faulting on a conjugate fault system detected by near-fault tilt measurements. Earth Planet. Space 67, 38 (2015).

    ADS  Google Scholar 

  7. Kato, A., Sakai, S., Matsumoto, S. & Iio, Y. Conjugate faulting and structural complexity on the young fault system associated with the 2000 Tottori earthquake. Commun. Earth. Environ. 2, 13 (2021).

    ADS  Google Scholar 

  8. Chen, K. et al. Cascading and pulse-like ruptures during the 2019 Ridgecrest earthquakes in the Eastern California Shear Zone. Nat. Commun. 11, 22 (2020).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  9. Shi, Q. & Wei, S. Highly heterogeneous pore fluid pressure enabled rupture of orthogonal faults during the 2019 Ridgecrest Mw7.0 earthquake. Geophys. Res. Lett. 47, e2020GL089827 (2020).

    ADS  Google Scholar 

  10. Magen, Y., Ziv, A., Inbal, A., Baer, G. & Hollingsworth, J. Fault rerupture during the July 2019 Ridgecrest earthquake pair from joint slip inversion of InSAR, optical imagery, and GPS. Bull. Seismol. Soc. Am. 110, 1627–1643 (2020).

    Google Scholar 

  11. Jin, Z. & Fialko, Y. Finite slip models of the 2019 Ridgecrest earthquake sequence constrained by space geodetic data and aftershock locations. Bull. Seismol. Soc. Am. 110, 1660–1679 (2020).

    Google Scholar 

  12. Qiu, Q., Barbot, S., Wang, T. & Wei, S. Slip complementarity and triggering between the foreshock, mainshock, and afterslip of the 2019 Ridgecrest rupture sequence. Bull. Seismol. Soc. Am. 110, 1701–1715 (2020).

    Google Scholar 

  13. Shelly, D. R. A high resolution seismic catalog for the initial 2019 Ridgecrest earthquake sequence: foreshocks, aftershocks, and faulting complexity. Seismol. Res. Lett. 91, 1971–1978 (2020).

    Google Scholar 

  14. Cheng, Y. & Ben-Zion, Y. Variations of earthquake properties before, during, and after the 2019 M7.1 Ridgecrest, CA, earthquake. Geophys. Res. Lett. 47, e2020GL089650 (2020).

    ADS  Google Scholar 

  15. Wang, K., Dreger, D. S., Tinti, E., Bürgmann, R. & Taira, T. Rupture process of the 2019 Ridgecrest, California Mw 6.4 foreshock and Mw 7.1 earthquake constrained by seismic and geodetic data. Bull. Seismol. Soc. Am. 110, 1603–1626 (2020).

    Google Scholar 

  16. Lachenbruch, A. H. & Sass, J. Heat flow and energetics of the San Andreas Fault zone. J. Geophys. Res. Solid Earth 85, 6185–6222 (1980).

    Google Scholar 

  17. Ulrich, T., Gabriel, A.-A., Ampuero, J.-P. & Xu, W. Dynamic viability of the 2016 Mw 7.8 Kaikoura earthquake cascade on weak crustal faults. Nat. Commun. 10, 1213 (2019).

    PubMed  PubMed Central  ADS  Google Scholar 

  18. Li, B. & Ghosh, A. in The Chile-2015 (Illapel) Earthquake and Tsunami (eds Braitenberg, C. & Rabinovich, A. B.) 33–43 (Springer, 2017).

  19. Hallo, M. & Gallovič, F. Bayesian self-adapting fault slip inversion with Green’s functions uncertainty and application on the 2016 Mw7.1 Kumamoto earthquake. J. Geophys. Res. Solid Earth 125, e2019JB018703 (2020).

    ADS  Google Scholar 

  20. Carena, S. & Suppe, J. Three-dimensional imaging of active structures using earthquake aftershocks: the Northridge thrust, California. J. Geol. Soc. 24, 887–904 (2002).

    Google Scholar 

  21. Liang, C., Ampuero, J.-P. & Pino Muñoz, D. Deep ductile shear zone facilitates near-orthogonal strike-slip faulting in a thin brittle lithosphere. Geophys. Res. Lett. 48, e2020GL090744 (2021).

    ADS  Google Scholar 

  22. Lee, E.-J. et al. Full-3-D tomography for crustal structure in Southern California based on the scattering-integral and the adjoint-wavefield methods. J. Geophys. Res. Solid Earth 119, 6421–6451 (2014).

    ADS  Google Scholar 

  23. Yang, W. & Hauksson, E. The tectonic crustal stress field and style of faulting along the Pacific North America Plate boundary in Southern California. Geophys. J. Int. 194, 100–117 (2013).

    ADS  Google Scholar 

  24. Verdecchia, A. & Carena, S. Coulomb stress evolution in a diffuse plate boundary: 1400 years of earthquakes in eastern California and western Nevada, USA. Tectonics 35, 1793–1811 (2016).

    ADS  Google Scholar 

  25. Copley, A. The strength of earthquake-generating faults. J. Geol. Soc. 175, 1–12 (2017).

    Google Scholar 

  26. Di Toro, G. et al. Fault lubrication during earthquakes. Nature 471, 494–498 (2011).

    PubMed  ADS  Google Scholar 

  27. Southern California Earthquake Data Center (SCEDC, 2013); https://scedc.caltech.edu.

  28. Goldberg, D. E. et al. Complex rupture of an immature fault zone: a simultaneous kinematic model of the 2019 Ridgecrest, CA earthquakes. Geophys. Res. Lett. 47, e2019GL086382 (2020).

    ADS  Google Scholar 

  29. Liu, M., Zhang, M., Zhu, W., Ellsworth, W. L. & Li, H. Rapid characterization of the July 2019 Ridgecrest, California, earthquake sequence from raw seismic data using machine-learning phase picker. Geophys. Res. Lett. 47, e2019GL086189 (2020).

    ADS  Google Scholar 

  30. Liu, C., Lay, T., Brodsky, E. E., Dascher-Cousineau, K. & Xiong, X. Coseismic rupture process of the large 2019 Ridgecrest earthquakes from joint inversion of geodetic and seismological observations. Geophys. Res. Lett. 46, 11820–11829 (2019).

    ADS  Google Scholar 

  31. Lozos, J. C. & Harris, R. A. Dynamic rupture simulations of the M6.4 and M7.1 July 2019 Ridgecrest, California, earthquakes. Geophys. Res. Lett. 47, e2019GL086020 (2020).

    ADS  Google Scholar 

  32. Cortez, J. T. et al. On the rupture propagation of the 2019 M6.4 Searles Valley, California, earthquake, and the lack of immediate triggering of the M7.1 Ridgecrest earthquake. Geophys. Res. Lett. 48, e2020GL090659 (2021).

    ADS  Google Scholar 

  33. Milliner, C. & Donnellan, A. Using daily observations from Planet Labs satellite imagery to separate the surface deformation between the 4 July Mw 6.4 foreshock and 5 July Mw 7.1 mainshock during the 2019 Ridgecrest earthquake sequence. Seismol. Res. Lett. 91, 1986–1997 (2020).

    Google Scholar 

  34. Gabriel, A.-A., Ampuero, J.-P., Dalguer, L. A. & Mai, P. M. The transition of dynamic rupture styles in elastic media under velocity-weakening friction. J. Geophys. Res. 117, B09311 (2012).

    ADS  Google Scholar 

  35. Melgar, D. et al. Real-time high-rate GNSS displacements: performance demonstration during the 2019 Ridgecrest, California, earthquakes. Seismol. Res. Lett. 91, 1943–1951 (2019).

    Google Scholar 

  36. Baltzopoulos, G., Luzi, L. & Iervolino, I. Analysis of near-source ground motion from the 2019 Ridgecrest earthquake sequence. Bull. Seismol. Soc. Am. 110, 1495–1505 (2020).

    Google Scholar 

  37. Toda, S. & Stein, R. S. Long- and short-term stress interaction of the 2019 Ridgecrest sequence and Coulomb-based earthquake forecasts. Bull. Seismol. Soc. Am. 110, 1765–1780 (2020).

    Google Scholar 

  38. Garagash, D. I. Fracture mechanics of rate-and-state faults and fluid injection induced slip. Phil. Trans. R. Soc. A. 379, 20200129 (2021).

    MathSciNet  PubMed  ADS  Google Scholar 

  39. Yue, H. et al. The 2019 Ridgecrest, California earthquake sequence: evolution of seismic and aseismic slip on an orthogonal fault system. Earth Planet Sci. Lett. 570, 117066 (2021).

    CAS  Google Scholar 

  40. Premus, J., Gallovič, F. & Ampuero, J.-P. Bridging time scales of faulting: from coseismic to postseismic slip of the Mw 6.0 2014 South Napa, California earthquake. Sci. Adv. 8, eabq2536 (2022).

    PubMed  PubMed Central  ADS  Google Scholar 

  41. Ponti, D. J. et al. Documentation of surface fault rupture and ground-deformation features produced by the 4 and 5 July 2019 Mw 6.4 and Mw 7.1 Ridgecrest earthquake sequence. Seismol. Res. Lett. 91, 2942–2959 (2020).

    Google Scholar 

  42. Rodriguez Padilla, A. M. et al. Near-field high-resolution maps of the Ridgecrest earthquakes from aerial imagery. Seismol. Res. Lett. 93, 494–499 (2021).

    Google Scholar 

  43. Taufiqurrahman, T., Gabriel, A.-A., Ulrich, T., Valentova, L. & Gallovič, F. Broadband dynamic rupture modeling with fractal fault roughness, frictional heterogeneity, viscoelasticity and topography: the 2016 Mw 6.2 Amatrice, Italy earthquake. Geophys. Res. Lett. 31, e2022GL098872 (2022).

  44. Antoine, S. L. et al. Diffuse deformation and surface faulting distribution from submetric image correlation along the 2019 Ridgecrest, California, ruptures. Bull. Seismol. Soc. Am. 111, 2275–2302 (2021).

    Google Scholar 

  45. Dumbser, M. & Käser, M. An arbitrary high-order discontinuous Galerkin method for elastic waves on unstructured meshes—II. The three-dimensional isotropic case. Geophys. J. Int. 167, 319–336 (2006).

    ADS  Google Scholar 

  46. Breuer, A. et al. Sustained petascale performance of seismic simulations with SeisSol on SuperMUC. In Supercomputing. ISC 2014. Lecture Notes in Computer Science Vol. 8488, 1–18 (Springer, 2014).

  47. Heinecke, A. et al. Petascale high order dynamic rupture earthquake simulations on heterogeneous supercomputers. In International Conference for High Performance Computing, Networking, Storage and Analysis, SC 3–14 (IEEE, 2014).

  48. Rettenberger, S., Meister, O., Bader, M. & Gabriel, A.-A. Asagi: a parallel server for adaptive geoinformation. In Proc. Exascale applications and Software Conference 2016, 2:1–2:9 (ACM, 2016).

  49. Uphoff, C. et al. Extreme scale multi-physics simulations of the tsunamigenic 2004 Sumatra megathrust earthquake. In Proc. International Conference for High Performance Computing, networking, Storage and Analysis, SC 2017 (2017).

  50. Krenz, L. et al. 3D acoustic-elastic coupling with gravity: the dynamics of the 2018 Palu, Sulawesi earthquake and tsunami. In Proc. International Conference for High Performance Computing, Networking, Storage and Analysis, SC’21 1–17 (ACM, N2021).

  51. Pelties, C., Gabriel, A.-A. & Ampuero, J.-P. Verification of an ADER-DG method for complex dynamic rupture problems. Geosci. Model Dev. 7, 847–866 (2014).

    ADS  Google Scholar 

  52. Harris, R. A. et al. Verifying a computational method for predicting extreme ground motion. Seismol. Res. Lett. 82, 638–644 (2011).

    ADS  Google Scholar 

  53. Harris, R. A. et al. A suite of exercises for verifying dynamic earthquake rupture codes. Seismol. Res. Lett. 89, 1146–1162 (2018).

    Google Scholar 

  54. Valkaniotis, S. Subpixel optical correlation co-seismic offsets for the Mw 6.4 and Mw 7.1 Ridgecrest, California earthquakes, from Copernicus Sentinel 2 data. Zenodo https://doi.org/10.5281/zenodo.3275073 (2019).

  55. Planet Data Application Program Interface. in Space for Life On Earth (Planet, 2019); https://www.planet.com/markets/education-and-research/.

  56. Wang, X. & Zhan, Z. Seismotectonics and fault geometries of the 2019 Ridgecrest sequence: insight from aftershock moment tensor catalog using 3-D Green’s functions. J. Geophys. Res. Solid Earth 124, e2020JB019577 (2020).

    Google Scholar 

  57. Plesch, A., Shaw, J. H., Ross, Z. E. & Hauksson, E. Detailed 3D fault representations for the 2019 Ridgecrest, California, earthquake sequence. Bull. Seismol. Soc. Am. 110, 1818–1831 (2020).

    Google Scholar 

  58. Xu, X., Sandwell, D. T. & Smith-Konter, B. Coseismic displacements and surface fractures from Sentinel-1 InSAR: 2019 Ridgecrest earthquakes. Seismol. Res. Lett. 91, 1979–1985 (2020).

    Google Scholar 

  59. Dunham, E. M., Belanger, D., Cong, L. & Kozdon, J. E. Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, part 1: planar faults. Bull. Seismol. Soc. Am. 101, 2296–2307 (2011).

    Google Scholar 

  60. Heaton, T. H. Evidence for and implications of self-healing pulses of slip in earthquake rupture. Phys. Earth Planet. Inter. 64, 1–20 (1990).

    ADS  Google Scholar 

  61. Nielsen, S. & Madariaga, R. On the self-healing fracture mode. Bull. Seismol. Soc. Am. 93, 2375–2388 (2003).

    Google Scholar 

  62. Dieterich, J. H. Modeling of rock friction: 1. Experimental results and constitutive equations. J. Geophys. Res. Solid Earth 84, 2161–2168 (1979).

    Google Scholar 

  63. Ruina, A. Slip instability and state variable friction laws. J. Geophys. Res. Solid Earth 88, 10359–10370 (1983).

    Google Scholar 

  64. Blanpied, M. L., Lockner, D. A. & Byerlee, J. D. Fault stability inferred from granite sliding experiments at hydrothermal conditions. Geophys. Res. Lett. 18, 609–612 (1991).

    ADS  Google Scholar 

  65. Wei, M., Kaneko, Y., Liu, Y. & McGuire, J. J. Episodic fault creep events in California controlled by shallow frictional heterogeneity. Nat. Geosci. 6, 566–570 (2013).

    CAS  ADS  Google Scholar 

  66. Kaneko, Y., Lapusta, N. & Ampuero, J.-P. Spectral element modeling of spontaneous earthquake rupture on rate and state faults: effect of velocity-strengthening friction at shallow depths. J. Geophys. Res. Solid Earth 113, B09317 (2008).

    ADS  Google Scholar 

  67. Tinti, E. et al. Constraining families of dynamic models using geological, geodetic and strong ground motion data: the Mw 6.5, October 30th, 2016, Norcia earthquake, Italy. Earth Planet Sci. Lett. 576, 117237 (2021).

    CAS  Google Scholar 

  68. Anderson, E. M. The dynamics of faulting. Trans. Edinb. Geol. Soc 8, 387–402 (1905).

    Google Scholar 

  69. Aochi, H. & Madariaga, R. The 1999 Izmit, Turkey, earthquake: nonplanar fault structure, dynamic rupture process, and strong ground motion. Bull. Seismol. Soc. Am. 93, 1249–1266 (2003).

    Google Scholar 

  70. Suppe, J. Fluid overpressures and strength of the sedimentary upper crust. J. Struct. Geol. 69, 481–492 (2014).

    ADS  Google Scholar 

  71. Madden, E. H., Ulrich, T. & Gabriel, A.-A. The state of pore fluid pressure and 3-D megathrust earthquake dynamics. J. Geophys. Res. Solid Earth 127, e2021JB023382 (2022).

    ADS  Google Scholar 

  72. Hauksson, E. et al. Preliminary report on the 1995 Ridgecrest earthquake sequence in Eastern California. Seismol. Res. Lett. 66, 54–60 (1995).

    Google Scholar 

  73. Verdecchia, A. & Carena, S. One hundred and fifty years of Coulomb stress history along the California–Nevada border, USA: Coulomb stress history CA–NV border. Tectonics 34, 213–231 (2015).

    ADS  Google Scholar 

  74. Rubin, A. M. & Ampuero, J.-P. Earthquake nucleation on (aging) rate and state faults. J. Geophys. Res. Solid Earth 110, B11312 (2005).

    ADS  Google Scholar 

  75. Lapusta, N. & Liu, Y. Three-dimensional boundary integral modeling of spontaneous earthquake sequences and aseismic slip. J. Geophys. Res. Solid Earth 114, B09303 (2009).

  76. Jiang, J. & Lapusta, N. Deeper penetration of large earthquakes on seismically quiescent faults. Science 352, 1293–1297 (2016).

    MathSciNet  CAS  PubMed  MATH  ADS  Google Scholar 

  77. Luo, B., Duan, B. & Liu, D. 3D finite-element modeling of dynamic rupture and aseismic slip over earthquake cycles on geometrically complex faults. Bull. Seismol. Soc. Am. 110, 2619–2637 (2020).

    Google Scholar 

  78. Meng, Q. & Duan, B. Dynamic modeling of interactions between shallow slow-slip events and subduction earthquakes. Seismol. Soc. Am. 94, 206–216 (2023).

    Google Scholar 

  79. Jiang, J. et al. Community-driven code comparisons for three-dimensional dynamic modeling of sequences of earthquakes and aseismic slip. J. Geophys. Res. Solid Earth 127, e2021JB023519 (2022).

    ADS  Google Scholar 

  80. Uphoff, C., May, D. A. & Gabriel, A.-A. A discontinuous Galerkin method for sequences of earthquakes and aseismic slip on multiple faults using unstructured curvilinear grids. Geophys. J. Int. 233, 586–626 (2022).

  81. Andrews, D. Rupture models with dynamically determined breakdown displacement. Bull. Seismol. Soc. Am. 94, 769–775 (2004).

    Google Scholar 

  82. Bizzarri, A. How to promote earthquake ruptures: different nucleation strategies in a dynamic model with slip-weakening friction. Bull. Seismol. Soc. Am. 100, 923–940 (2010).

    Google Scholar 

  83. Hu, F., Huang, H. & Chen, X. Effect of the time-weakening friction law during the nucleation process. Earthq. Sci. 30, 91–96 (2017).

    ADS  Google Scholar 

  84. Harris, R. A. et al. A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek–Hayward–Calaveras fault system, California. J. Geophys. Res. Solid Earth 126, e2020JB020577 (2021).

    ADS  Google Scholar 

  85. Galis, M. et al. On the initiation of sustained slip-weakening ruptures by localized stresses. Geophys. J. Int. 200, 890–909 (2015).

    ADS  Google Scholar 

  86. Freund, L. B. Dynamic Fracture Mechanics (Cambridge Univ. Press, 1998).

  87. Hardebeck, J. L. & Michael, A. J. Damped regional-scale stress inversions: methodology and examples for Southern California and the Coalinga aftershock sequence. J. Geophys. Res. Solid Earth 111, B11310 (2006).

    ADS  Google Scholar 

  88. Farr, T. G. et al. The Shuttle Radar Topography Mission. Rev. Geophys. 45, RG2004 (2007).

    ADS  Google Scholar 

  89. Wollherr, S., Gabriel, A.-A. & Uphoff, C. Off-fault plasticity in three-dimensional dynamic rupture simulations using a modal discontinuous Galerkin method on unstructured meshes: implementation, verification and application. Geophys. J. Int. 214, 1556–1584 (2018).

    ADS  Google Scholar 

  90. Uphoff, C. & Bader, M. Generating high performance matrix kernels for earthquake simulations with viscoelastic attenuation. In 2016 International Conference on High Performance Computing & Simulation (HPCS) 908–916 (IEEE, 2016).

  91. Day, S. M. & Bradley, C. R. Memory-efficient simulation of anelastic wave propagation. Bull. Seismol. Soc. Am. 91, 520–531 (2001).

    Google Scholar 

  92. Graves, R. W. et al. Broadband simulations for Mw 7.8 southern San Andreas earthquakes: ground motion sensitivity to rupture speed. Geophys. Res. Lett. 35, L22302 (2008).

    ADS  Google Scholar 

  93. Roten, D., Olsen, K. B., Day, S. M., Cui, Y. & Fäh, D. Expected seismic shaking in los angeles reduced by San Andreas Fault zone plasticity. Geophys. Res. Lett. 41, 2769–2777 (2014).

    ADS  Google Scholar 

  94. Andrews, D. J. Rupture dynamics with energy loss outside the slip zone. J. Geophys. Res. Solid Earth 110, B01307 (2005).

    ADS  Google Scholar 

  95. Ma, S. A physical model for widespread near-surface and fault zone damage induced by earthquakes. Geochem. Geophys. Geosyst. 9, Q11009 (2008).

    ADS  Google Scholar 

  96. Gabriel, A.-A., Ampuero, J.-P., Dalguer, L. A. & Mai, P. M. Source properties of dynamic rupture pulses with off-fault plasticity. J. Geophys. Res. Solid Earth 118, 4117–4126 (2013).

    ADS  Google Scholar 

  97. Ulrich, T., Gabriel, A.-A. & Madden, E. H. Stress, rigidity and sediment strength control megathrust earthquake and tsunami dynamics. Nat. Geosci. 15, 67–73 (2022).

    CAS  ADS  Google Scholar 

  98. Xie, Y., Bao, H. & Meng, L. Source imaging with a multi-array local back-projection and its application to the 2019 Mw 6.4 and Mw 7.1 Ridgecrest earthquakes. J. Geophys. Res. Solid Earth 126, e2020JB021396 (2021).

    ADS  Google Scholar 

  99. Kennett, B. L. N. & Engdahl, E. R. Traveltimes for global earthquake location and phase identification. Geophys. J. Int. 105, 429–465 (1991).

    ADS  Google Scholar 

  100. Ghosh, A., Vidale, J. E. & Creager, K. C. Tremor asperities in the transition zone control evolution of slow earthquakes. J. Geophys. Res. Solid Earth 117, B10301 (2012).

    ADS  Google Scholar 

  101. Li, B. et al. Rupture heterogeneity and directivity effects in back-projection analysis. J. Geophys. Res. Solid Earth 127, e2021JB022663 (2022).

    ADS  Google Scholar 

  102. Yang, J., Zhu, H. & Lumley, D. Time-lapse imaging of coseismic ruptures for the 2019 Ridgecrest earthquakes using multiazimuth backprojection with regional seismic data and a 3-D crustal velocity model. Geophys. Res. Lett. 47, e2020GL087181 (2020).

    ADS  Google Scholar 

  103. Yin, J. & Denolle, M. A. Relating teleseismic backprojection images to earthquake kinematics. Geophys. J. Int. 217, 729–747 (2019).

    ADS  Google Scholar 

  104. Tinti, E., Fukuyama, E., Piatanesi, A. & Cocco, M. A kinematic source-time function compatible with earthquake dynamics. Bull. Seismol. Soc. Am. 95, 1211–1223 (2005).

    Google Scholar 

  105. Pasyanos, M. E., Dreger, D. S. & Romanowicz, B. Toward real-time estimation of regional moment tensors. Bull. Seismol. Soc. Am. 86, 1255–1269 (1996).

    Google Scholar 

  106. Cotton, F. & Coutant, O. Dynamic stress variations due to shear faults in a plane-layered medium. Geophys. J. Int. 128, 676–688 (1997).

    ADS  Google Scholar 

  107. Hallo, M. & Gallovič, F. Fast and cheap approximation of Green function uncertainty for waveform-based earthquake source inversions. Geophys. J. Int. 207, 1012–1029 (2016).

    ADS  Google Scholar 

  108. Sambridge, M. A parallel tempering algorithm for probabilistic sampling and multimodal optimization. Geophys. J. Int. 196, 357–374 (2013).

    ADS  Google Scholar 

  109. Albuquerque Seismological Laboratory/USGS. Global Seismograph Network (GSN - IRIS/USGS) [data set]. International Federation of Digital Seismograph Networks https://doi.org/10.7914/SN/IU (2014).

  110. van Driel, M., Krischer, L., Stähler, S., Hosseini, K. & Nissen-Meyer, T. Instaseis: instant global seismograms based on a broadband waveform database. Solid Earth 6, 701–717 (2015).

    ADS  Google Scholar 

  111. Dziewonski, A. M. & Anderson, D. L. Preliminary reference Earth model. Phys. Earth Plan. Int. 25, 297–356 (1981).

  112. Mégnin, C. & Romanowicz, B. The three-dimensional shear velocity structure of the mantle from the inversion of body, surface and higher-mode waveforms. Geophys. J. Int. 143, 709–728 (2000).

  113. Krischer, L. et al. ObsPy: a bridge for seismology into the scientific Python ecosystem. Comput. Sci. Discov. 8, 014003 (2015).

    Google Scholar 

Download references

Acknowledgements

We thank M. Bader, L. Krenz, S. Wolf, R. Dorozhinskii and the group of hardware-aware algorithms and software for high-performance computing at TUM for decade-long collaboration; N. Schliwa, J. Biemiller, C. Nicholson and S. A. Wirp for discussions; and S. Antoine for sharing surface offset data. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme (TEAR grant number 852992) and Horizon Europe (ChEESE-2P grant number 101093038, DT-GEO grant number 101058129 and Geo-INQUIRE grant number 101058518), the National Science Foundation (grant number EAR-2121666), the German Research Foundation (DFG projects GA 2465/2-1 and GA 2465/3-1) and the Southern California Earthquake Center (SCEC award 21112). We acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de), in project pr63qo.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, formal analysis, software, visualization and writing: T.T., A.-A.G., D.L., T.U., B.L., S.C., A.V. and F.G. Funding acquisition and resources: A.-A.G..

Corresponding author

Correspondence to Alice-Agnes Gabriel.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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

Supplementary information

Supplementary Information

This file contains Supplementary Tables 1–4, Figs. 1–22 and legends for Supplementary Videos 1–8.

Peer Review File

Supplementary Video 1

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Preferred foreshock dynamic rupture scenario.

Supplementary Video 2

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Preferred mainshock dynamic rupture scenario.

Supplementary Video 3

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative mainshock dynamic rupture scenario not accounting for the dynamic and static foreshock stress changes.

Supplementary Video 4

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative mainshock dynamic rupture scenario not accounting for the dynamic and static foreshock stress changes and in addition omitting the effects of the long-term ΔCFS.

Supplementary Video 5

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative foreshock dynamic rupture scenario omitting the long-term ΔCFS.

Supplementary Video 6

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative mainshock dynamic rupture scenario omitting the long-term ΔCFS.

Supplementary Video 7

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative foreshock dynamic rupture scenario loaded with an alternative community ambient stress model.

Supplementary Video 8

Evolution of absolute slip rate (m s−1) across the fault network from four perspectives. Alternative mainshock dynamic rupture scenario loaded with an alternative community ambient stress model.

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taufiqurrahman, T., Gabriel, AA., Li, D. et al. Dynamics, interactions and delays of the 2019 Ridgecrest rupture sequence. Nature 618, 308–315 (2023). https://doi.org/10.1038/s41586-023-05985-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-023-05985-x

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