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.
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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.
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.
Ross, Z. E. et al. Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence. Science 366, 346–351 (2019).
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).
Hamling, I. J. et al. Complex multifault rupture during the 2016 Mw 7.8 Kaikoura earthquake, New Zealand. Science 356, eaam7194 (2017).
DuRoss, C. B. et al. Surface displacement distributions for the July 2019 Ridgecrest, California, earthquake ruptures. Bull. Seismol. Soc. Am. 110, 1400–1418 (2020).
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).
Fukuyama, E. Dynamic faulting on a conjugate fault system detected by near-fault tilt measurements. Earth Planet. Space 67, 38 (2015).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Lachenbruch, A. H. & Sass, J. Heat flow and energetics of the San Andreas Fault zone. J. Geophys. Res. Solid Earth 85, 6185–6222 (1980).
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).
Li, B. & Ghosh, A. in The Chile-2015 (Illapel) Earthquake and Tsunami (eds Braitenberg, C. & Rabinovich, A. B.) 33–43 (Springer, 2017).
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).
Carena, S. & Suppe, J. Three-dimensional imaging of active structures using earthquake aftershocks: the Northridge thrust, California. J. Geol. Soc. 24, 887–904 (2002).
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).
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).
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).
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).
Copley, A. The strength of earthquake-generating faults. J. Geol. Soc. 175, 1–12 (2017).
Di Toro, G. et al. Fault lubrication during earthquakes. Nature 471, 494–498 (2011).
Southern California Earthquake Data Center (SCEDC, 2013); https://scedc.caltech.edu.
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Garagash, D. I. Fracture mechanics of rate-and-state faults and fluid injection induced slip. Phil. Trans. R. Soc. A. 379, 20200129 (2021).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Harris, R. A. et al. Verifying a computational method for predicting extreme ground motion. Seismol. Res. Lett. 82, 638–644 (2011).
Harris, R. A. et al. A suite of exercises for verifying dynamic earthquake rupture codes. Seismol. Res. Lett. 89, 1146–1162 (2018).
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).
Planet Data Application Program Interface. in Space for Life On Earth (Planet, 2019); https://www.planet.com/markets/education-and-research/.
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).
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).
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).
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).
Heaton, T. H. Evidence for and implications of self-healing pulses of slip in earthquake rupture. Phys. Earth Planet. Inter. 64, 1–20 (1990).
Nielsen, S. & Madariaga, R. On the self-healing fracture mode. Bull. Seismol. Soc. Am. 93, 2375–2388 (2003).
Dieterich, J. H. Modeling of rock friction: 1. Experimental results and constitutive equations. J. Geophys. Res. Solid Earth 84, 2161–2168 (1979).
Ruina, A. Slip instability and state variable friction laws. J. Geophys. Res. Solid Earth 88, 10359–10370 (1983).
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).
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).
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).
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).
Anderson, E. M. The dynamics of faulting. Trans. Edinb. Geol. Soc 8, 387–402 (1905).
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).
Suppe, J. Fluid overpressures and strength of the sedimentary upper crust. J. Struct. Geol. 69, 481–492 (2014).
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).
Hauksson, E. et al. Preliminary report on the 1995 Ridgecrest earthquake sequence in Eastern California. Seismol. Res. Lett. 66, 54–60 (1995).
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).
Rubin, A. M. & Ampuero, J.-P. Earthquake nucleation on (aging) rate and state faults. J. Geophys. Res. Solid Earth 110, B11312 (2005).
Lapusta, N. & Liu, Y. Three-dimensional boundary integral modeling of spontaneous earthquake sequences and aseismic slip. J. Geophys. Res. Solid Earth 114, B09303 (2009).
Jiang, J. & Lapusta, N. Deeper penetration of large earthquakes on seismically quiescent faults. Science 352, 1293–1297 (2016).
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).
Meng, Q. & Duan, B. Dynamic modeling of interactions between shallow slow-slip events and subduction earthquakes. Seismol. Soc. Am. 94, 206–216 (2023).
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).
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).
Andrews, D. Rupture models with dynamically determined breakdown displacement. Bull. Seismol. Soc. Am. 94, 769–775 (2004).
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).
Hu, F., Huang, H. & Chen, X. Effect of the time-weakening friction law during the nucleation process. Earthq. Sci. 30, 91–96 (2017).
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).
Galis, M. et al. On the initiation of sustained slip-weakening ruptures by localized stresses. Geophys. J. Int. 200, 890–909 (2015).
Freund, L. B. Dynamic Fracture Mechanics (Cambridge Univ. Press, 1998).
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).
Farr, T. G. et al. The Shuttle Radar Topography Mission. Rev. Geophys. 45, RG2004 (2007).
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).
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).
Day, S. M. & Bradley, C. R. Memory-efficient simulation of anelastic wave propagation. Bull. Seismol. Soc. Am. 91, 520–531 (2001).
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).
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).
Andrews, D. J. Rupture dynamics with energy loss outside the slip zone. J. Geophys. Res. Solid Earth 110, B01307 (2005).
Ma, S. A physical model for widespread near-surface and fault zone damage induced by earthquakes. Geochem. Geophys. Geosyst. 9, Q11009 (2008).
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).
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).
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).
Kennett, B. L. N. & Engdahl, E. R. Traveltimes for global earthquake location and phase identification. Geophys. J. Int. 105, 429–465 (1991).
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).
Li, B. et al. Rupture heterogeneity and directivity effects in back-projection analysis. J. Geophys. Res. Solid Earth 127, e2021JB022663 (2022).
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).
Yin, J. & Denolle, M. A. Relating teleseismic backprojection images to earthquake kinematics. Geophys. J. Int. 217, 729–747 (2019).
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).
Pasyanos, M. E., Dreger, D. S. & Romanowicz, B. Toward real-time estimation of regional moment tensors. Bull. Seismol. Soc. Am. 86, 1255–1269 (1996).
Cotton, F. & Coutant, O. Dynamic stress variations due to shear faults in a plane-layered medium. Geophys. J. Int. 128, 676–688 (1997).
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).
Sambridge, M. A parallel tempering algorithm for probabilistic sampling and multimodal optimization. Geophys. J. Int. 196, 357–374 (2013).
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).
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).
Dziewonski, A. M. & Anderson, D. L. Preliminary reference Earth model. Phys. Earth Plan. Int. 25, 297–356 (1981).
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).
Krischer, L. et al. ObsPy: a bridge for seismology into the scientific Python ecosystem. Comput. Sci. Discov. 8, 014003 (2015).
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.
The authors declare no competing interests.
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This file contains Supplementary Tables 1–4, Figs. 1–22 and legends for Supplementary Videos 1–8.
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.
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Taufiqurrahman, T., Gabriel, AA., Li, D. et al. Dynamics, interactions and delays of the 2019 Ridgecrest rupture sequence. Nature (2023). https://doi.org/10.1038/s41586-023-05985-x
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