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Several regularly recurring moderate-size earthquakes motivated dense instrumentation of the Parkfield section of the San Andreas fault, providing an invaluable near-fault observatory. We present a seismo-geodetic dynamic inversion of the 2004 Parkfield earthquake, which illuminates the interlinked complexity of faulting across time scales. Using fast-velocity-weakening rate-and-state friction, we jointly model 3D coseismic dynamic rupture and the 90-day evolution of postseismic slip. We utilize a parallel tempering Markov chain Monte Carlo approach to solve this non-linear high-dimensional inverse problem, constraining spatially varying prestress and fault friction parameters by 30 strong motion and 12 GPS stations. From visiting >2 million models, we discern complex coseismic rupture dynamics that transition from a strongly radiating pulse-like phase to a mildly radiating crack-like phase. Both coseismic phases are separated by a shallow strength barrier that nearly arrests rupture and leads to a gap in the afterslip. Coseismic rupture termination involves distinct arrest mechanisms that imprint on afterslip kinematics. A backward propagating afterslip front may drive delayed aftershock activity above the hypocenter. Analysis of the 10,500 best-fitting models uncovers local correlations between prestress levels and the reference friction coefficient, alongside an anticorrelation between prestress and rate-state parameters b−a. We find that a complex, fault-local interplay of dynamic parameters determines the nucleation, propagation, and arrest of both, co- and postseismic faulting. This study demonstrates the potential of inverse physics-based modeling to reveal novel insights and detailed characterizations of well-recorded earthquakes.

Dynamic rupture simulations generate synthetic waveforms that account for nonlinear source and path complexity. Here, we analyze millions of spatially dense waveforms from 3D dynamic rupture simulations in a novel way to illuminate the spectral fingerprints of earthquake physics. We define a Brune-type equivalent near-field corner frequency (fc) to analyze the spatial variability of ground-motion spectra and unravel their link to source complexity. We first investigate a simple 3D strike-slip setup, including an asperity and a barrier, and illustrate basic relations between source properties and fc variations. Next, we analyze >13,000,000 synthetic near-field strong-motion waveforms generated in three high-resolution dynamic rupture simulations of real earthquakes, the 2019 Mw 7.1 Ridgecrest mainshock, the Mw 6.4 Searles Valley foreshock, and the 1992 Mw 7.3 Landers earthquake. All scenarios consider 3D fault geometries, topography, off-fault plasticity, viscoelastic attenuation, and 3D velocity structure and resolve frequencies up to 1–2 Hz. Our analysis reveals pronounced and localized patterns of elevated fc, specifically in the vertical components. We validate such fc variability with observed near-fault spectra. Using isochrone analysis, we identify the complex dynamic mechanisms that explain rays of elevated fc and cause unexpectedly impulsive, localized, vertical ground motions. Although the high vertical frequencies are also associated with path effects, rupture directivity, and coalescence of multiple rupture fronts, we show that they are dominantly caused by rake-rotated surface-breaking rupture fronts that decelerate due to fault heterogeneities or geometric complexity. Our findings highlight the potential of spatially dense ground-motion observations to further our understanding of earthquake physics directly from near-field data. Observed near-field fc variability may inform on directivity, surface rupture, and slip segmentation. Physics-based models can identify “what to look for,” for example, in the potentially vast amount of near-field large array or distributed acoustic sensing data.