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ABSTRACT Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics-based ground-motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics-informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high-resolution, frequency-dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point-source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal-component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced-order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite-source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high-resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time-to-solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics-based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high-performance computing and reduced-order modeling techniques for PSHA. 

SUMMARY Elastodynamic Green’s functions are an essential ingredient in seismology as they form the connection between direct observations of seismic waves and the earthquake source. They are also fundamental to various seismological techniques including physics-based ground motion prediction and kinematic or dynamic source inversions. In regions with established 3-D models of the Earth’s elastic structure, such as southern California, 3-D Green’s functions can be computed using numerical simulations of seismic wave propagation. However, such simulations are computationally expensive, which poses challenges for real-time ground motion prediction and uncertainty quantification in source inversions. In this study, we address these challenges by using a reduced-order model (ROM) approach that enables the rapid evaluation of approximate Green’s functions. The ROM technique developed approximates three-component time-dependent surface velocity wavefields obtained from numerical simulations of seismic wave propagation. We apply our ROM approach to a 50 km $$\times$$ 40 km area in greater Los Angeles accounting for topography, site effects, 3-D subsurface velocity structure, and viscoelastic attenuation. The ROM constructed for this region enables rapid computation ($$\approx 0.0001$$ CPU hr) of complete, high-resolution (500 m spacing), 0.5 Hz surface velocity wavefields that are accurate for a shortest wavelength of 1.0 km for a single elementary moment tensor source. Using leave-one-out cross validation, we measure the accuracy of our Green’s functions for the CVM-S velocity model in both the time domain and frequency domain. Averaged across all sources, receivers, and time steps, the error in the rapid seismograms is less than 0.01 cm s−1. We demonstrate that the ROM can accurately and rapidly reproduce simulated seismograms for generalized moment tensor sources in our region, as well as kinematic sources by using a finite fault model of the 1987 $$M_\mathrm{ W}$$ 5.9 Whittier Narrows earthquake as an example. We envision that rapid, accurate Green’s functions from reduced-order modelling for complex 3-D seismic wave propagation simulations will be useful for constructing real-time ground motion synthetics and source inversions with high spatial resolution. 

Abstract The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The Mw 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral Mw 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data-driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems. 

Key Points Physics‐based simulations are useful for seismic hazard assessment and ground motion prediction but are computationally expensive Our reduced‐order model accurately predicts simulated peak ground velocities (PGVs) for scenarios, including 3D wavefield and topographic effects The reduced‐order model produces physics‐based ground motion maps in milliseconds for variable source depths and focal mechanisms 

The destructive 2023 moment magnitude ( M w ) 7.8-7.7 earthquake doublet ruptured multiple segments of the East Anatolian Fault system in Turkey. We integrate multi-scale seismic and space-geodetic observations with multi-fault kinematic inversions and dynamic rupture modeling to unravel the events’ complex rupture history and stress-mediated fault interactions. Our analysis reveals three sub-shear slip episodes during the initial M w 7.8 earthquake with delayed rupture initiation to the southwest. The M w 7.7 event occurred 9 hours later with larger slip and supershear rupture on its western branch. Mechanically consistent dynamic models accounting for fault interactions can explain the unexpected rupture paths, and require a heterogeneous background stress. Our results highlight the importance of combining near- and far-field observations with data-driven and physics-based models for seismic hazard assessment. 

Abstract We measure pseudospectral and peak ground motions from 44 intermediate‐depth Mw≥4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 Mw 7.1 earthquake near Anchorage, to identify regional amplification features (0.1–5  s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and we compute bias, between‐, and within‐event terms through a linear mixed‐effects regression. Between‐event residuals are analyzed to assess the relative source characteristics of the Cook Inlet earthquakes and suggest a difference in the scaling of the source with depth, relative to global observations. The within‐event residuals are analyzed to investigate regional amplification, and various spatial patterns manifest, including correlations of amplification with depth of the Cook Inlet basin and varying amplifications east and west of the center of the basin. Three earthquake clusters are analyzed separately and indicate spatial amplification patterns that depend on source location and exhibit variations in the depth scaling of long‐period basin amplification. The observations inform future seismic hazard modeling efforts in the Cook Inlet region. More broadly, they suggest a greater complexity of basin and regional amplification than is currently used in seismic hazard analyses.