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Understanding the generation of damaging, high‐frequency ground motions during earthquakes is essential both for fundamental science and for effective hazard preparation. Various theories exist regarding the origin of high‐frequency ground motions, including the standard paradigm linked to slip heterogeneity on the rupture plane, and alternative perspectives associated with fault complexity. To assess these competing hypotheses, we measure ground motion amplitudes in different frequency bands for 3 ≤ M ≤ 5.8 earthquakes in Southern California and compare them to empirical ground motion models. We utilize a Bayesian inference technique called the Integrated Nested Laplace Approximation (INLA) to identify earthquake source regions that produce higher or lower ground motions than expected. Our analysis reveals a strong correlation between fault complexity measurements and the high‐frequency ground motion event terms identified by INLA. These findings suggest that earthquakes on complex faults (or fault networks) lead to stronger‐than‐expected ground motions at high frequencies. Plain Language Summary An important and unresolved question in earthquake science is how damaging, rapid ground shaking is generated during an earthquake. Various ideas currently exist to explain the cause of such ground motions, with the standard view attributing strong ground motion to frictional variations on the fault plane that ruptures during an earthquake. However, recent studies have also indicated that geometric complexities within fault networks may likewise influence the strong ground shaking. To help resolve this conundrum, we analyzed the ground motions produced by earthquakes in Southern California to assess the dependence of these ground motions to the complex fault networks on which the earthquakes occur. Our findings indicate that complex fault network systems have a substantial influence on how damaging earthquake ground shaking could be. These results have broad implications for our understanding of the physics of earthquakes and have important implications for earthquake hazards. Key Points We investigate the influence of fault network complexity on the high‐frequency ground motions of earthquakes in California We observe a strong correlation between fault complexity and residual ground motions at high frequencies The correlation is frequency‐dependent, with stronger correlations observed at frequencies above 2 Hz

This paper provides an overview and introduction to the development of non-ergodic ground-motion models, GMMs. It is intended for a reader who is familiar with the standard approach for developing ergodic GMMs. It starts with a brief summary of the development of ergodic GMMs and then describes different methods that are used in the development of non-ergodic GMMs with an emphasis on Gaussian process (GP) regression, as that is currently the method preferred by most researchers contributing to this special issue. Non-ergodic modeling requires the definition of locations for the source and site characterizing the systematic source and site effects; the non-ergodic domain is divided into cells for describing the systematic path effects. Modeling the cell-specific anelastic attenuation as a GP, and considerations on constraints for extrapolation of the non-ergodic GMMs are also discussed. An updated unifying notation for non-ergodic GMMs is also presented, which has been adopted by the authors of this issue.

This study proposes a new simplified Ground Motion Model (GMM) for vertical spectra by combining comprehensive datasets from the NESS and NGA-West2 databases. The proposed Artificial Neural Network (ANN) architecture-based model requires only 288 unknowns to predict spectral accelerations (Sa) at 33 distinct periods ranging from 0 to 4 s. Notably, this model inherently captures known physical phenomena with reduced variability using a minimum number of unknowns compared to the GMMs existing literature, thus offering a valuable addition to current hazard estimation frameworks. Furthermore, recognizing the necessity for physics-based simulations in vertical ground motion analysis, we introduce a physics-based broadband model for vertical spectra using ANN methodology. The proposed broadband model exhibits better robustness due to the comprehensiveness of the dataset utilized and the inclusion of source path and site characteristics at the input layer. Additionally, the model effectively captures the physical trends with minimal deviation. Further, we verified the predictive ability of the developed models through a comprehensive case study of the 2008 Iwate–Miyagi earthquake. The proposed models serve as essential tools for physics-based broadband simulations and hazard assessments in active shallow crustal regions.

This study is focused on wide-area deformation monitoring initiatives based on the differential interferometric SAR technique (DInSAR). In particular, it addresses the use of advanced DInSAR (A-DInSAR) techniques, which are based on large sets of synthetic aperture radar (SAR) and Copernicus Sentinel-1 images. Such techniques have undergone a dramatic development in the last twenty years: they are now capable to process big sets of SAR images and can be exploited to realize a wide-area A-DInSAR monitoring. The study describes several initiatives to establish wide-area ground motion services (GMS), both at county- and region-level. In the second part of the study, some of the key technical aspects related to wide-area A-DInSAR monitoring are discussed. Finally, the last part of the study is devoted to the European ground motion service (EGMS), which is part of the Copernicus land monitoring service. It represents the most important wide-area A-DInSAR deformation monitoring system ever developed. The study describes its main characteristics and its main products. The end of the production of the first EGMS baseline product is foreseen for the last quarter of 2021.

The so-called site effects caused by superficial geological layers may be responsible for strong ground motion amplification in certain configurations. We focus here on the industrialized Tricastin area, in the French Rhône valley, where a nuclear site is located. This area lies above an ancient Rhône Canyon whose lithology and geometry make it prone to site effects. This study presents preliminary measurements to investigate the local seismic amplification. We deployed three seismic stations in the area for several months: two stations were located above the canyon, the third one was located on a nearby reference rock site. The recorded seismicity was analysed using the Standard Spectral Ratio technique (SSR). The estimated amplification from weak motions reaches a value of 6 for some frequencies. These first results confirm the possibility of estimating seismic amplification using earthquakes recorded for less than one year, in this highly anthropogenic and industrialized environment, despite the local low-to-moderate level of seismicity. Noise-based SSR, that presents an obvious interest in such seismic context, shows also promising results in the area. To complement this empirical approach, we estimated the amplification using 1D wave propagation modelling. This numerical estimate is based on shear wave velocity profiles resulting from geophysical characterization campaigns. Comparison of the two approaches at low frequency, where numerical estimate is considered as the most representative, tends to suggest that edge-generated surface waves may have a strong influence in the local seismic response. This interpretation will be further investigated in the future.

A new non-ergodic ground-motion model (GMM) for effective amplitude spectral ( EAS ) values for California is presented in this study. EAS , which is defined in Goulet et al. (Effective amplitude spectrum (eas) as a metric for ground motion modeling using fourier amplitudes, 2018), is a smoothed rotation-independent Fourier amplitude spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset (Ancheta in PEER NGA-West2 database. Tech. rep., PEER, Berkeley, CA, 2013). The Bayless and Abrahamson (Bull Seismol Soc Am 109(5): 2088-2105, https://doi.org/10.1785/0120190077 , 2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (Bull Seismol Soc Am 106(6):2574-2583. https://doi.org/10.1785/0120160118 , 2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (Bull Seismol Soc Am 103(2B):1360-1372, https://doi.org/10.1785/0120120125 , 2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to 40 % smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past events.

On the 6th of February 2023, a large magnitude earthquake (Pazarcık earthquake), M w = 7.7, occurred in southeast Türkiye, which caused significant destruction in Türkiye and Syria. Relatively large magnitude aftershocks followed the main shock, and after 9 hours of the main event, another large magnitude earthquake (Elbistan earthquake) occurred, M w = 7.6, on a nearby fault. This study analyzes the near-fault seismic signals from earthquakes larger than 5.5 recorded between the main shock and the 31st of March 2023. More than 60 impulsive motions are detected in 3 earthquakes, mostly concentrated in the Pazarcık and Elbistan earthquakes. In the Pazarcık earthquake, many impulsive motions are recorded in near-fault stations with periods of up to 14 s. In contrast, in the Elbistan earthquake, impulsive motions are spatially distributed, with pulse periods of up to 11 s and at distances greater than 150 km. Pulse periods mostly correlate with the magnitude of the earthquake, but pulse probability models do not predict impulsive motions over long distances. The presence of strong impulsive motions in vertical components is also observed. For both earthquakes, peak ground velocities (PGVs) are larger than predicted by ground motion prediction equations. The observation of long-period, large amplitude signals may indicate the presence of a directivity effect for both earthquakes. In some stations, spectral periods exceed the 2018 Turkish building design codes for long periods ( ≥ 1 s).

A dataset of simulated ground motions is created for seven recorded and previously validated, along with three hypothetical earthquakes in Turkey. This dataset has potential uses in engineering practice and research by both seismological and engineering communities. The simulated ground motion dataset with extensive information on the simulations and ground motion intensity parameters for each simulated motion is presented in an open-access online repository. A two-level randomization scheme is proposed to account for the uncertainties in input parameters and source-to-site geometries. An investigation of the magnitude-distance ranges in the simulated dataset, as well as the distribution of ground motion intensity measures, showed that the created dataset fills the gaps observed in recorded ground motion datasets. Pulse-like motions in the dataset are identified, and the relationship between pulse periods and earthquake magnitude is shown to agree with other relationships in the literature which are derived from recorded ground motions. The effects of source-to-site geometry and uncertainties in the following four input parameters are investigated: magnitude (Mw), stress drop, (Δτ), time-averaged shear-wave velocity in the upper 30 m (VS30), and high-frequency attenuation parameter (κ0). The dataset is validated by investigating the variability and inter-period correlation of normalized residual spectral acceleration values (ϵ), calculated using a ground motion model (GMM). The variability of ϵ is found to be consistent with the variability of GMMs. However, inter-period correlations of ϵ are shown to be larger than predictions of empirical models based on recorded earthquakes.

On the 6th February 2023 Mw 7.8 and Mw 7.6 Kahramanmaraş Earthquake Sequence occurred at the East Anatolian Fault Zone (EAFZ) and the Sürgü-Çardak Fault Zone (SCFZ), causing significant damage to buildings and infrastructure in southeast-central Türkiye and northern Syria, and claiming the lives of > 50,000 of people. We use the strong ground motion records provided by the Disaster and Emergency Management Presidency of Türkiye (AFAD) to discuss the characteristics of response spectra of interested stations, to identify and analyze the pulse-like ground motion records in the earthquake doublet, and compare the PGA, PGV, spectral acceleration and significant duration with the relevant prediction models. It is found that pulse-like ground motions are mainly distributed on the fault zone, and the velocity pulses are characterized by short-duration, short-period, and high-amplitude. The smaller pulse period may be due to the small proportion of low-frequency content energy of pulse-like ground motions. The residuals of the empirical model increase with the increase of V S 30 , implying that the regional duration model needs to be further studied. The existing models significantly overestimates the significant duration of pulse-like ground motion records, which may be related to the directional effect of pulse-like ground motion. The existing model has well predicted the attenuation of ground motion for short periods, while the ground motion records in Türkiye attenuated faster for the larger distances (> 120 km). Due to the presence of many large-amplitude, long-period velocity pulse-like records in the near-fault, PGV and long-period response spectra of pulse-like ground motion records are underestimated by the existing model. The complex dynamics of the 2023 sequence justify further studies.

The current state of the practice in performance-based earthquake engineering relies on using ergodic ground motion models (GMMs), which assume that the ground motion variability observed in a global database is the same as the variability in ground motion at a single site-source combination. However, as empirical ground motion databases have grown, it has become clear that there are significant systematic differences, which depend on repeatable effects for a combination of sites and seismic sources in a particular region. These systematic differences do not support the ergodic assumption, which is prompting the transition from ergodic to nonergodic GMMs. In this study, we use the Ridgecrest ground motion database, which has 20,000 + ground motion recordings, to evaluate the performance of ergodic and nonergodic GMMs. The large number of ground motions in the Ridgecrest database allows us to quantify repeatable effects for a relatively small region, considering earthquakes with a range of magnitudes, which has been seldom attempted in previous efforts. In developing the nonergodic GMMs, we propose a novel approach based on computer graphics to quantify the cell-specific attenuation terms to constrain the path effects. We use the developed ergodic and nonergodic GMMs to evaluate their performance in earthquake scenarios that occurred in the Ridgecrest area by creating GMM-based maps of ground shaking (MGSs) and comparing them with actual MGSs from recorded ground motions. We use the results from MGSs to assess the assumption in nonergodic GMMs, namely that repeatable effects observed in small magnitude earthquakes are correlated with repeatable effects observed in large magnitude earthquakes. Our results show that the nonergodic GMMs provide information on the spatial variation of repeatable effects induced by complex physical processes; they have a lower aleatory variability, consistent with previous studies; they have a better performance for the considered earthquake scenarios in the Ridgecrest area; and the repeatable effects quantified in small magnitude earthquakes improve the estimation of intensity measures (IMs) at larger magnitudes.