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We propose an alternative procedure for the capture of the hard‐rock regional kappa (κ0ref). In our approach, we make use of a potential link between the well‐known κ parameter and the properties of coda waves. In our analysis, we consider near‐distance records of four crustal earthquakes of local magnitude 3.7–4.9 that occurred in four regions of France in different geological contexts: the crystalline axial chain of Pyrenees to the southwest, the large sedimentary basin to the southeast, the Alpine range to the east, and the extensional Rhine graben to the northeast. Each earthquake has been recorded at a pair of nearby soft‐ and hard‐rock station sites. The high‐frequency (16–32 Hz) spectral amplitudes of the coda window (carefully selected on the time series of the accelerograms) confirm an exponential decrease, which we quantify by κAHcoda and call “kappa of coda.” It is found that κAHcoda is independent of the soil type but shows significant regional variations. κ measurements (Anderson and Hough, 1984) over the coda window (κAHcoda) and full time series (κAH) show strong correlation at hard‐rock sites. This suggests that κAHcoda can provide a new proxy to estimate the regional hard rock κ0ref (Ktenidou et al., 2015). Theoretical analysis is also presented to relate the regional κAHcoda and coda quality factor Qc, which quantifies the average attenuation properties of the crust (both scattering and absorption). It allows interpreting κAHcoda as the time spent by the waves in the medium, weighted by its attenuation properties. This theoretical analysis also shows that the classical κ measurement should be frequency dependent; this was confirmed by the spectra of the observed records.
To evaluate the spatiotemporal variations of ground motions in northern Chile, we built a high-quality rock seismic acceleration database and an interface earthquakes catalog. Two ground-motion prediction equation (GMPE) models for subduction zones have been tested and validated for the area. They were then used as backbone models to describe the time-space variations of earthquake frequency content (Fourier and response spectra). Consistent with previous studies of large subduction earthquakes, moderate interface earthquakes in northern Chile show an increase of the high-frequency energy released with depth. A regional variability of earthquake frequency content is also observed, which may be related to a lateral segmentation of the mechanical properties of the subduction interface. Finally, interface earthquakes show a temporal evolution of their frequency content in the earthquake sequence associated with the 2014 Iquique M-w 8.1 megathrust earthquake. Surprisingly, the change does not occur with the mainshock but is associated with an 8 month slow slip preceding the megathrust. Electronic Supplement: Strong-motion database.
Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.
A transparent and data-driven global tectonic regionalization model for seismic hazard assessment
(2018)
A key concept that is common to many assumptions inherent within seismic hazard assessment is that of tectonic similarity. This recognizes that certain regions of the globe may display similar geophysical characteristics, such as in the attenuation of seismic waves, the magnitude scaling properties of seismogenic sources or the seismic coupling of the lithosphere. Previous attempts at tectonic regionalization, particularly within a seismic hazard assessment context, have often been based on expert judgements; in most of these cases, the process for delineating tectonic regions is neither reproducible nor consistent from location to location. In this work, the regionalization process is implemented in a scheme that is reproducible, comprehensible from a geophysical rationale, and revisable when new relevant data are published. A spatial classification-scheme is developed based on fuzzy logic, enabling the quantification of concepts that are approximate rather than precise. Using the proposed methodology, we obtain a transparent and data-driven global tectonic regionalization model for seismic hazard applications as well as the subjective probabilities (e.g. degree of being active/degree of being cratonic) that indicate the degree to which a site belongs in a tectonic category.
Detections of pP and sP phase arrivals (the so-called depth phases) at teleseismic distance provide one of the best ways to estimate earthquake focal depth, as the P-pP and the P-sP delays are strongly dependent on the depth. Based on a new processing workflow and using a single seismic array at teleseismic distance, we can estimate the depth of clusters of small events down to magnitude M-b 3.5. Our method provides a direct view of the relative variations of the seismicity depth from an active area. This study focuses on the application of this new methodology to study the lateral variations of the Guerrero subduction zone (Mexico) using the Eielson seismic array in Alaska (USA). After denoising the signals, 1232 M-b 3.5 + events were detected, with clear P, pP, sP and PcP arrivals. A high-resolution view of the lateral variations of the depth of the seismicity of the Guerero-Oaxaca area is thus obtained. The seismicity is shown to be mainly clustered along the interface, coherently following the geometry of the plate as constrained by the receiver-function analysis along the Meso America Subduction Experiment profile. From this study, the hypothesis of tears on the western part of Guerrero and the eastern part of Oaxaca are strongly confirmed by dramatic lateral changes in the depth of the earthquake clusters. The presence of these two tears might explain the observed lateral variations in seismicity, which is correlated with the boundaries of the slow slip events.
Accelerometric data from the well-studied valley EUROSEISTEST are used to investigate ground motion uncertainty and variability. We define a simple local ground motion prediction equation (GMPE) and investigate changes in standard deviation (σ) and its components, the between-event variability (τ) and within-event variability (φ). Improving seismological metadata significantly reduces τ (30–50%), which in turn reduces the total σ. Improving site information reduces the systematic site-to-site variability, φ S2S (20–30%), in turn reducing φ, and ultimately, σ. Our values of standard deviations are lower than global values from literature, and closer to path-specific than site-specific values. However, our data have insufficient azimuthal coverage for single-path analysis. Certain stations have higher ground-motion variability, possibly due to topography, basin edge or downgoing wave effects. Sensitivity checks show that 3 recordings per event is a sufficient data selection criterion, however, one of the dataset’s advantages is the large number of recordings per station (9–90) that yields good site term estimates. We examine uncertainty components binning our data with magnitude from 0.01 to 2 s; at smaller magnitudes, τ decreases and φ SS increases, possibly due to κ and source-site trade-offs Finally, we investigate the alternative approach of computing φ SS using existing GMPEs instead of creating an ad hoc local GMPE. This is important where data are insufficient to create one, or when site-specific PSHA is performed. We show that global GMPEs may still capture φ SS , provided that: (1) the magnitude scaling errors are accommodated by the event terms; (2) there are no distance scaling errors (use of a regionally applicable model). Site terms (φ S2S ) computed by different global GMPEs (using different site-proxies) vary significantly, especially for hard-rock sites. This indicates that GMPEs may be poorly constrained where they are sometimes most needed, i.e., for hard rock.
In this study, we analyzed 10 yrs of seismicity in central Italy from 2008 to 2017, a period witnessing more than 1400 earthquakes in the magnitude range 2.5≤Mw≤6.5. The data set includes the main sequences that have occurred in the area, including those associated with the 2009 Mw 6.3 L'Aquila earthquake and the 2016–2017 sequence (Mw 6.2 Amatrice, Mw 6.1 Visso, and Mw 6.5 Norcia earthquakes). We calibrated a local magnitude scale, investigating the impact of changing the reference distance at which the nonparametric attenuation is tied to the zero‐magnitude attenuation function for southern California. We also developed an attenuation model to compute the radiated seismic energy (Es) from the time integral of the squared ground‐motion velocity. Seismic moment (M0) and stress drop (Δσ) were estimated for each earthquake by fitting a ω‐square model to the source spectra obtained by applying a nonparametric spectral inversion. The Δσ‐values vary over three orders of magnitude from about 0.1 to 10 MPa, the larger values associated with the mainshocks. The Δσ‐values describe a lognormal distribution with mean and standard deviation equal to log(Δσ)=(−0.25±0.45) (i.e., the mean Δσ is 0.57 MPa, with a 95% confidence interval from 0.08 to 4.79 MPa). The Δσ variability introduces a spread in the distribution of seismic energy versus moment, with differences in energy up two orders of magnitudes for earthquakes with the same moment. The variability in the high‐frequency spectral levels is captured by the local magnitude (ML), which scales with radiated energy as ML=(−1.59+0.52logEs) for logEs≤10.26 and ML=(−1.38+0.50logEs) otherwise. As the peak ground velocity increases with increasing Δσ, local and energy magnitudes perform better than moment magnitude as predictors for the shaking potential. The availability of different magnitude scales and source parameters for a large earthquake population will help characterize the between‐event ground‐motion variability in central Italy.
With increasing amount of strong motion data, Ground Motion Prediction Equation (GMPE) developers are able to quantify empirical site amplification functions (delta S2S(s)) from GMPE residuals, for use in site-specific Probabilistic Seismic Hazard Assessment. In this study, we first derive a GMPE for 5% damped Pseudo Spectral Acceleration (g) of Active Shallow Crustal earthquakes in Japan with 3.4 <= M-w <= 7.3 and 0 <= R-JB <= 600km. Using k-mean spectral clustering technique, we then classify our estimated delta S2S(s)(T = 0.01 - 2s) of 588 wellcharacterized sites, into 8 site clusters with distinct mean site amplification functions, and within-cluster site-tosite variability similar to 50% smaller than the overall dataset variability (phi(S2S)). Following an evaluation of existing schemes, we propose a revised data-driven site classification characterized by kernel density distributions of V-s30, V-s10, H-800, and predominant period (T-G) of the site clusters.
On April 29, 2017 at 0:56 UTC (2:56 local time), an M (W) = 2.8 earthquake struck the metropolitan area between Leipzig and Halle, Germany, near the small town of Markranstadt. The earthquake was felt within 50 km from the epicenter and reached a local intensity of I (0) = IV. Already in 2015 and only 15 km northwest of the epicenter, a M (W) = 3.2 earthquake struck the area with a similar large felt radius and I (0) = IV. More than 1.1 million people live in the region, and the unusual occurrence of the two earthquakes led to public attention, because the tectonic activity is unclear and induced earthquakes have occurred in neighboring regions. Historical earthquakes south of Leipzig had estimated magnitudes up to M (W) ae 5 and coincide with NW-SE striking crustal basement faults. We use different seismological methods to analyze the two recent earthquakes and discuss them in the context of the known tectonic structures and historical seismicity. Novel stochastic full waveform simulation and inversion approaches are adapted for the application to weak, local earthquakes, to analyze mechanisms and ground motions and their relation to observed intensities. We find NW-SE striking normal faulting mechanisms for both earthquakes and centroid depths of 26 and 29 km. The earthquakes are located where faults with large vertical offsets of several hundred meters and Hercynian strike have developed since the Mesozoic. We use a stochastic full waveform simulation to explain the local peak ground velocities and calibrate the method to simulate intensities. Since the area is densely populated and has sensitive infrastructure, we simulate scenarios assuming that a 12-km long fault segment between the two recent earthquakes is ruptured and study the impact of rupture parameters on ground motions and expected damage.
Ground‐motion prediction equations (GMPEs) are calibrated to predict the intensity of ground shaking at any given location, based on earthquake magnitude, source‐to‐site distance, local soil amplifications, and other parameters. GMPEs are generally assumed to be independent of time; however, evidence is increasing that large earthquakes modify the shallow soil conditions and those of the fault zone for months or years. These changes may affect the intensity of shaking and result in time‐dependent effects that can potentially be resolved by analyzing between‐event residuals (residuals between observed and predicted ground motion for individual earthquakes averaged over all stations). Here, we analyze a data set of about 65,000 recordings for about 1400 earthquakes in the moment magnitude range 2.5–6.5 that occurred in central Italy from 2008 to 2017 to capture the temporal variability of the ground shaking at high frequency. We first compute between‐event residuals for each earthquake in the Fourier domain with respect to a GMPE developed ad hoc for the analyzed data set. The between‐events show large changes after the occurrence of mainshocks such as the 2009 Mw 6.3 L'Aquila, the 2016 Mw 6.2 Amatrice, and Mw 6.5 Norcia earthquakes. Within the time span of a few months after the mainshocks, the between‐event contribution to the ground shaking varies by a factor 7. In particular, we find a large drop in the between‐events in the aftermath of the L'Aquila earthquake, followed by a slow positive trend that leads to a recovery interrupted by a new drop at the beginning of 2014. We also quantify the frequency‐dependent correlation between the Brune stress drop Δσ and the between‐events. We find that the temporal changes of Δσ resemble those of the between‐event residuals; in particular, during the period when the between‐events show the positive trend, the average logarithm of Δσ increases with an annual rate of 0.19 (i.e., the amplification factor for Δσ is 1.56 per year). Breakpoint analysis located a change in the linear trend coefficients of Δσ versus time in February 2014, although no large earthquakes occurred at that time. Finally, the temporal variability of Δσ mirrors the relative seismic‐velocity variations observed in previous studies for the same area and period, suggesting that both crack healing along the main fault system and healing of microcracks distributed at shallow depths throughout the surrounding region might be necessary to explain the wider observations of postearthquake recovery.