ALBERT

Description: This article describes the Engineering Strong-Motion Database (ESM), developed in the framework of the European project Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation (NERA, see Data and Resources ). ESM is specifically designed to provide end users only with quality-checked, uniformly processed strong-motion data and relevant parameters and has done so since 1969 in the Euro-Mediterranean region. The database was designed for a large variety of stakeholders (expert seismologists, earthquake engineers, students, and professionals) with a user-friendly and straightforward web interface. Users can access earthquake and station information and download waveforms of events with magnitude≥4.0 (unprocessed and processed acceleration, velocity, and displacement, and acceleration and displacement response spectra at 5% damping). Specific tools are also available to users to process strong-motion data and select ground-motion suites for code-based seismic structural analyses.

Description: 〈span〉〈div〉ABSTRACT〈/div〉The task of downloading comprehensive datasets of event‐based seismic waveforms has been made easier through the development of standardized webservices but is still highly nontrivial because the likelihood of temporary network failures or subtle data errors naturally increases when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging because the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user‐defined output. Here, we present stream2segment, a highly customizable Python 2+3 package helping the user in the entire workflow of downloading, inspecting, and processing event‐based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages, and an integrated processing subroutine requiring a configuration file and a single Python function to produce user‐defined output. Stream2segment can also produce diagnostic maps or user‐defined plots, which, unlike existing tools, do not require external software dependencies and are not static images but instead are interactive browser‐based applications ideally suited for data inspection or annotation tasks and subsequent training of classifiers in foreseen supervised machine‐learning applications.Stream2segment has already been used as a data quality tool for datasets within the European Integrated Data Archive and to create a weak‐motion database (in the form of a so‐called flat file) for the stable continental region of Europe in the context of the European Ground Shaking Intensity Model service, in turn an important building block for seismic hazard studies.〈/span〉

Description: 〈p〉In many cases, it takes several minutes after an earthquake to publish online a seismic location with confidence. Via monitoring for specific types of increased website, app, or Twitter usage, crowdsourced detection of seismic activity can be used to "seed" the search in the seismic data for an earthquake and reduce the risk of false detections, thereby accelerating the publication of locations for felt earthquakes. We demonstrate that this low-cost approach can work at the global scale to produce reliable and rapid results. The system was retroactively tested on a set of real crowdsourced detections of earthquakes made during 2016 and 2017, with 50% of successful locations found within 103 s, 76 s faster than GEOFON and 271 s faster than the European-Mediterranean Seismological Centre’s publication times, and 90% of successful locations found within 54 km of the final accepted epicenter.〈/p〉

Description: 〈span〉〈div〉SUMMARY〈/div〉We derive a harmonized local magnitude scale across Europe using data disseminated by network operators through the European Integrated Data Archive (EIDA). We first calibrate simultaneously a set of non-parametric attenuation functions regionalized by considering six different regions covering central and southern Europe, anchoring the models to the Richter’s scale at 17 km. Uncertainties on the attenuation coefficients, station corrections and magnitude values are evaluated through bootstrap analysis. The obtained attenuation functions show significant differences among the regions, up to 0.4 m.u. at 400 km, being the attenuation of the Wood–Anderson amplitude stronger for regions in the Mediterranean area. The non-parametric attenuation functions capture the changes in the rate of attenuation with distance due to the effects of later arrivals generated by crustal heterogeneity. A second calibration is performed to derive a parametric attenuation model. We consider a piece-wise linear function to describe the attenuation with the logarithm of distance, introducing two breakpoint distances at 10 and 60 km. For distances above 10 km, we also consider the anelastic attenuation term. We apply a mixed effect regression with network-dependent random effects on the anelastic coefficients. The parametric analysis confirms the stronger attenuation for networks operating in the Mediterranean area, such as the Italian and Greek networks, with respect to networks located in continental Europe. The network-dependent random effects allow us to quantify the between-network variability for different networks operating in the same region or country. The observed between-network variability is within ±0.2 m.u., smaller than the variability among the six regions.〈/span〉

Description: In this note, we derive an attenuation function for computing magnitude values equivalent to M w using strong-motion data. We analyze 106 earthquakes of the 1 April 2014 M w  8.1 Pisagua sequence, which occurred along the 1877 seismic gap in northern Chile. We considered both foreshocks and aftershocks with moment magnitude available from moment tensor inversion in the GEOFON bulletin and recorded by the Integrated Plate boundary Observatory Chile strong-motion network. The maximum peak displacement measured over the double integrated traces is used to construct the magnitude scale, following a nonparametric approach. A bootstrap analysis is performed to assess the uncertainty of the model parameters, and cross-validation tests are performed to proof the suitability of the derived model in predicting the M w in the analyzed area, with an uncertainty of 0.2 magnitude units. The derived scale is applied to an early aftershock, which occurred about 155 s after the mainshock, initially missed in bulletins published by rapid global earthquake monitoring agencies (e.g., National Earthquake Information Center and GEOFON), because its phase arrivals at regional/teleseismic distances mix with those of the mainshock and its later arrivals. The estimated magnitude equivalent to M w is 6.6±0.3, which rank this event as the second largest aftershock of the sequence, after the M w  7.6 earthquake that occurred on 3 April 2014.

Description: 〈span〉〈div〉Summary〈/div〉We derive a harmonized local magnitude scale across Europe using data disseminated by network operators through the European Integrated Data Archive (EIDA). We first calibrate simultaneously a set of non-parametric attenuation functions regionalized by considering six different regions covering central and southern Europe, anchoring the models to the Richter’s scale at 17 km. Uncertainties on the attenuation coefficients, station corrections and magnitude values are evaluated through bootstrap analysis. The obtained attenuation functions show significant differences among the regions, up to 0.4 m.u. at 400 km, being the attenuation of the Wood-Anderson amplitude stronger for regions in the Mediterranean area. The non-parametric attenuation functions capture the changes in the rate of attenuation with distance due to the effects of later arrivals generated by crustal heterogeneity. A second calibration is performed to derive a parametric attenuation model. We consider a piece-wise linear function to describe the attenuation with the logarithm of distance, introducing two breakpoint distances at 10 and 60 km. For distances above 10km, we also consider the anelastic attenuation term. We apply a mixed effect regression with network-dependent random effects on the anelastic coefficients. The parametric analysis confirms the stronger attenuation for networks operating in the Mediterranean area, such as the Italian and Greek networks, with respect to networks located in continental Europe. The network-dependent random effects allow us to quantify the between-network variability for different networks operating in the same region or country. The observed between-network variability is within ±0.2 m.u., smaller than the variability among the six regions.〈/span〉

Description: 〈span〉〈div〉ABSTRACT〈/div〉The task of downloading comprehensive datasets of event‐based seismic waveforms has been made easier through the development of standardized webservices but is still highly nontrivial because the likelihood of temporary network failures or subtle data errors naturally increases when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging because the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user‐defined output. Here, we present stream2segment, a highly customizable Python 2+3 package helping the user in the entire workflow of downloading, inspecting, and processing event‐based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages, and an integrated processing subroutine requiring a configuration file and a single Python function to produce user‐defined output. Stream2segment can also produce diagnostic maps or user‐defined plots, which, unlike existing tools, do not require external software dependencies and are not static images but instead are interactive browser‐based applications ideally suited for data inspection or annotation tasks and subsequent training of classifiers in foreseen supervised machine‐learning applications.Stream2segment has already been used as a data quality tool for datasets within the European Integrated Data Archive and to create a weak‐motion database (in the form of a so‐called flat file) for the stable continental region of Europe in the context of the European Ground Shaking Intensity Model service, in turn an important building block for seismic hazard studies.〈/span〉

Description: We infer seismic azimuthal anisotropy from ambient-noise-derived Rayleigh waves in the wider Vienna Basin region. Cross-correlations of the ambient seismic field are computed for 1953 station pairs and periods from 5 to 25? s to measure the directional dependence of interstation Rayleigh-wave group velocities. We perform the analysis for each period on the whole data set, as well as in overlapping 2°-cells to regionalize the measurements, to study expected effects from isotropic structure, and isotropic–anisotropic trade-offs. To extract azimuthal anisotropy that relates to the anisotropic structure of the Earth, we analyse the group velocity residuals after isotropic inversion. The periods discussed in this study (5–20? s) are sensitive to crustal structure, and they allow us to gain insight into two distinct mechanisms that result in fast orientations. At shallow crustal depths, fast orientations in the Eastern Alps are S/N to SSW/NNE, roughly normal to the Alps. This effect is most likely due to the formation of cracks aligned with the present-day stress-field. At greater depths, fast orientations rotate towards NE, almost parallel to the major fault systems that accommodated the lateral extrusion of blocks in the Miocene. This is coherent with the alignment of crystal grains during crustal deformation occurring along the fault systems and the lateral extrusion of the central part of the Eastern Alps.

Description: The town of Potenza (Southern Italy) is one of the test sites for preparing ground-motion scenarios within the framework of the Italian Dipartimento Protezione Civile-Istituto Nazionale di Geofisica e Vulcanologia (DPC-INGV) 2004-2006 projects. An area in the neighboring village of Tito was selected to evaluate different techniques for estimating site effects involving a 40-m-deep instrumented borehole. This two-sensor vertical array records teleseismic, regional, and local seismicity. Close to the borehole, three seismological microarrays (utilizing short-period sensors and digitizers with a high dynamic range) were installed in May 2005 to record seismic noise. Differing acquisition geometries allowed the checking of any dependency in the derived dispersion curves based on the adopted analysis method (extended spatial autocorrelation [ESAC] and frequency wave-number [F-K]). In general, the ESAC method appears to provide more reliable results in the low-frequency range. Furthermore, the soil-velocity profiles obtained from the microarray data were compared with the S-wave velocity profile derived from down-hole measurements. A good agreement was observed in the depth range well constrained by the data. Finally, empirical site responses were compared with those calculated numerically from the S-wave velocity profiles obtained from the microarray data. Although this comparison did not resolve a preference among the derived models, it showed the importance of downgoing waves in modifying the site response at the Tito site.

Description: Using three different short-period electromagnetic sensors with resonance frequencies of 1 Hz (Mark L4C-3D), 2 Hz (Mark L-22D), and 4.5 Hz (I/O SM-6), coupled with three digital acquisition system, the portable data acquisition system (PDAS) Teledyne Geotech, the refraction technology (REFTEK) 72A, and the Earth Data Logger PR6-24 (EDL), the effect of the seismic instruments on the horizontal-to-vertical spectral ratio (H/V) using seismic noise for frequencies less than 1 Hz has been evaluated. For all possible sensors-acquisition system pairs, the background seismic signal and instrumental self-noise power spectral densities have been calculated and compared. The results obtained when coupling the short-period sensors with different acquisition systems show that the performance of the considered instruments at frequencies 〈1 Hz strongly depends upon the sensor-acquisition system combination and the gain used, with the best performance obtained for sensors with the lowest resonance frequency. For all acquisition systems, it was possible to retrieve correctly the H/V peak down to 0.1-0.2 Hz by using a high gain and a 1-Hz sensor. In contrast, biased H/V spectral ratios were retrieved when low-gain values were considered. Particular care is required when using 4.5-Hz sensors, because they may not even allow the fundamental resonance frequency peak to be reproduced.