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The dataset contains source parameters of acoustic emission (AE) events recorded during triaxial friction (stick-slip) experiments performed on the Westerly Granite sample WgN05. In addition we provide raw waveform data of AE events recorded in triggered mode with a network of 16 AE sensors. Basic seismic catalog associated with the stick-slip experiment contains origin time, hypocentral location in local Cartesian coordinate system of the sample (with associated uncertainties), and AE-derived magnitude. In addition, for a subset of AEs we provide full moment tensors. This catalog include information on fault parameters (strike, dip and rake of the two nodal planes), percentage of isotropic, compensated linear vector dipole and double-couple components of the full moment tensor, P, T, B axes orientations in the coordinate system of the sample, uncertainty assessment, as well as the six independent moment tensor components. Finally, we provide a time series of axial stress values as presented in the Kwiatek et al. (2023) as well as the coordinates of the AE sensors. The catalog and parametric data is supplemented with the raw waveform recordings stored in HDF5 format from 16 acoustic emission sensors placed on the surface of the sample.
The Geldingadalir 2021 eruption in Iceland started on 19 March and ended on 18 September. It featured nearly 9000 lava fountain episodes of minute to day duration that were all accompanied by seismic tremor. We measured the duration, repose time, tremor amplitude and shape using seismometers from the University of Potsdam. We publish the corresponding catalogs that contain information about these episodes. Periodically, aerial surveys were conducted by the University of Iceland using unoccupied aerial systems (UAS). These surveys lead to digital surface models (DSM), orthomosaics, and 3D models. These products were used to supplement the seismic observations.
This data repository contains electrical and seismic tremor measurements, thermal infrared imagery, atmospheric conditions and information on plume heights that were recorded and collected during the 2021 Tajogaite eruption on La Palma, Canary Islands, Spain. The 2021 Tajogaite eruption lasted from 19 September until 13 December 2021. The "data description" file provides more detailed information on each dataset and the way the data is formatted. The electrical data was recorded using a Biral Thunderstorm Detector BTD-200. This sensor was installed at two consecutive locations: BTD1 (28.635°N, 17.876389°W) recorded from 11-26 October 2021 and BTD2 (28.602365°N, 17.880475°W) recorded from 27 October 2021 until the end of the eruption. The volcanic tremor measurements were recorded at seismic station PLPI (28.5722°N, 17.8654°W), which was operated by the Instituto Volcanológico de Canarias. Here we provide the seismic tremor amplitudes within the Very Long Period (0.4-0.6 Hz) and the Long Period (1-5 Hz) frequency bands between 10 September and 20 December 2021. Thermal infrared videography of the explosive volcanic activity was done using an InfraTec HD thermal infrared (TIR) video camera. This camera was installed in El Paso (28.649361°N, 17.882279°W) and recorded almost continuously between 3-8 November 2021. Here we provide individual thermal infrared frames. Atmospheric conditions were obtained from weather balloon measurements at Güímar (station nr. 60018) on Tenerife, which were provided by the University of Wyoming, Department of Atmospheric Science (http://weather.uwyo.edu/). In addition, atmospheric data was collected from ground-based weather stations at El Paso and Roque de los Muchachos, which were operated by the State Meteorological Agency (AEMET) of Spain on La Palma. Information on the volcanic plume heights was obtained from both the Toulouse Volcanic Ash Advisory Center (https://vaac.meteo.fr/volcanoes/la-palma/) as well as the Plan de Emergencias Volcánicas de Canarias.
This data publication contains vertical seismic profiling (VSP) data collected at the Groß Schönebeck site, Germany, from February 15-18, 2017. Energy excitation was performed with vibroseis sources. Data was acquired in the two 4.3 km deep wells E GrSk 3/90 and Gt GrSk4/05 using hybrid wireline fiber-optic sensor cables and distributed acoustic sensing (DAS) technology. The survey design and data acquisition, the overall characteristics of the acquired data, as well as the data processing and evaluation for a zero-offset source position are described in the paper of Henninges et al. (2021) published in Solid Earth. The data for several source positions presented in this paper is contained here, mostly in the form of full waveform data stored in seg-y format. A detailed description of the individual data sets is given in the attached data description document.
We perform a teleseismic P-wave travel-time tomography to examine the geometry and structure of subducted lithosphere in the upper mantle beneath the Alpine orogen. The tomography is based on waveforms recorded at over 600 temporary and permanent broadband stations of the dense AlpArray Seismic Network deployed by 24 different European institutions in the greater Alpine region, reaching from the Massif Central to the Pannonian Basin and from the Po plain to the river Main. Teleseismic travel times and travel-time residuals of direct teleseismic P-waves from 331 teleseismic events of magnitude 5.5 and higher recorded between 2015 and 2019 by the AlpArray Seismic Network are extracted from the recorded waveforms using a combination of automatic picking, beamforming and cross-correlation. The resulting database contains over 162.000 highly accurate absolute P-wave travel times and travel-time residuals. For tomographic inversion, we define a model domain encompassing the entire Alpine region down to a depth of 600 km. Predictions of travel times are computed in a hybrid way applying a fast Tau-P method outside the model domain and continuing the wavefronts into the model domain using a fast marching method. We iteratively invert demeaned travel-time residuals for P-wave velocities in the model domain using a regular discretization with an average lateral spacing of about 25 km and a vertical spacing of 15 km. The inversion is regularized towards an initial model constructed from a 3D a priori model of the crust and uppermost mantle and a 1D standard earth model beneath. The resulting model provides a detailed image of slab configuration beneath the Alpine and Apenninic orogens. Major features are a partly overturned Adriatic slab beneath the Apennines reaching down to 400 km depth still attached in its northern part to the crust but exhibiting detachment towards the southeast. A fast anomaly beneath the western Alps indicates a short western Alpine slab whose easternmost end is located at about 100 km depth beneath the Penninic front. Further to the east and following the arcuate shape of the western Periadriatic Fault System, a deep-reaching coherent fast anomaly with complex internal stucture generally dipping to the SE down to about 400 km suggests a slab of European origin limited to the east by the Giudicarie fault in the upper 200 km but extending beyond this fault at greater depths. In its eastern part it is detached from overlying lithosphere. Further to the east, well-separated in the upper 200 km from the slab beneath central Alps but merging with it below, another deep-reaching, nearly vertically dipping high-velocity anomaly suggests the existence of a slab beneath the Eastern Alps of presumably the same origin which is completely detached from the orogenic root. The data are fully described in Paffrath et al. (2021). The model is provided as tabular data with six columns (1) Longitude (deg), (2) Latitude (deg), (3) Depth (km), (4) vp (km/s), (5) dVp (%), (6) Resolution.
The 'Earthquake Network’ (EQN) is an app which detects earthquakes by creating an ad-hoc network of smartphones' accelerometer sensors and provides early warnings for earthquakes via the same smartphone app. Detections are not due to individual smartphone measurements but due to near-simultaneous trigger signals from clusters of smartphones running the app. Therefore detections are normally located in the closest populated regions to an earthquake's epicentre. In order to investigate the mechanisms of EQN's earthquake detection system, we searched for seismic accelerometer stations with publically available data that were close to the EQN detection locations (rather than close to the epicentre). This confirmed that EQN's detections followed strong shaking motions but that detections could follow both P-phase or S-phase rather than consistantly being sensitive to only one particular phase. It also showed that detections generally occurred between 0 - 5 seconds after the peak ground acceleration measured by the seismic station. Analysis was conducted on 550 detections made by the EQN system between 2017-12-15 and 2020-01-31 in Chile, Italy and the USA. Strong motion accelerometer data was collected from seismic stations via the FDSN protocol. The data was calibrated, detrended and a small time shift was applied to correct for differences in distances from the epicentre between the EQN detection and the strong motion seismic station. Calibrated waveform data was obtained for 410 EQN detections. Plots were made for each event and an analysis was carried out on the dataset to compare EQN detection times with the peak ground acceleration measured by the nearest seismic station. The dataset consists of a zip-file containing a table of results and some summary graphs derived from it as well as a set of 410 graphs of strong motion files that are presented as image files (png-files). The graphs show the waveform data for a seismic station within 20 km of each EQN detection.
The 'Earthquake Network’ (EQN) is an app which detects earthquakes by creating an ad-hoc network of smartphones' accelerometer sensors and provides early warnings for earthquakes via the same smartphone app. Detections are not due to individual smartphone measurements but due to near-simultaneous trigger signals from clusters of smartphones running the app. Therefore detections are normally located in the closest populated regions to an earthquake's epicentre. These datasets compare sets of detections with the earthquake parameters published by seismic institutes in order to analyse the performance of the EQN network. One dataset contains 550 detections made by EQN between 2017-12-15 and 2020-01-31 in Chile, USA and Italy. Wherever possible, each detection was associated with an earthquake from the parameter catalogue of each country's seismic institute (CSN for Chile, USGS for USA and INGV for Italy). Associations were carried out automatically but also checked manually. The other dataset contains 134 detections from around the world that could be associated to earthquakes with magnitude ≥ M5 or magnitude ≥ M4.5 in Italy and the USA. There are 68 detections that are common to the first dataset. All detections were associated to parameters from the the USGS earthquake parameter catalogue for consistency.
This dataset is supplementary material to "Detection limits and near-field ground motions of fast and slow earthquakes" by G. Kwiatek and Y. Ben-Zion published in Journal of Geophysical Research - Solid Earth.The dataset contains spatial variations of ground motions (peak ground velocities) expected from various rupture scenarios of magnitude M6 earthquake that occurs in Southern California area, United States. The performed calculations of ground motions are based on synthetic velocity seismograms calculated with Discrete Wavenumber Method assuming crustal seismic velocities and attenuation properties in Southern California. The selected rupture scenarios include slow- and fast propagating ruptures (varying rupture velocity), crack- and pulse-type rupture type (varying rise time) and different rupture directivities (circular-to-unilateral, circular-to-bilateral ruptures are considered). The dataset allows to reproduce Figures 7-8 and S3-S4 from the original manuscript.
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