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During the last decades, the availability of Synthetic Aperture Radar (SAR) satellite missions, such as the ERS-1/2 and ENVISAT ones operating at C-band who have worked since 1992 to 2011, as well as the X-band COSMOSkyMed and TerraSAR-X constellations, up to the brand new Sentinel-1 mission, have strongly contributed to SAR data diffusion and popularity in the generation of different studies at different scales and in different research fields. One of the most popular SAR technique is the one referred to as Differential SAR Interferometry (DInSAR), which allows measuring with centimeter accuracy the Earth's surface deformation entity related to both natural and man-made hazards. Nowadays, with the increasing of SAR data availability provided by Sentinel-1 constellation of Copernicus European Program, which is composed by two twin satellites operating in C-band since 2014 and 2016, with a repeat pass of 6 days and with a global (i.e. worldwide) data acquisition policy, the SAR EO scenario is becoming more and more operational, thus mainly providing support for natural hazards monitoring. This allows, in theory, and disposing of sufficient computing power, the EO community to monitor, for instance, the deformation of every volcano or to obtain co-seismic displacement maps in a short time frame and anywhere in the world. Accordingly, in this work, we present a fully automatic and fast processing service for the generation of co-seismic displacement maps by using Sentinel-1 data. The implemented system is completely unsupervised and is triggered by the all significant (i.e. larger than a defined magnitude) seismic event registered by the online catalog as those provided by the United States Geological Survey (USGS) and the National Institute of Geophysics and Volcanology of Italy (INGV). The service has been specifically designed to operate for Civil Protection purposes. The generated DInSAR measurements are made available to the geoscience community through the EPOS Research Infrastructure and they will contribute to the creation of a global database of co-seismic displacement maps. Finally, it is worth noting that the developed system relies on widely common IT methods and protocols and is not specifically tied to a defined computing architecture, thus implying its portability, in view also of the European Commission Data and Information Access Services (DIAS) where satellite data (mainly Sentinel) and processing facilities are co-located to reduce the data transfer time during their processing.

This dataset compiles SEM images, modelled isopach map and topographic profiles, and data of radiocarbon ages, parameters of Tephra2 and AshCalc codes of Holocene volcanic ashes of of Southern Puna and neighbouring areas (NW Argentina). SEM images detail differences among the Bolsón de Fiambalá, Cerro Blanco and Cueros de Purulla fallout ash deposits. Tephra2 code was used to simulate the ash fallout, and the AshCalc code to compare different methods for ash volume estimates associated with the 4.2 ka cal BP eruption of the Cerro Blanco Volcanic Complex. Topographic profiles are used to explain the secondary thickening of fallout ash deposits. Material suplementario (Figuras S1-S4 y Tablas S1-S4 del artículo Fernandez-Turiel, J.-L.; Perez-Torrado, F. J.; Rodriguez-Gonzalez, A.; Saavedra, J.; Carracedo, J. C., Rejas, M.; Lobo, A.; Osterrieth, M.; Carrizo, J. I.; Esteban, G.; Gallardo, J.; Ratto, N. (2019). The large eruption 4.2 ka cal BP in Cerro Blanco, Central Volcanic Zone, Andes: Insights to the Holocene eruptive deposits in the southern Puna and adjacent regions. Estudios Geológicos 75(1): e088. https://doi.org/10.3989/egeol.43438.515 MINECO, CGL2011-23307, Proyecto QUECA Peer reviewed

Background This data is camera images and nozzle pressure gauge voltage traces from rapid decompression shots at the LMU shock tube facility. This data is discussed in the "Materials and Methods" section of the paper "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows". Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and <100 mg of diamond particles and observe sparks occurring below the sharp boundary of a condensation cloud. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. Simulation results agree closely with the experimentally observed Mach disk shock shape and height. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena. Accessing Data The prefixes of the filenames correspond to the shot dates and times listed in table S1 of the paper. The "_camera.zip" files contains tiff images of the camera frames. The ".ixc" file in each zip lists camera settings in plain text. The ".dat" file contains the voltage measurement of the nozzle pressure gauge. Row 1 is the header, row 2 is the time in seconds, and row 3 is the voltage of the pressure gauge in Volts. The peak pressure in the header can be used to relate the voltage to pressure. This work was performed in part under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344, and Mission Support and Test Services, LLC, under Contract No. DE-NA0003624 with support from the Site-Directed Research and Development program, DOE/NV/03624--0956, and in part by the European Plate Observing Systems Transnational Access program of the European Community HORIZON 2020 research and innovation program under grant N 676564. CC acknowledges the support from the DFG grant CI 25/2-1 and from the European Community HORIZON 2020 research and innovation programme under the Marie Sklodowska Curie grant nr. 705619. LLNL-MI-817289. This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, complete- ness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific com- mercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes. {"references": ["C. Cimarelli, M. Alatorre-Ibargengoitia, U. Kueppers, B. Scheu, D. Dingwell, Experimen- tal generation of volcanic lightning. Geology 42, 79\u201382 (2014)"]}

The critical zone (CZ) represents the most-shallow subsurface, where the bio-, hydro-, and geospheres interact with anthropogenic activity. To characterize the thickness and lateral variations of the CZ, here we focus on the Eastern Betic Shear Zone (EBSZ), one of the most tectonically active regions in the Iberian Peninsula. Within the EBSZ, the Guadalentín Depression is a highly populated area with intensive agricultural activity, where the characterization of the CZ would provide valuable assets for land use management and seismic hazard assessments. To achieve this, we have conducted an interdisciplinary geophysical study along the eastern border of the Guadalentín Depression to characterize the CZ and the architecture of the shallow subsurface. The datasets used include Electrical Resistivity Tomography (ERT), first-arrival travel time seismic tomography, and multichannel analysis of surface waves (MASW). The geophysical datasets combined help to constrain the high-resolution structure of the subsurface and image active fault systems along four transects. The resulting geophysical models have allowed us to interpret the first ~150 m of the subsurface and has revealed: (i) the variable thickness of the CZ; (ii) the CZ relationship between the fault zone and topographic slope; and (iii) the differences in CZ thickness associated with the geological units. Our results provide a method for studying the shallow subsurface of active faults, complementing previous geological models based on paleo-seismological trenches, and can be used to improve the CZ assessment of tectonically active regions. The geophysical data used in this study consisted of two datasets, namely electrical resistivity data and seismic data. Resistivity data were obtained from the Electrical Resistivity Tomography (ERT) method, while seismic data (Vp and Vs) were obtained from the multi-channel analysis of surface waves (MASW) and P-wave travel time tomography. The resistivity and seismic data used in this study were acquired within the INTER GEO research project, which was funded by the Spanish national research program. Funding: J.A. is funded by grant IJC2018-036074-I and by MCIN/AEI /10.13039/501100011033. I.P. is funded by the Spanish Government and the Universidad de Salamanca (Beatriz Galindo grant BEGAL 18/00090). This project was funded by Grant 2017SGR1022 (GREG) from the Generalitat de Catalunya (AGAUR); EU (H2020) 871121 (EPOS-SP); and EIT-RawMaterias 17024 from the European Institute of Technology (EIT) (SIT4ME). Horizon 2020 Framework Programme 871121, EIT-RawMaterias 17024 Universidad de Salamanca 2017SGR1022, BEGAL 18/00090 Agència de Gestió d'Ajuts Universitaris i de Recerca European Institute of Technology SIT4ME Spanish national research program Agencia Estatal de Investigación Generalitat de Catalunya European Commission MCIN

We present an unsupervised and automatic system for volcano deformation monitoring via the Copernicus Sentinel-1 data. The system relies on the Parallel Small BAseline Subset (P-SBAS) approach, permitting us to generate updated displacement time series at every new Sentinel-1 acquisition over a selected area of interest in a fast and accurate way. The service is currently operative to monitor the main active Italian volcanoes in the framework of cooperation with the Italian Department of Civil Protection. The system is potentially extendable to every area on the Earth, thus making it suitable for surface displacement monitoring of a large variety of phenomena. Finally, the obtained results are made available to the scientific community through the EPOS Research Infrastructure.

A cycle of four webinars on Open Science and Open Access for earth and environmental sciences, with discipline-specific tools and practical resources. Course outline: Module 1: - Introduction and motivations - Open Science in Solid Earth Science Module 2: - Research Data Management - OS in solid Earth sciences: the EPOS research infrastructure experience Module 3: - FAIR principles and Open Data - Implementing FAIR. Considerations from the solid Earth domain Module 4: - The Data Management Plan - The adoption of Open Science Paradigm at INGV - Practical Tips Scientific committee: Maria Silvia Giamberini, IGG/CNR Gina Pavone, ISTI/CNR

In Bindi et al. (2019) a harmonized local magnitude scale across Europe has been derived using data disseminated by network operators through the European Integrated Data Archive (EIDA). This data set contains regionalized non-parametric attenuation tables, attenuation corrections to the parametric model and station corrections for both non-parametric and parametric models for more than 2000 stations in Europe. Regionalization has been performed considering six different regions covering Europe and the polygons defining them are also provided. Data are subject to updates that can be triggered by the availability of new and substantial input data (reviewed earthquake catalogues and/or new waveforms). Each update will be released with a new version of the data. The data are provided in ASCII format (.csv).

Earth's surface deformation that occur as a consequence of an earthquake is a crucial information for investigating the causative source of the seismic event. In this context, the space-borne Differential Synthetic Aperture Radar Interferometry (DInSAR) has proven to be one of the key methods for the quantitative measurement of the Earth's surface deformation, with centimetres to millimetres accuracy [1]. DInSAR relies on the evaluation of the phase difference between two SAR images, acquired from different orbital positions and at different times [1]. Depending on the system configuration, the footprint of space-borne SAR acquisitions can span from a few kilometres up to hundreds of kilometres, making it particularly suitable for accurate investigations of wide areas at relative low cost. In these sense, according to USGS records [2], from 1992 to 2016, about 3700 earthquakes with significant magnitudes (Mw > 6.0) have occurred, while only a limited number of them has been successfully investigated through DInSAR [3]. This is mainly due, apart the intrinsic limitation of the DInSAR technique, to the lack of a satellite program with a systematic and global acquisition policy, which are fundamental characteristics to allow creating DInSAR operational services at global scale. However, since the launch of the Copernicus Sentinel-1 SAR satellite missions in 2014 and 2016, the availability of SAR images dramatically increased. Indeed, this constellation acquires, with global coverage policy, radar images every 6/12 days over the same area, allowing us to dispose of a huge archive of SAR data that can be processed for obtaining co-seismic displacement maps in a short time frame and anywhere in the world. Considering the relevance of the satellite interferometric analysis for the hazards monitoring, as well as the availability of new radar systems as Sentinel-1, which are characterized by a high reliability level, is it therefore possible the development of operational services for the generation of DInSAR products, some of them being already in place [4, 5]. In this work an unsupervised and automatic tool for the generation of DInSAR co-seismic displacement maps is presented. Benefiting from the mostly global availability of Sentinel-1 SAR data and the on-line earthquake catalogues, the tool retrieves information about the depth and magnitude of recent earthquakes and triggers, if necessary, the interferometric process over the area affected by the seismic event. The workflow process is the following (Figure 1). First, the extraction of earthquake information (epicenter location, magnitude, time, ...) from the on-line public available web catalogues, as those provided by main international geophysical institutions (e.g. USGS [2], INGV [6]), is performed (Block A of Figure 1). The retrieved information is provided according to different standard formats (QuakeML, geoJSON, ...) and is accessible via subscription feeds that are updated with a defined frequency. The system is not limited to a single earthquake catalog interface. The relevant earthquake information is collected in accordance to an empirical magnitude and depth relation, which considers that only high magnitude (> Mw 6.0) and relatively shallow earthquakes (typically < 20 km) very likely induce a surface deformation that is detectable via DInSAR [7] (Block B). Among the earthquakes that respect the relation, only those with the epicentre on land (or even on water but that can likely induce detectable deformation on land) are processed. Once the occurred earthquake has been selected, the SAR data retrieval is performed via an automatic query to the open access Sentinel-1 catalogue (Block C). The query is performed over an area whose extension depends of the relation between magnitude, depth and epicenter location, which is derived from theoretical and empirical considerations and is susceptible of further tuning and refinement. Once all the tracks covering the earthquake area have been identified, the system retrieves all the available SAR Sentinel-1 data (from both ascending and descending passes) up to 30 days before the event (or at least 1 pre-event image even in a larger time span), in order to allow the generation of the co-seismic interferograms. The data retrieval, and accordingly the subsequent DInSAR processing, remains active up to 30 days after the event. Once the data are downloaded, they are processed through an efficient DInSAR algorithm [8] (Block D). According to this scenario and taking benefit from the operational capability of the Sentinel-1 constellation, the processing of the different tracks can be carried out in parallel, while actually their execution depends on the available computing resources and on the effective temporal acquisition of the SAR data. A processing prioritization of the different tracks on the basis of the post-event acquisition time has been implemented (according to a First come-First served policy). The tool provides wrapped interferograms and displacement maps (unwrapped interferograms converted in centimetres) in the satellite Line of Sight (LOS). The output data are provided according to the specification of the European Plate Observing System (EPOS) [9] research infrastructure, and will be made openly available through the EPOS portal, to be investigated and interpreted by the scientific community. The system has been implemented on in-house computing facilities and has been tested through a controlled experiment with several significant earthquakes. Although tested with Sentinel-1 data, the implemented tool is independent from the exploited SAR acquisitions, thus increasing the number of data to be processed. Indeed, the only dependency is on the catalog interface that, if does not respect an Open standard, requires the implementation of an appropriate wrapper. It is also worth noting that the presented tool, since it takes benefit from efficient and scalable DInSAR algorithms, can be exploited to perform large processing campaigns of all the co-seismic DInSAR pairs acquired by the Sentinel-1, and even ERS and ENVISAT, since their respective launch. To do this, disposing of proper computing facilities, such as those provided by the DIAS [10] platforms where data and processing are co-located, is strongly envisaged.