SM2.5 | (1) Challenges and opportunities for operating modern seismic networks: from site selection to advanced data products; (2) Advancing science with global seismological and geophysical networks
(1) Challenges and opportunities for operating modern seismic networks: from site selection to advanced data products; (2) Advancing science with global seismological and geophysical networks
Convener: Carlo Cauzzi | Co-conveners: Frederik J. Simons, Christos Evangelidis, Damiano Pesaresi, Angelo Strollo, Frederik Tilmann, Martin Vallée
| Tue, 25 Apr, 16:15–18:00 (CEST)
Room D3
Posters on site
| Attendance Tue, 25 Apr, 14:00–15:45 (CEST)
Hall X2
Posters virtual
| Attendance Tue, 25 Apr, 14:00–15:45 (CEST)
Orals |
Tue, 16:15
Tue, 14:00
Tue, 14:00
We welcome contributions from all aspects of modern seismic network deployment, operation, management, and delivery of downstream waveform data products, at local, regional and global level: best practice for seismic data management (site selection, equipment testing and installation, planning and telemetry, policies for redundancy in data acquisition, processing and archiving, data and metadata QC, data management and dissemination policies); integration of new data types and communities (DAS systems, large-N instrumentation, OBS, GNSS, gravity, infrasound instruments, rotational sensors, etc.); development, testing, comparison of emerging strategies (e.g. machine learning) and software tools for earthquake monitoring including real-time applications (e.g., source imaging, earthquake early warning, rapid shaking assessment); delivery of technical and scientific seismological and multidisciplinary data products; facilitating the integration of recorded seismological data in computational workflows and digital twins. Promoted by EGU SM-SII and ORFEUS, this session facilitates seismological data discovery and promotes open and FAIR data policies.
Four decades of globally distributed and openly available very broadband seismic recordings have enabled significant advances in characterizing earthquake sources, mapping the deep structure of the Earth, and understanding the behavior of the atmosphere, hydrosphere, and cryosphere. Long-term deployment has illuminated time-dependent processes and allowed subtle signals to be enhanced and utilized through stacking. Real-time telemetry has revolutionized the monitoring capability for large and potentially destructive earthquakes. Central to these activities have been the international partnerships, infrastructure investments, and technological developments that have facilitated, grown, and maintained the availability of low-noise and high-fidelity seismic recordings worldwide. This session focuses on impactful current science being done with globally distributed real-time networks, to understand how technological developments can optimize existing resources, to share ideas for expanding global networks (e.g., Global Seismographic Network, GeoScope) to include other geophysical and environmental observations, to recognize how increased partnerships and collaboration can further grow high-quality station coverage, and to reflect on the common challenges to operating and sustaining these scientific resources.

Orals: Tue, 25 Apr | Room D3

Chairpersons: Carlo Cauzzi, Frederik J. Simons
On-site presentation
Tetiana Amashukeli, Luca Malatesta, Liudmyla Farfuliak, Olexander Ganiev, and Kostiantyn Petrenko

In February 2022, the Ukrainian seismic network already faced multiple critical issues and its modernization was needed. The war exacerbated all existing issues and accelerated the need for a fundamental reorganization and modernization. In this presentation we will report on the network’s status and draft reconstruction plans. As of January 5th 2023, the Ukrainian seismic network has been damaged by the war as follows:

  • partial or complete destruction of facilities and infrastructure caused by power and internet outages;
  • inability to serve stations;
  • complete destruction of Zmiinyi Island (Snake Island) infrastructure where one seismograph was installed;
  • internal and external migration of people involved in the maintenance of stations;
  • delayed standardization of existing seismic stations.

While relatively quiescent, the Ukrainian territory needs an operational seismic network for safety and research purposes. Ukraine hosts a great number of industrial and agricultural facilities critical for the world’s food supply, as well as four nuclear power plants with 15 reactors are located. Seismicity in Ukraine is aligned along the Alpide seismic orogenic belt across the southern and western part of the territory. In addition, significant intraplate earthquakes are recorded in Central and Eastern Ukraine where heavy industries and iron ore mining are concentrated.

The Ukrainian seismic network is currently  divided into three autonomous branches that make up the seismic network of the Institute of Geophysics of the National Academy of Sciences of Ukraine (NAS): Carpathian, Crimean and Central. Unfortunately, these branches were not combined into one unified national network. The base station for observations in Central Ukraine is the IRIS KIEV seismic station (IU, Global Seismograph Network), which is operated by the Institute of Geophysics with support from the US Geological Survey Seismological Laboratory (Albuquerque).

The main goals of modernizing the network must focus on: access to seismological data; long-term data accessibility; calculation of seismic risk; geodynamic and seismic monitoring; surveillance of hazardous facilities. A modernized seismic network is not only a mean of surveillance, but also as a fundamental infrastructure for academic geophysical research in Ukraine.

The integration and data exchange in the European and international community require certificated, industry-standardized seismic instruments and up-to-date digital infrastructure. The seismic network of the Institute of Geophysics of the NAS is equipped with outdated and non-certificated seismic instruments that degrade instrumental data and hamper the exchange of observational materials and scientific analyses with the global community.

The first steps for the modernization of the Ukrainian seismic network started in 2019 with the initiation of a unified platform to process data. For this purpose, the industry-standard SeisComP seismic network software was adopted. In Nov. 2022, we purchased four low-cost Raspberry Shake Seismographs (RS3D) that will be tested in different setting across the territory of Ukraine. Deployment of budget seismometers is a stop-gap measure for both data collection and education in Ukraine.

How to cite: Amashukeli, T., Malatesta, L., Farfuliak, L., Ganiev, O., and Petrenko, K.: Current situation and challenges for the Ukrainian seismic network, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3590,, 2023.

On-site presentation
Nicolas Leroy, Martin Vallée, Dimitri Zigone, Armelle Bernard, Jean-Yves Thoré, Constanza Pardo, Maxime Bes de Berc, Eléonore Stutzmann, Céleste Broucke, Frédérick Pesqueira, Alessia Maggi, Luis Rivera, Michel Le Cocq, and Olivier Sirol

The GEOSCOPE observatory provides more than 4 decades of high-quality continuous broadband data to the scientific community. Started in 1982 with a few stations, the network has grown over the years thanks to numerous international partnerships. The 33 operational GEOSCOPE stations are now installed in 18 countries, across all continents and on islands throughout the oceans, filling important gaps in the global Earth coverage (in Africa, Antarctica, Indian Ocean, Pacific Ocean islands and more). Most of the first installed stations are still running today allowing for long term observations and new sites are being prospected for future installations.

Over the years GEOSCOPE contributed to define today's global seismology standards through the FDSN (data format, data quality level, instrumentation requirements), being the french contribution to the international effort (with GSN, GEOFON and others) towards global seismic observations. The stations are equipped with the best quality seismometers (from the very first STS1 in the early 80's to the last STS-6A and Trilium T360 nowadays) and digitizers (Q330HR and Centaur), in order to record with a high fidelity the ground motions generated by all types of seismic sources. Furthermore, most of the stations are also equipped with accelerometers, pressure and temperature sensors allowing for a wider range of observable events such as the recent Hunga-Tonga eruption. All the data are sent in real-time to IPGP data center and are automatically transmitted to other data centers (IRIS-DMC and RESIF) and tsunami warning centers.

In 2022, a workshop has been organized to celebrate the 40th anniversary of GEOSCOPE and illustrate the main scientific achievements made possible by all the global networks. After a brief look at the history of the network and a feedback on the workshop, the recent evolutions of the observatory (new stations in Africa, new generation 360s sensors upgrades, IT infrastructure) and the perspectives (future stations) will be presented.

How to cite: Leroy, N., Vallée, M., Zigone, D., Bernard, A., Thoré, J.-Y., Pardo, C., Bes de Berc, M., Stutzmann, E., Broucke, C., Pesqueira, F., Maggi, A., Rivera, L., Le Cocq, M., and Sirol, O.: GEOSCOPE: 40 years of global broadband seismic data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9171,, 2023.

Virtual presentation
Jonathan Schaeffer and Helle Pedersen and the EIDA staff

     Data delivery statistics is one of the classical key performance indicators for a large variety of usages : providing insight of data usage to founders, to seismological network managers, to data management centre operational teams.

EIDA is the European Integrated Data Infrastructure from the Orfeus project, federating 12 data management centres which distribute seismological data with the same standardized  methods, enabling users to seamlessly access data from seismological networks (more than 16000 stations) accross Europe.

Since the beginning of the project, various stakeholders have put interest in the data distribution statistics, but sharing the meaningfull indicators to build an unified view turned out to be very challenging. Nonetheless, since 2021, a complete unified statistics service is operational and provides meaningfull KPI over data distribution accross all EIDA nodes.

We will present the story of this project and the lessons learned from the different implementations, emphasising the identified caveats and the useful open source technologies which made the implementation possible.

How to cite: Schaeffer, J. and Pedersen, H. and the EIDA staff: Providing unified data delivery statistics service from european seismological data centers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5304,, 2023.

On-site presentation
Johanna Lehr and Klaus Stammler

Continuous monitoring of data quality is a major issue in seismology because the achievement of robust scientific results depends on the reliability of the underlying data resources. We present a Python package which provides means to perform a systematic analysis of noise data in the time and frequency domain. The tool is designed to process large amounts of channels and years of data. In a first step, average amplitude levels and power spectral densities are computed for large parts - preferably the whole available time range - of the data of a station. Depending on the size of the data set, this processing takes minutes to hours. Therefore, the results are stored in rapidly accessible HDF5-files. Subsequently, they are visualized using color-coded matrix displays (spectrograms) and interactive 3D-figures. The resulting figures give insight to characteristic noise patterns at the station and possible noise sources, like various forms of anthropogenic noise or wind generated noise. Furthermore, changes in noise levels or noise patterns are easily detectable. Such changes either indicate changes in the environmental conditions at the recording site or changes in the recording hardware improperly reflected by the station metadata, often signaling a problem with the metadata. Furthermore, the processed data can easily be restricted to selected times, e.g. to investigate the influence of day/night cycles or to obtain wind-speed dependent spectrograms. In this manner, a comprehensive picture of relevant characteristics at a station site may be acquired.

The package is build from established Python libraries like obspy, scipy and h5py. Matplotlib and plotly are used for data visualization. The core functionalities are accessible via command line interface while the underlying API allows for more customized workflows.

How to cite: Lehr, J. and Stammler, K.: A Python tool to monitor noise characteristics in large seismic data bases, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7144,, 2023.

On-site presentation
Reinoud Sleeman, Elske de Zeeuw-van Dalfsen, and Andreas Krietemeyer

In the Caribbean Netherlands, on Saba, St. Eustatius and St. Maarten, the Royal Netherlands Meteorological Institute (KNMI) deploys the seismic network NA (Caribbean Netherlands Seismic Network) to monitor local tectonic earthquakes and volcanic seismicity. Saba and St. Eustatius are part of the Lesser Antilles volcanic arc and each host an active but quiescent volcano: Mt. Scenery on Saba and The Quill on St. Eustatius. The network comprises 11 broadband seismometers of which data are a) transmitted to KNMI by DSL, cellular connection and VSAT, b) processed in real-time at KNMI using SeisComP and a coincidence trigger, c) forwarded in real-time to the Pacific Tsunami Warning Center (PTWC) and d) openly available to research and monitoring communities through ORFEUS/EIDA and EPOS via standardized services. 

In the past six years we detected and located more than 350 earthquakes with magnitudes ranging from 0.4 to 6 within a 150 km radius from the center of the network. About 230 of these earthquakes were exclusively reported by KNMI as they were probably too small to be detected by, or too distant from, seismic networks operated by other agencies in the region. A previously unnoticed shallow (5-10 km depth) swarm of 22 tectonic earthquakes was detected and located through reanalysis of data from before 2017. This swarm took place in 2008, in the same area as the tectonic swarm of earthquakes in 1992, less than 15 km west of Saba, with magnitudes ranging between 2.3 and 4. One of the challenges for our network is building a reliable detection, identification and location system for volcanic earthquakes, which is hampered by the quiet state of both volcanoes. Another challenge is decreasing the hypocenter uncertainties, which are caused by the complex seismic velocity structure underneath the volcanoes, the large lateral velocity inhomogeneities in the subduction zone and the elongated set-up of the regional seismic networks.

How to cite: Sleeman, R., de Zeeuw-van Dalfsen, E., and Krietemeyer, A.: Developments during 15 years of seismic monitoring in the Caribbean Netherlands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15448,, 2023.

Virtual presentation
Avilash Cramer, Madeline Hunt, Kirsten Arnell, Alan Horton, Susan Stanford, Kent Anderson, and Bruce Beaudoin

Mt Erebus, the world’s southernmost active volcano, is only 30 miles from McMurdo Station (US) and Scott Base (NZ). Scientific instruments deployed on the volcano need to survive a range of environmental factors including high winds, extreme cold, lava bombs, and months of total darkness. Additionally, the reduced air pressure at high elevations affects the lift of the helicopters and the physiology of the engineers during installation.

We present a novel design for a network of environmentally hardened seismic stations intended specifically for the constraints of this polar volcano. The purpose of the network is to provide a baseline measurement of volcanic events and act as a fiducial array for future experiments. Stations are designed to function continuously over both summer and winter for years at a time. The station’s instrument package comprises a data logger recording broadband seismic and infrasound data, and a second data logger recording strong-motion seismic data.  The station design is modular and can be scaled for various experiment requirements and easily adapted for different instrument packages.

Station state-of-health will be monitored at the EarthScope Primary Instrument Center (EPIC, formerly IRIS PASSCAL) and low sample rate (20 sps) broadband data are transmitted by Iridium modems and captured in near-real time. Higher sample rate (100-200 sps) data are recorded locally and collected annually during the austral summer. All data will be available from the EarthScope Data Management Center (network codes 1G, 8E, and 2H).

A prototype was installed near McMurdo station in 2021/22 season and evaluated over the Antarctic winter. Based on this prototype, four stations recording data from nine instruments were installed around Mt Erebus in the 2022/23 season. An additional three stations of an older design that are recording data from five instruments were installed in previous seasons as part of an interim network. These stations will be upgraded to the new design in upcoming seasons.

Our talk will center on the following three components:

1) the electrical and mechanical design of this new station, including power electronics, satellite telemetry, insulation, and rigging;

2) the logistics of Antarctic volcanology, including site selection, geographical constraints, and US Antarctic Program helicopter operations;

3) recent results and future plans for maintaining and upgrading seismic networks on Mt. Erebus.

How to cite: Cramer, A., Hunt, M., Arnell, K., Horton, A., Stanford, S., Anderson, K., and Beaudoin, B.: High-latitude, high-altitude seismic stations on Mt. Erebus, Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9287,, 2023.

On-site presentation
Ruth Murdie, Huaiyu Yuan, John Paul O'Donnell, Subhash Chandra, and Simon Johnson

The Government of Western Australia, through the Geological Survey of Western Australia, is funding a passive seismic acquisition  program, WA array, which has been designed to map Earth’s lithosphere at an optimal level of station spacing across the state of WA (over 2.5 million square kilometres).

The program, which started on 1 July 2022 will involve the deployment of an “array” of 165 seismometers arranged in a grid pattern spaced at 40 kilometre intervals, moving progressively across the state over a period of ten years. Instruments will be relocated on an annual basis across nine regional areas.

It is primarily designed to investigate the crustal and lithospheric mantle structure with the aim of identifying prospective regions for mineral exploration, especially in areas undercover. At the continental scale, the large lithospheric models will target the bulk lithospheric velocities and upper mantle discontinuities, which will provide direct information to better constrain tectonic deformation processes that operated through time. From the Archean nuclei to the Phanerozoic passive margins, WA is composed of many domains with a rich tectonic history; thus WA array will also provide an unprecedented opportunity to study lithospheric structure related to early Earth tectonics, Earth evolution and the Earth today.

The results of the program will step change in our understanding of Western Australia’s lithospheric architecture. This knowledge will provide a sound scientific basis for mineral and energy exploration, but also for evaluating crucial land use decisions over the coming decades, at a time when large areas of the State are expected to accommodate renewable energy projects.

In addition, the data will be used to evaluate the risks from seismic events, which would contribute to risk assessments for the placement industrial infrastructure such as pipelines and hydrogen generation and storage installations as well as building codes for housing and other buildings.

The first deployment of stations is now in the ground with 158 stations currently running. The first results and raw data will become available at the end of 2024. We will present and discuss the design of the array, initial modelling status and model updates, and related program applications.

How to cite: Murdie, R., Yuan, H., O'Donnell, J. P., Chandra, S., and Johnson, S.:         WA array: the next state-wide passive seismic survey, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10584,, 2023.

On-site presentation
Dimitri Zigone, Maxime Bes de Berc, Peter Danecek, Alain Steyer, Francesco Zanolin, Sophie Lambotte, Olivier Alemany, Philippe Possenti, Adriano Cavaliere, Stefano Marino, Jean-Yves Thore, Alessia Maggi, Armelle Bernard, Jean-Jacques Leveque, Luis Rivera, Martin Vallée, Nicolas Leroy, Eleonore Stutzmann, Frédéric Pesqueira, and Constanza Pardo

In the Southern Hemisphere, the prevalence of the oceans and the difficulty of access to land result in a lack of coverage of seismological station which is a strong limitation Our knowledge of the Earth’s structures and of large earthquakes sources. This is particularly critical inside the Antarctic continent where only two permanent seismological stations are currently available (QSPA and CCD). Among them, the seismological station CCD is a joint program between EOST (Strasbourg) and INGV (Roma) and is installed at the Concordia scientific base (75°S 123°E). This observatory, built in 2000 with state-of-the-art surface instrumentation installed in a vault made of snow-covered containers, meets the required quality criteria and has been part of the GEOSCOPE network since 2008. However, it has become necessary to replace this installation for safety reasons, recurring snow coverage issues and seismological performances. The existing seismic vault is deformed by the hydrostatic pressure of the snow. Its proximity to the base causes strong daytime noise (~30 dB) at high frequencies (>1 Hz); the unconsolidated layer of snow about 100m thick forms a waveguide that traps anthropogenic noise from the base. In addition, a coupling defect of the instruments in contact with the snow limits the performance at low frequencies (< 0.03 Hz) on the horizontal channels.

Eight years ago, we proposed to install a borehole seismometer at a depth of 120m to limit the waveguide effects. A new shelter on stilt and the borehole drilling were carried out in 2018/2019. The installation of all the instrumentation has been completed by our team in January 2020. The analyses of the data show that the high-frequency disturbances are very largely attenuated (-30 dB at 10 Hz) compared to the surface installation and that the horizontal channels have a lower noise level at low frequencies (-20 dB at 0.01Hz). In addition, data for all components are below the standard noise model for frequencies between 5 and 9Hz, which already makes this new station one of the quietest installations in the world for those frequencies. A few problems remain to be solved, such as atmospheric pressure-related perturbations for periods longer than 600s on the vertical component. We are currently implementing several patches to try to better insulate the borehole. Updates will be presented during the meeting. Despite this problem at long period, the new CCD borehole stations is a success with better-than-expected performances at all periods shorter than 500s. The data produced are now distributed in the world data centers as G.CCD.20.

How to cite: Zigone, D., Bes de Berc, M., Danecek, P., Steyer, A., Zanolin, F., Lambotte, S., Alemany, O., Possenti, P., Cavaliere, A., Marino, S., Thore, J.-Y., Maggi, A., Bernard, A., Leveque, J.-J., Rivera, L., Vallée, M., Leroy, N., Stutzmann, E., Pesqueira, F., and Pardo, C.: Evolution of the Concordia seismological observatory station CCD (GEOSCOPE network): a new post-hole installation on Antarctica plateau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12520,, 2023.

On-site presentation
Michele De solda, Francesco` Grigoli, Peidong Shi, Federica Lanza, and Stefan Wiemer

In the last few years, the number of dense seismic networks deployed around the world has grown exponentially and will continue to grow in the next years, producing larger and larger datasets. Among the different seismological applications where these massive datasets are usually collected microseismic monitoring operations are certainly the most relevant and are a perfect playground for data-intensive techniques. In these applications we generally deal with seismic sequences characterized by a large number of weak earthquakes overlapping each other or with short inter-event times; in these cases, pick-based detection and location methods may struggle to correctly assign picks to phases and events, and errors can lead to missed detections and/or reduced location resolution. Among the seismological data analysis methods recently developed, waveform-based approaches have gained popularity due to their ability to detect and locate earthquakes without the phase picking and association steps. These approaches exploit the information of the entire network to simultaneously detect and locate seismic events, producing coherence matrices whose maximum corresponds to the coordinates of the seismic event. These methods are particularly powerful at locating microseismic events strongly noise-contaminated, but despite their excellent performance as locators, waveform-based methods still show several disadvantages when used as detectors. Waveform-based earthquake detectors strongly depend on the threshold selected for a certain application. If it is too high, small events may be missed; if it is too low, false events might be detected. To solve this problem, deep learning techniques used for the classification of images can be used to remove the dependence on threshold levels during the detection process. When applied to continuous seismic data, waveform staking methods produce coherence matrices with clear patterns that can be used to distinguish true events from false ones (i.e. noise). The coherence matrices for a seismic event generally show a single and well-focused maximum while pure noise waveforms produce blurred images with low coherence values or many poorly focused maxima. Deep Learning algorithms are the perfect tool to classify these kinds of images and improve the detection capability of waveform-based techniques. The aim of this work is the development of a workflow that, through a Convolutional Neural Network (CNN), detects seismic events by classifying the coherence matrices. We aim to train the CNN by feeding them with synthetic coherence matrices. To generate realistic coherence matrices both for events and noise we use a stochastic modeling approach to generate synthetic noise records with the same spectral properties as the observed one. For each synthetic event or pure noise recording, we finally use waveform stacking to generate coherence matrices that will be used to train the CNN. One important feature of the workflow here exposed is that the training is performed entirely on synthetics without the need for large labeled data, often missing when new microseismic networks are deployed. To test the workflow we apply it to the recently released dataset collected in Iceland, within the COSEISMIQ project.

How to cite: De solda, M., Grigoli, F., Shi, P., Lanza, F., and Wiemer, S.: A deep learning-based workflow for microseismic event detection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1638,, 2023.


Posters on site: Tue, 25 Apr, 14:00–15:45 | Hall X2

Chairpersons: Carlo Cauzzi, Frederik Tilmann
Alberto Michelini, Licia Faenza, Carlo Cauzzi, Valentino Lauciani, John Clinton, Philipp Kästli, Florian Haslinger, Stefan Wiemer, Nikolaos Melis, Nikolaos Theodoulidis, Maren Böse, Graeme Weatherill, Fabrice Cotton, and Domenico Giardini

We present the status of ShakeMap-EU, an initiative initially proposed in 2018 to: (i) provide an integrated archive of ShakeMaps at the European level built on EPOS Seismology ( services & data products and modern community software; (ii) serve as a backup to authoritative ShakeMap implementations; (iii) deliver ShakeMaps for Euro-Mediterranean regions where no local capability is yet available. ShakeMap-EU products are accessible since mid-2020 at the web portal Jointly governed by the institutions participating in the initiative, ShakeMap-EU is founded on voluntary institutional contributions and EC-funded projects. ShakeMap-EU has become a reliable European seismological service that can easily and consistently integrate authoritative models and workflows. The system is based on:  (a) the latest version of ShakeMap® (; (b) the earthquake information delivered by the EMSC (; (c) the earthquake shaking data distributed by ORFEUS (; (d) the ground motion models adopted within EFEHR ( for mapping seismic hazard across Europe; (d) the official ShakeMap configurations of some of the most hazardous countries in Europe. Configuration of, and input to the system are managed via a GitHub repository that allows automatic / manual triggering and interaction by authorized users. ShakeMap-EU provides a collaboration framework and laboratory for seismological agencies to address the challenges posed by the heterogeneity of ground shaking mapping strategies across Europe and the need to promote homogenization and best practices in this domain. ShakeMap-EU is used in research projects as the test platform for novel international collaborative research: among recent examples are the ongoing enhancements towards an evolutionary hazard information system including real-time seismicity characterisation and information on earthquake-induced phenomena.

How to cite: Michelini, A., Faenza, L., Cauzzi, C., Lauciani, V., Clinton, J., Kästli, P., Haslinger, F., Wiemer, S., Melis, N., Theodoulidis, N., Böse, M., Weatherill, G., Cotton, F., and Giardini, D.: ShakeMap-EU: an update on the shakemap service in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5937,, 2023.

Léna Pellorce, Véronique Mendel, Antoine Schlupp, and Marc Grunberg

Shakemaps are important tools for characterizing and visualizing the geographic impact of seismic events. It is also a great support of communication and crisis management, especially in the early stage following an event. It is thus important to constrain at best the parameters controlling the calculation to have the most reliable shakemaps possible. 

Our study consists in optimizing the shakemaps in an application for moderate seismic activity in mainland France and French overseas territories. 

We studied the evolution from v3.5 to v4 of USGS ShakeMapTM and compared the associated shakemaps for past events. An in-depth study of the core calculations of the v4 was necessary to take advantage of their new approaches and optimize the parameters and configuration for the French territories. 

Our goal was not only to implement the ShakeMap v4 as the new automatic functional version on, the BCSF-Rénass website (Résif-Epos), but also to evaluate the prospects and limitations for computing high-resolution shakemaps. We analyzed the uncertainties of shakemaps between rapid shaking assessment based on preliminary data and the late reference shakemap based on complete validated datasets for recent damaging or largely felt events in France.

What can we improve today to reach high-resolution? What might be possible in a few years? Finally, what are the limits that we may never be able to overcome in the ShakeMapTM  program approach?

How to cite: Pellorce, L., Mendel, V., Schlupp, A., and Grunberg, M.: ShakeMapTM v4 study, analysis of rapid shaking assessment, optimization and evaluation of high-resolution prospects for mainland France and French overseas territories, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6302,, 2023.

Yih-Min Wu

Building an earthquake early warning (EEW) network requires the installation of seismic instruments around the seismogenic zone. Using low-cost sensors to build a seismic network for EEW and to generate shakemaps is a cost-effective way in the field of seismology. The National Taiwan University (NTU) network employing 770 P-Alert low-cost sensors based on micro-electro-mechanical systems (MEMS) technology is operational for almost the last 10 years in Taiwan. This instrumentation is capable of recording the strong ground motions of up to ± 2g and is dense enough to record the near-field ground motion. The NTU system has shown its importance during various earthquakes that caused damage in Taiwan. Although the system is capable of acting as a regional as well as an on-site warning system, it is particularly useful for onsite warning. Using real-time seismic signals, each P-Alert device provided a 2–8 s warning time for the near-source earthquake regions situated in the blind zone of the Central Weather Bureau (CWB) regional EEW system, during the 2016 Mw6.4 Meinong and 2018 Mw6.4 Hualien earthquakes. The shakemaps plotted by the P-Alert dense network help to assess the damage pattern and act as key features in the risk mitigation process. These shakemaps are delivered to the intended users, including the disaster mitigation authorities, for possible relief purposes. Currently, the P-Alert network can provide peak ground acceleration (PGA), peak ground velocity (PGV), spectral acceleration (Sa) at different periods, and CWB intensity shakemaps. Using shakemaps it is found that PGV is a better indicator of damage detection than PGA. Encouraged by the performance of the P-Alert network, more instruments are installed in Asia-Pacific countries.

How to cite: Wu, Y.-M.: Development of an earthquake early warning and shakemaps system using low-cost sensors in Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2499,, 2023.

Carlo Cauzzi, Jarek Bieńkowski, Wayne Crawford, Susana Custódio, Sebastiano D'Amico, Christos Evangelidis, Christian Haberland, Florian Haslinger, Anastasia Kiratzi, Petr Kolínský, Giovanni Lanzano, Zafeiria Roumelioti, Karin Sigloch, Reinoud Sleeman, and Angelo Strollo

ORFEUS (Observatories and Research Facilities for European Seismology, is a non-profit foundation that coordinates and promotes seismology in the Euro-Mediterranean area and beyond, through harmonized collection, archival and distribution of seismic waveform data, metadata, alongside offering services and products managed at national level by more than 60 participating seismological Institutions. ORFEUS is one of the founding members of EPOS Seismology ( and a fundamental partner of EC-funded projects. ORFEUS services are largely integrated in the EPOS Data Access Portal ( The key goals of ORFEUS (Bylaws, Article I.3: are achieved through the development and maintenance of data services targeted to a broad community of seismological data users. ORFEUS comprises: (i) the European Integrated waveform Data Archive (EIDA;; (ii) the European Strong-Motion databases (; and iii) the recently established group representing the community of European mobile pools, including amphibian instrumentation ( Products and services for computational seismology are also considered for integration in the ORFEUS domain. Currently, ORFEUS services  provide access to the waveforms acquired by ~18,000 stations in the Euro-Mediterranean region, including dense temporary experiments (e.g., AlpArray, AdriaArray), with strong emphasis on open, high-quality data. Access to data and products is ensured through state-of-the-art information and communication technologies, with strong emphasis on federated web services, clear policies and licenses, and acknowledging the crucial role played by data providers. Significant efforts are underway, by ORFEUS participating institutions,  to enhance the existing services to tackle the challenges posed by the Big Data Era, and to actively encourage interoperability and integration of multidisciplinary datasets in seismological and Earth Science workflows.  ORFEUS also implements Community services that include software and travel grants, webinars, workshops and editorial initiatives. ORFEUS data and services are assessed and improved through the technical and scientific feedback of a User Advisory Group, which comprises European Earth scientists with expertise on a broad range of disciplines. 

How to cite: Cauzzi, C., Bieńkowski, J., Crawford, W., Custódio, S., D'Amico, S., Evangelidis, C., Haberland, C., Haslinger, F., Kiratzi, A., Kolínský, P., Lanzano, G., Roumelioti, Z., Sigloch, K., Sleeman, R., and Strollo, A.: ORFEUS Data Services, Products and Actions to Coordinate Access to Seismic Waveform Data in the Euro-Mediterranean Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9051,, 2023.

Claudia Mascandola, Maria D'Amico, Emiliano Russo, Lucia Luzi, Giovanni Lanzano, Chiara Felicetta, Francesca Pacor, and Sara Sgobba

Strong-motion records and open access to strong-motion data repositories are fundamental to seismology, earthquake engineering and practice. The main archive to disseminate high quality processed waveforms for the European-Mediterranean region is the Engineering Strong-Motion Database (ESM, ESM is developed under the general coordination of the ORFEUS Strong-Motion Management Committee (Observatories and Research facilities for European Seismology;, with the aim to provide users daily access to updated strong-motion waveforms of earthquakes with magnitude greater than 4, mainly recorded in the Pan-European regions. ESM is fully compatible with the European Integrated Data Archive (EIDA; and disseminates waveforms and related metadata according to the Federation of Digital Seismograph Networks (FDSN,

The strategy of ESM is to disseminate only manually processed data to ensure the highest quality. However, the rapid increase in the number of waveforms, due to the increment of seismic stations, leads to the need of automatic procedures for data processing and data quality control.

In this work, we present ESMpro, a modular Python software for a renewed processing framework of ESM. The ESM data processing  is improved with:

(1) automated data quality-check that speeds up the processing time through the rejection of poor-quality records;

(2)  advancement  of the automatic settings for waveform trimming and filtering;

(3) introduction of different algorithms for data processing (Paolucci et al., 2011; Schiappapietra et al., 2021);

(4) modular and flexible software structure that allows the addition of new algorithms and custom workflows.

The accuracy of the updated automatic processing is evaluated by comparison with the waveforms processed by expert analysts, used as benchmarks (Mascandola et al., 2022).

ESMpro is distributed in a stand-alone Beta version available on GitLab (D’Amico et al., 2022;, following the Open Science principles to promote collaborations and contributions from the scientific community. In the next future, a renewed ESM web-processing frontend will be developed to include the ESMpro improvements, as well as new functionalities to process stand-alone data (i.e., not stored in the ESM database) and to allow different input seismic data formats.

How to cite: Mascandola, C., D'Amico, M., Russo, E., Luzi, L., Lanzano, G., Felicetta, C., Pacor, F., and Sgobba, S.: Toward a renewed data processing of the Engineering Strong Motion (ESM) database, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2210,, 2023.

Felix Eckel, Johannes Stampa, Máté Timkó, and Luděk Vecsey

The dense coverage of Europe with seismological stations offers a large variety of advanced seismological data processing options. With thousands of stations available a manual quality check of the data becomes more and more unfeasible. Moreover, with rising network traffic, increasing amounts of users, data requests and data size, errors are more likely to occur and the requested data will not always be available for various reasons. Identifying stations and networks that are more likely to be unavailable during data requests is also part of a data quality control. We show how randomized tests can be used to evaluate the data availability for the European stations and how very simple data processing routines calculating average noise levels at stations can be used to identify erroneous data or metadata.

How to cite: Eckel, F., Stampa, J., Timkó, M., and Vecsey, L.: Data Quality and Availability Tests of public Seismometer Data in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7852,, 2023.

Tomislav Fiket

Deployment of the mobile seismic network around Petrinja in the aftermath of the Petrinja earthquake

After the devastating Petrinja earthquake (ML 6.2) in December 2020, the Croatian Seismological Survey acquired 20 sets (seismographs and accelerographs ) to use as a mobile pool of seismic stations. From January 2021, the installation of more than 20 stations in the wider Petrinja area began. All stations were operational in less than two weeks. Initially, the mobile pool worked offline until a working data transmission solution was found, as DynDNS didn't work with the current cellular network operator. Finally, a VPN solution was applied by installing an OpenVPN server and creating a VPN network that was proven to work properly. Since April 2021, all stations have been online and transmitting data to the CSS headquarters, where the SeisComP3 machine is responsible for data acquisition and processing. After the Ljubinje earthquake in April 2022, some of the stations of the Petrinja mobile pool were relocated to the wider Dubrovnik area. Both sites use accelerographs and seismographs for earthquake detection purposes, with 100 Hz and 200 Hz sampling for seismographs and 200 Hz for accelerographs.The Petrinja Mobile Network is still active today as the aftershock sequence is still active in that area. Details of the equipment purchased, problems encountered and solutions found for data transmission, site selection procedures applied and results achieved are presented.

How to cite: Fiket, T.: Deployment of the mobile seismic network around Petrinja in the aftermath of the Petrinja ML 6.2 earthquake, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2142,, 2023.

Michael Roth, Björn Lund, Gunnar Eggertsson, Peter Schmidt, and Hossein Shomali

In recent years the Swedish National Seismic Network (SNSN) made an increased effort to modernize station and communication equipment, and thereby has significantly improved continuous real-time data availability and data quality.  Currently, the SNSN is operating 67 permanent broadband seismic stations evenly distributed in the South, along the Eastern shore and the North of Sweden. In addition, a temporay network of 13 stations was deployed in 2021 for a 3-year period to monitor small earthquakes associated with a linear cluster of events at the Western cost of the Gulf of Bothnia. SNSN transmits continuous real-time data to networks in the neighboring countries (Norway, Denmark, Finland, Germany) and in turn receives and processes data from about 120 stations abroad.

Compared to many other countries, Sweden has a relatively low seismicity. This makes it all the more important to focus on small seismic events in order to map crustal structures and processes and to provide a data basis for reasonable long-term seismic hazard assessments. Turning to small events means to deal with many events and most of them being man-made seismic events (blasts related to quarries, underground mines, road/tunnel constructions, etc). Within the last 22 years SNSN has recorded and analyzed about 170,000 seismic events out of which only 11,000 (~6.5%) were classified as natural events. Automatic event processing and event type classification are of the essence in order to cope with the amount of data and to decrease the workload of the analysts.

SNSN is running four different and independent automatic processing routines in parallel: SeisComp (SC), Earthworm (EW), MSIL and a migration stack algorithm (MS). The main purpose of SC and EW is to detect and locate events in realtime. Both systems are set up to be very sensitive in order to detect as small events as possible, which on the other side also increases the probability to generate spurious events. To counterbalance that we generate a common event catalogue (i.e. events that were located both by SC as well as EW) which turnes out to be very reliable. The common event bulletin captures events as small as about ML1 and contains almost all events ML > 1.5.  MSIL and MS are running in offline and delayed mode which allows the backfilling of potential data gaps, before processing. These systems are catching events down to about magnitude ML0. All events of the common bulletin and the MSIL bulletin are subject to an automatic Neural Network event typ classification into earthquakes, blasts and mining-induced events. In a final step all events classified as earthquakes, significant blasts (felt events or events of special interest) or events with unclear cassification are reviewed by SNSN analysts and are being made available on the SNSN web page. In the framework of EPOS-Sweden, SNSN will make available the waveform and metadata data of the permanent network via FDSN-services.

How to cite: Roth, M., Lund, B., Eggertsson, G., Schmidt, P., and Shomali, H.: The Swedish National Seismic Network - Infrastructure, Data Processing and Products, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6914,, 2023.

Marcel Paffrath, Antje Schlömer, Markus Terpoorten, Sven Egdorf, Arne Schwab, and Wolfgang Friederich

As part of the “Deutsches Seismologisches Breitband Array” (DSEBRA), a mobile station array of 100 identical seismological broadband stations, the remote monitoring devices “PowBox” were developed by the Ludwig-Maximilians-Universität München.

The PowBoxes log and report the health status of the autonomously operating seismological stations, such as 12V/230V availability or battery temperature. With their various fail-safes the most common issues such as router and battery charger problems are fixed by automatic power resets and efforts and costs on unnecessary maintenance trips can be reduced.

More than 80 PowBoxes are now in operation for the first time with the deployment of the DSEBRA stations in South-East Europe as part of the AdriaArray project, a follow-up to the successful AlpArray project.

To ensure a good overview for the network operator, the modular Python software tool “survBot” was developed at the Ruhr-Universität Bochum. It analyses the different state-of-health channels of the PowBox and the Datalogger, displays them in a graphical user interface or as a html-webpage and informs about emerging problems via e-mail. It is openly available on github.

How to cite: Paffrath, M., Schlömer, A., Terpoorten, M., Egdorf, S., Schwab, A., and Friederich, W.: Enhancing remote monitoring of autonomous seismic stations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15147,, 2023.

James Lindsey, Neil Watkiss, Will Reis, and Dan Whealing

The Guralp Minimus broadband digitizer has led the way with introducing a number of innovative features to broadband digitizers including easy network configuration, compact form-factor, extensive State of Health (SOH) monitoring and low latency digitization. Since its introduction, there have been major technological advances in processing chips resulting in the power consumption of seismic digitizers decreasing drastically in the last few years. The next iteration of Minimus, Minimus2, takes advantage of modern chip power consumption to reduce overall nominal power consumption by over 50% whilst maintaining high functionality. This significant decrease in power consumption will facilitate far more simplified field deployments for offline deployments.

The Minimus platform also provides a high level of functionality for online stations, including the industry unique option of sending State of Health (SOH) data via the SEEDlink protocol. This makes SOH monitoring far simpler for larger networks as SOH data be managed using similar methods as waveform data. This also allows for time-series analysis of SOH data to be able to proactively maintain stations and advance diagnose any issues before they result in any loss of data. The Minimus platform seamlessly interfaces the Discovery software to seamlessly integrate new stations into existing networks. The management of large numbers of real-time seismic stations is further enhanced with Guralp Data Centre (“GDC”) a cloud-based software package to build on the Discovery tool set.

The Minimus platform was built from the ground up to provide one of the lowest latency digitizers available with digitization latencies down to 40ms, making it well suited to Earthquake Early Warning applications. This is achieved with the use of causal decimation filters, high sample rates and Guralp’s proprietary GDI protocol. The Minimus platform is built as a modular digitizer platform that is available within a number of different packages to suit a range of applications, including as a standalone digitizer or built within Broadband seismometer and Force Balance Accelerometer systems. 

How to cite: Lindsey, J., Watkiss, N., Reis, W., and Whealing, D.: The Minimus digitizer platform: a user-friendly ecosystem for efficient network management and seismic station configuration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6725,, 2023.

Michael Laporte, Tim Parker, Valarie Hamilton, and Dan McNamara

More science, particularly related to hazard reduction and earthquake forecasting, is enabled via the availability of rich seismic datasets and event catalogs. Deployment of high performing monitoring networks, which produce high quality datasets, is an investment that enables ongoing and future science advancements.

One measure of network performance, magnitude of completeness (Mc), is determined by a number of factors including station density, network geometry, self-noise and passband of the system used, ambient noise environment and sensor installation method and depth.  Sensor installation techniques related to depth are of particular importance due to their impact on deployment cost and station performance. It is well established that deploying seismic sensors at greater depths reduces their exposure to cultural and environmental noise, improving seismic signal detection. When extended to overall network performance, this noise suppression results in improved (decreased) magnitude of completeness for the network. Using modeling tools, we assess the theoretical improvement in performance associated with an upgrade to borehole installations, increasing sensor depth, for a real world network in the Puget Sound area of Washington State.

The goals of monitoring networks and science are overlapping and dependent. Establishing measurable and achievable performance metrics for these supported networks helps the community understand the present distribution of performance and converge on recommendations for government agencies that will benefit both science and monitoring. For example, datasets from monitoring networks with reduced Mc are likely to inform and enable earthquake forecasting research with the potential to benefit hazard reduction for the general population.

How to cite: Laporte, M., Parker, T., Hamilton, V., and McNamara, D.: Designing or Upgrading a Seismic Network To Meet Specific Performance Criteria Using Array Modeling, a Case Study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16691,, 2023.

Antonio Brcković, Vedran Damjanović, Valentina Gašo, Stijepo Grljević, Marko Kapelj, Iva Kostanjšek, Viktorija Milec, Marko Pervan, Anamarija Tremljan, and Tomislav Fiket

The Republic of Croatia is a seismically highly active area and is currently insufficiently covered by seismological stations. Due to the shape of Croatia, a dense network of seismological stations is needed for more accurate determination of the magnitude and location of earthquakes. One of the main goals of the CROSSNET Project, which the Croatian Seismological Survey carries out, is to install 95 new seismological stations across the Republic of Croatia.

Selection of a site for a seismological station is a complex process that requires careful consideration of a range of factors to ensure that the station is at an optimal location for collecting accurate and reliable data on seismic activity. Field surveys will be required to verify methods used for spatial analysis. The location of the seismological station was chosen based on several factor maps, including natural and anthropogenic noise sources (such as roads, railways, energy infrastructure, industry, and surface waters), geology, and geomorphological criteria (such as slope and aspect).

This study aims to find the most appropriate locations for installing a network of seismological stations in Osječko-baranjska and Vukovarsko-srijemska counties in Croatia. It is necessary to set up seismological instruments at locations with reduced seismic noise conditions and favourable geological conditions to improve the quality of the data acquired.

Given the large scope of the project and the area it covers, an adequate approach is necessary to plan field investigations; therefore, the Suitability modeller in ESRI software ArcGIS Pro was used to evaluate locations for future field surveys. The suitability modelling identifies relevant criteria (factor maps), prepares criteria data, transforms values for each criterion to a standard suitability scale, weights criteria relative to one another according to their importance, combines the criteria into a suitability map, and finally locates the most suitable areas for field investigations.

This work has been fully supported by Next Generation EU and National Recovery and Resilience Plan under project C6.1. R4-I1.

How to cite: Brcković, A., Damjanović, V., Gašo, V., Grljević, S., Kapelj, M., Kostanjšek, I., Milec, V., Pervan, M., Tremljan, A., and Fiket, T.: Seismological station placement in Vukovarsko-srijemska and Osječko-baranjska counties, Croatia: a GIS analysis of environmental noise effects for the CROSSNET project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5389,, 2023.

Euna Park, Jae-Kwang Ahn, Eui-Hong Hwang, Hye-Won Lee, and Sun-Cheon Park

Earthquake early warning (EEW) is a technology that aims to reduce damage by notifying an alarm message before a large shaking due to an earthquake. The EEW currently adopted by most national or local governments is a network-based method. Network-based EEW produces seismic source information based on seismic wave detection from at least three observation stations, so the density of the observation network is a very important factor in shortening the warning time. However, a huge budget and space are required to construct a dense seismic observation network. In order to compensate for such limitations, all sensors capable of detecting vibration are being expanded and applied to seismometers. The Korea Meteorological Administration (KMA) signed an MOU with a private telecommunication service provider and installed about 6,700 MEMS sensors across the country. This is about 22 times more sensors than the existing KMA seismic observation network. In this study, the seismic detection performance of MEMS sensors and the KMA seismometers installed across the country was analyzed from the perspective of time. Since it is difficult to apply the existing seismic wave detection technology to the MEMS sensor as it is, an artificial intelligence-based seismic detection technology was applied. We compared the analysis results of the KMA observation network and the MEMS observation network in real-time for earthquakes of M 3.5 or greater. As a result of real-time detection, it was found that the high-density of observation network was more effective in detecting earthquakes than the performance of the sensor.

How to cite: Park, E., Ahn, J.-K., Hwang, E.-H., Lee, H.-W., and Park, S.-C.: A Study on Earthquake Detection Performance of MEMS Sensors According to Seismic Observation Network Density, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3032,, 2023.

Frederik Tilmann, Thomas Bornstein, Joachim Saul, Jannes Münchmeyer, and Moshe Beutel

Recent years have seen the development of several very powerful machine learning pickers for P and S waves. The recent development of the SeisBench platform ( in combination with mixed regional teleseismic benchmark datasets published by the NEIC (USGS) and GEOFON (GFZ Potsdam) enabled the retraining of the most popular picker neural network models (PhaseNet and EQTransformer) optimised for global monitoring applications in the benchmark study of Münchmeyer et al (2021, J. Geophys. Res.).  

In this contribution we introduce a module scdlpicker, which connects SeisBench to SeisComP (  through a client submodule, which listens to new event detections from the regular SeisComP automatic detection system and triggers repicking of those events with any picker implemented in SeisBench, using the improved picks to trigger a relocation. The machine learning picks are subsequently available within the SeisComP GUI in case further manual refinement or checking is desired. 
We demonstrate application of this system with the GEOFON global earthquake monitoring service (, evaluating the benefits of using the machine learning picker with respect to the conventional workflow relying on traditional pickers with respect to timeliness of reporting earthquakes and reduction of manual work load, and improvement in the number of high quality picks available for each event. 
The quantification of the uncertainty of machine learning picks is important when weighing the contribution of different picks in many location algorithms, yet this information is not readily available from machine learning pickers. They do return, however, a characteristic function (nominally the confidence in the pick), whose properties might correlate with the uncertainty of the pick. We will show whether and how the picking uncertainty correlates with properties of the characteristic function. 

How to cite: Tilmann, F., Bornstein, T., Saul, J., Münchmeyer, J., and Beutel, M.: Employing machine learning pickers for routine global earthquake monitoring with SeisComP: What are the benefits and how can we quantify the uncertainty of picks?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10046,, 2023.

Posters virtual: Tue, 25 Apr, 14:00–15:45 | vHall GMPV/G/GD/SM

Chairperson: Carlo Cauzzi
DIVEnet, an example of drilling monitoring
Roberto Guardo, Simone Salimbeni, Irene Molinari, Silvia Pondrelli, and Adriano Cavaliere