Very low frequency earthquakes (VLFEs) are generally absent from the standard seismicity catalogs because of their depleted seismic radiation at frequencies around and above 1 Hz. With the aim of improving their detection, we have developed an approach where the continuous three-component records of a station pair are first template-matched with the corresponding surface-wave time windows of previously known earthquakes. As a time delay is allowed for one of the stations of the pair, detected events may be not collocated with their templates, and their epicenters can be determined as soon as a second pair is considered. In a second stage, based on their high-frequency radiation, we determine whether the detected events are standard earthquakes absent from the template catalog or VLFEs. This two-stage method, referred as VLFE\_DRL (VLFE Detection and Relative Location), is applied to the southern Ryukyu subduction zone where VLFEs were already known to occur. When compared with existing VLFE catalogs of the area, VLFE\_DRL is shown to provide robust estimates of the VLFE source parameters. Between 2004 and 2024, VLFE\_DRL detects and locates there more than 160 VLFEs with moment magnitude greater than 4, occurring in areas distinct from the standard interplate seismicity.

The faulting caused by dyke intrusions provide a novel opportunity to study the way natural fault systems respond to time-varying changes to the stress field. The recent 2024-2025 Fentale-Dofen dyking episode in the northern Main Ethiopian Rift (NMER) offers a rare opportunity to investigate these processes, as the surface deformation was captured in unusually high spatial and temporal resolution by satellite radar. In our study, we combine Interferometric Synthetic Aperture Radar (InSAR) data from the COSMO-SkyMed satellite, high resolution Digital Elevation Model (DEM), with a catalogue of >150 relocated moderated-sized earthquakes (M4.5-6) to study the spatio-temporal evolution of seismic and aseismic fault slip linked to dyking in the NMER. We focus on an area ~15 km north of the tip of the dyke, where we find fault patches showing both repeated seismic and aseismic slip occurring in close proximity, associated with surface deformation of

Prompt Elasto-Gravity Signals (PEGS) are light-speed gravity perturbations that can be recorded by broadband seismometers before the arrival of P waves. This characteristics has raised interest for potential early warning applications but the emerging nature of PEGS and their extremely small amplitudes (nm/s2) have challenged their operational use. We developed a deep learning approach to rapidly estimate the magnitude and location of large earthquakes from PEGS. In order to optimize the performances, we designed a graph neural network (PEGSGraph) capturing the geometrical information of the seismic network. This approach is not subject to saturation and can reliably estimate the magnitude of Mw ≥ 7.6 earthquakes within 2 minutes from initiation in Alaska, making it a viable solution for tsunami warning. We are currently testing possible implementations of PEGSGraph into the tsunami early warning systems of Peru and Alaska and including GNSS version in the deep learning framework.

Here we analyze the rupture process of the 29 December 2020 M(W)6.4 Petrinja earthquake (Croatia), the largest event instrumentally recorded in this area characterized by a moderate strain-rate intraplate setting. We use foreshocks and aftershocks, recorded at more than 80 broadband stations located 70-420 km from the earthquake, as empirical Green's functions (EGFs) to separate source effects from propagation and local site effects. First, we deconvolve the mainshock P-wave time windows from the EGFs in the frequency domain to obtain the corner frequency (f(c)). Spectral analysis based on the Brune's source model reveals a large stress drop of 24 MPa. Next, by deconvolving the Love waves in the time domain, we calculate the Apparent Source Time Functions (ASTFs). We find that the average duration of the source is similar to 5 s, with no significant directivity effects, indicating a bilateral rupture. To extract physical rupture parameters such as rupture velocity, slip distribution and rise time, we deploy two techniques: (a) Bayesian inversion and (b) backprojection onto isochrones of ASTFs. Both techniques show a low rupture velocity (40%-50% of the shear wave velocity) and a rupture length of less than 10 km, that is, much less than would typically be expected for a magnitude 6.4 earthquake. This apparent anticorrelation between stress drop and rupture velocity may be attributed to the complex and segmented fault system characteristic of immature intraplate settings.

A signal, coined PEGS for Prompt Elasto-Gravity Signal, was recently identified on seismograms preceding the seismic waves generated by very large earthquakes, opening promising applications for earthquake and tsunami early warning. Nevertheless, this signal is about 1,000,000 times smaller than seismic waves, making its use in operational warning systems very challenging. A Deep Learning algorithm, called PEGSNet, was later designed to estimate, as fast as possible, the magnitude of an ongoing large earthquake from PEGS recorded in real time. PEGSNet was applied to Japan and Chile and proved capable of tracking the magnitude of the Mw 9.1 Tohoku-oki and Mw 8.8 Maule earthquakes within a few minutes from the events origin times. Here, we apply this algorithm to a very well instrumented region: Alaska. We find that, applied to such a dense seismic network, the performance of PEGSNet is drastically improved, with robust performances obtained for earthquakes with magnitudes down to 7.8. The gain in resolution also allows us to estimate the focal mechanism of the events in real time, providing all the information required for tsunami warning within less than 3 minutes.

In the Southern Hemisphere, the prevalence of oceans and the difficulty of access to land result in reduced coverage of seismological stations, limiting our detailed knowledge of Earth 's structures and of large earthquakes sources. This situation is exacerbated inside the antarctic continent, where only two permanent seismic stations are currently available (IU.QSPA at South Pole and G.CCD). The CCD station, built in early 2000s with state -of -theart surface instrumentation and located at the French -Italian Concordia base (75 degrees S, 123 degrees E), has been providing seismological data since 2008. However, it suffers from several problems: the vault is deformed by the hydrostatic pressure of the snow, the firn waveguide traps anthropogenic noise from the base causing strong noise below 1 s, and a coupling defect limits the performance above 30 s on the horizontal channels. To ensure the continuity of CCD and to improve its overall performance, we started in 2014 to plan the installation of a borehole seismometer at the site. In this article, we describe in detail this renovation of CCD and some examples of data analysis. The new borehole sensor shows that short -period disturbances are largely attenuated ( -20 dB at 0.1 s) compared to the surface installation and that the horizontal channels have a lower noise level at long periods ( -8 dB at 100 s). Data for all components are below the standard noise model between 0.1 and 0.2 s, which makes this sensor one of the quietest installations in the world for this bandwidth. For periods > 600 s we observe atmospheric pressure-related perturbations on the vertical component. Despite this problem, the new CCD borehole station is a success with better-than-expected performances at all periods < 600 s. The data produced are now distributed in the world 's data centers as G.CCD.20 and we encourage the scientific community to use the data for all studies requiring seismograms from Antarctica.

Prompt ElastoGravity Signals are light-speed gravity-induced signals recorded before the arrival of seismic waves. They have raised interest for early warning applications but their weak amplitudes close to the background seismic noise have questioned their actual potential for operational use. A deep-learning model has recently demonstrated its ability to mitigate this noise limitation and to provide in near real-time the earthquake magnitude (Mw). However, this approach was efficient only for large earthquakes (Mw >= 8.3) of known focal mechanism. Here we show unprecedented performance in full earthquake characterization using the dense broadband seismic network deployed in Alaska and Western Canada. Our deep-learning model provides accurate magnitude and focal mechanism estimates of Mw >= 7.8 earthquakes, 2 minutes after origin time (hence the tsunamigenic potential). Our results represent a major step towards the routine use of prompt elastogravity signals in operational warning systems, and demonstrate its potential for tsunami warning in densely-instrumented areas. A deep-learning model can estimate the magnitude and focal mechanism of large earthquakes in near-real time using light-speed gravity-induced signals recorded by seismometers before the arrival of seismic waves, advancing tsunami warning systems.

The GEOSCOPE observatory (Institut de physique du globe de Paris [IPGP] and École et Observatoire des Sciences de la Terre de Strasbourg, 1982) provides more than four decades of high-quality continuous broadband data to the scientific community. Started in 1982 with only two stations, the network has grown over the years thanks to numerous international partnerships. At present, 34 stations operate in 18 countries across all continents and on islands throughout the oceans, filling important gaps in global Earth coverage. Most of the first installed stations are still running today, allowing for long-term observations, and new sites are being prospected to further improve global coverage. Over the years, GEOSCOPE has contributed to defining today’s global seismology standards (data format, data quality level, instrumentation requirements), being the French contribution to the international effort for global seismic observations. The stations are instrumented with the best quality seismometers (from the very first STS-1 in the early 80s to the last STS-6A and Trillium T360 today) and digitizers (Q330HR and Centaur) to record with high fidelity the ground motions generated by all types of seismic sources. Real-time data are sent to the tsunami warning centers and both validated and real-time data are available at the IPGP, Epos-France and Earthscope data centers. The quality of GEOSCOPE data and metadata is ensured by daily and yearly validation that enables issue detection and mitigation. GEOSCOPE, in collaboration with the other global networks, has played and continues to play a crucial role in the study of Earth’s structure and global dynamics and the characterization of all types of seismic sources.

In the minutes following a large earthquake, robust characterization of the seismic rupture can be obtained from full wavefield records at local distances or from early signals recorded by regional broadband seismometers. We focus here on the latter configuration, and evaluate the individual and joint performances of the early low-frequency elastic phases (W phase) and the recently discovered prompt elastogravity signals (PEGS). The 2011 Mw 9.1 Tohoku-Oki earthquake is a natural target for this evaluation, because the high quality of global and regional networks enabled to gather the best PEGS data set so far. We first confirm that the well-established W-phase method, using records from global seismological networks, is able to provide a reliable centroid moment tensor solution 22 min after the earthquake origin time. Using regional stations, an accurate W-phase solution can be obtained more rapidly, down to 10 min after origin time. On the other hand, a PEGS-based source inversion can provide even earlier, starting 3 min after origin time, a lower bound of the seismic moment (Mw 8.6) and constraints on the focal mechanism type. However, relying solely on PEGS introduces uncertainties caused by the hindering seismic noise and trade-offs between source parameters that limit the accuracy of source determination. We show that incorporating even a few early W phase signals to the PEGS data set reduces these uncertainties. Using more complete W phase and PEGS data sets available 5 min after origin time enables to converge towards a result close to the Global Centroid Moment Tensor solution.

The 2019/05/26 Northern Peru earthquake (Mw=8) is a major intermediate-depth earthquake that occurred close to the eastern edge of the Nazca slab flat area. We analyze its rupture process using high-frequency back-projection and seismo-geodetic broadband inversion. The latter approach shows that the earthquake propagated with almost purely normal faulting along the 60° eastward dipping plane. Both imaging techniques provide a very consistent image of the peculiar space-time rupture process of this earthquake: its 60-second long rupture is characterized both by a main northward propagation (resulting in a rupture extent of almost 200 km in this direction) and by a reactivation phase of the hypocentral area, particularly active 35 s to 50 s after origin time. Given the depth of this earthquake (125-140 km), the reactivation time window coincides with the arrival time of the surface-reflected elastic wavefield. Computed values of the dynamic Coulomb stresses associated with this wavefield are of the order of ten to several tens of kPa, in a range of values where dynamic triggering has already been observed. The reactivation phase of the Peru earthquake may thus originate from fault areas that were brought close to rupture by the initial rupture front before being triggered by stress increments provided by the reflected wavefield. Source time function complexity observed for other large intermediate-depth earthquakes further suggests that such a mechanism is not an isolated case.

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.

The 2019/05/26 Northern Peru earthquake (Mw=8) is a major intermediate-depth earthquake that occurred close to the eastern edge of the Nazca slab flat area. We analyze its rupture process using high-frequency back-projection and seismo-geodetic broadband inversion. Both imaging techniques provide a very consistent image of the peculiar space-time rupture process of this earthquake : its 60-second long rupture is characterized both by a main northward propagation (resulting in a rupture extent of almost 200km in this direction) and by a reactivation phase of the hypocentral area, particularly active 35s to 50s after origin time.Given the depth of this earthquake (125-140km), the reactivation time window coincides with the arrival time of the surface-reflected elastic wavefield. Computed values of the dynamic Coulomb stresses associated with this wavefield are of the order of ten to several tens of kPa, in a range of values where dynamic triggering has already been observed. The reactivation phase of the Peru earthquake may thus originate from fault areas that were brought close to rupture by the initial rupture front before being triggered by stress increments provided by the reflected wavefield. Source time function complexity observed for other large intermediate-depth earthquakes further suggests that such a mechanism is not an isolated case.

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.

The dataset includes waveform data for centroid moment tensor solutions inferred using Hamiltonian Monte Carlo and a 3-D Earth model in the Japanese islands. The data are provided as Green's strains at the maximum-likelihood location (indicated in the title of each text file) for all study events inverted at different periods. Inversion period is also indicated in the title. All the data are filtered between 15 s and 80 s. Additionally we provide a Python code to obtain displacement from strains given a moment tensor.

The highly used Global Seismographic Network (GSN) is a pillar of the seismological research community and contributes to numerous groundbreaking publications. Despite its wide recognition, this survey found that the GSN is not consistently acknowledged in scientific literature and is underrepresented by roughly a factor of 3 in citation searches. Publication tracking is a key metric that factors into operational decisions and funding support for the network; thus, consistent and proper citation of the GSN is important. This study not only serves as a reminder for researchers using GSN observations to cite the network's digital object identifiers (DOIs) but also promotes a community-wide conversation among researchers, journal editors, network operators, and other stakeholders regarding more standardized policies and review processes to ensure seismic networks are properly and consistently recognized for their contributions to research.

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

Properties of earthquake source physics can be inferred from the comparison between seismic observations and results of dynamic rupture models. Although simple self-similar rupture models naturally explain the space and time observations at the scale of the whole earthquake, several observational studies based on the analysis of source time functions (STFs) suggest that they are unable to reproduce the initial accelerating phases of the rupture. We here propose to reproduce the observed transient moment accelerations, without affecting the global self-similarity of the rupture, to constrain their possible physical origins. Simulated STFs are generated from dynamic simulations with heterogeneous slipweakening distance Dc. Heterogeneity is introduced on the fault plane through a fractal number-size distribution of circular patches, in which Dc takes a value proportional to their radius. As a consequence of the stochastic spatial distribution of the patches, rupture development exhibits a large variability, and delays between initiation and main rupture activation frequently occur. This variability, together with the dynamic correlation between rupture velocity and slip velocity inside each broken patch, successfully perturbs the self-similar properties: rather than growing quadratically with time, STFs have an higher apparent time exponent, close to the observed value of 2.7. In a broader perspective, our simulations show that to respect observed STF shapes, realistic dynamic models should generate bursts of seismic moment, most likely by episodes where slip and rupture velocity are correlated. Such a behavior appears to emerge more naturally when considering heterogeneities in the friction parameters rather than in the initial stress.