ALBERT

Description: We present a new upper-mantle tomographic model derived solely from hum seismic data. Phase correlograms between station pairs are computed to extract phase-coherent signals. Correlograms are then stacked using the time–frequency phase-weighted stack method to build-up empirical Green's functions. Group velocities and uncertainties are measured in the wide period band of 30–250 s, following a resampling approach. Less data are required to extract reliable group velocities at short periods than at long periods, and 2 yr of data are necessary to measure reliable group velocities for the entire period band. Group velocities are first regionalized and then inverted versus depth using a simulated annealing method in which the number and shape of splines that describes the S-wave velocity model are variable. The new S-wave velocity tomographic model is well correlated with models derived from earthquakes in most areas, although in India, the Dharwar craton is shallower than in other published models.

Description: The Afar area is one of the biggest continental hotspots active since about 30 Ma. It may be the surface expression of a mantle “plume” related to the African Superswell. Central Africa is also characterized by extensive intraplate volcanism. Around the same time (30 Ma), volcanic activity re-started in several regions of the African plate and hotspots such as Darfur, Tibesti, Hoggar and Mount Cameroon, characterized by a significant though modest volcanic production. The interactions of mantle upwelling with asthenosphere, lithosphere and crust remain unclear and seismic anisotropy might help in investigating these complex interactions. We used data from the global seismological permanent FDSN networks (GEOSCOPE, IRIS, MedNet, GEO- FON, etc.), from the temporary PASSCAL experiments in Tanzania and Saudi Arabia and a French deployment of 5 portable broadband stations surrounding the Afar Hotspot. A classical two-step tomographic inversion from surface waves performed in the Horn of Africa with selected Rayleigh wave and Love wave seismograms leads to a 3D-model of both SV velocities and azimuthal anisotropy, as well as radial SH/SV anisotropy, with a lateral resolution of 500 km. The region is characterized by low shear-wave velocities beneath the Afar Hotspot, the Red Sea, the Gulf of Aden and East of the Tanzania Craton to 400 km depth. High velocities are present in the Eastern Arabia and the Tanzania Craton. The results of this study enable us to rule out a possible feeding of the Central Africa hotspots from the “Afar plume” above 150–200 km. The azimuthal anisotropy displays a complex pattern near the Afar Hotspot. Radial anisotropy, although poorly resolved laterally, exhibits SH slower than SV waves down to about 150 km depth, and a reverse pattern below. Both azimuthal and radial anisotropies show a stratification of anisotropy at depth, corresponding to different physical processes. These results suggest that the Afar hotspot has a different and deeper origin than the other African hotspots (Darfur, Tibesti, Hoggar). These latter hotspots can be traced down to 200 km from S-wave velocity but have no visible effect on radial and azimuthal anisotropy.

Description: Seismic noise spectra at all seismic stations display two peaks in the 1–20 s period band, called primary and secondary microseisms. They are caused by the coupling of ocean waves into Rayleigh waves. At most locations, microseismic power is greater during local winter (when nearby oceans are stormier) than local summer. This tendency is reversed for stations in Antarctica, where growth of local winter sea ice seems to impede microseism generation in near coastal areas. A decade of continuous data from coastal seismic stations in Antarctica show systematic seasonality in microseismic signal levels, and demonstrate associations with both broad-scale and local sea-ice conditions. Primary microseisms are known to be generated at the coast and the modulation that we observe can be associated with sea-ice variations both in the vicinity of the station and along other Antarctic coasts. The similar modulation of short-period secondary microseisms corroborates their mostly near-coastal origin, while the continued presence of long-period secondary microseisms suggests more distant source regions. These observations could be used to extend the monitoring of climate variability prior to the availability of satellite-derived climate indicators.

Description: The GEOSCOPE observatory provides more than four 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 installed in 18 countries, filling gaps in the global Earth coverage (in Africa, Antarctica, Indian Ocean, Pacific Ocean islands and more). 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, IRIS-DMC, RESIF, and tsunami warning data 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 look at the history of the network, the recent evolutions of the observatory in terms of instrumentation and data products (near-real time earthquake analyses) will be presented.

Description: The Greenland ice sheet is a critical component of the global climate system, and its significant mass loss due to iceberg-calving has greatly contributed to sea-level rise. Through the quantification of the spatio-temporal changes in Greenland’s ice mass loss resulting from iceberg calving, we gain a deeper understanding of the impact of climate change. The mass loss related to calving icebergs can be estimated by combining mechanical simulation of iceberg calving and inversion of seismic data. Indeed, seismic signals are generated by the time-varying force produced during iceberg calving on marine-terminating glacier termini. Those events, known as glacial earthquakes, are recorded by the Greenland Ice Sheet Monitoring Network at tens of km from the source. However, differentiating these signals from tectonic events, anthropogenic noise, and other natural noise is challenging due to their wide frequency range. To overcome this challenge, we use a detection algorithm based on the STA/LTA method and machine learning (Random Forests) trained on catalogues with known events. This algorithm will be applied to continuous data to detect new and possibly smaller events. As a result, we will present a comprehensive catalogue spanning several years and discuss its relevance and reliability. Finally, we will examine the correlations between events in the catalogue and external factors, such as climatic and meteorological events. The catalogue and machine learning approach can be used in the future to extract properties of the source from the generated seismic signals, such as the volume or the shape of the iceberg.

Description: In December 2018, the National Aeronautics and Space Administration (NASA) Interior exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission deployed a seismometer on the surface of Mars. In preparation for the data analysis, in July 2017, the marsquake service initiated a blind test in which participants were asked to detect and characterize seismicity embedded in a one Earth year long synthetic data set of continuous waveforms. Synthetic data were computed for a single station, mimicking the streams that will be available from InSight as well as the expected tectonic and impact seismicity, and noise conditions on Mars (Clinton et al., 2017). In total, 84 teams from 20 countries registered for the blind test and 11 of them submitted their results in early 2018. The collection of documentations, methods, ideas, and codes submitted by the participants exceeds 100 pages. The teams proposed well established as well as novel methods to tackle the challenging target of building a global seismicity catalog using a single station. This article summarizes the performance of the teams and highlights the most successful contributions.