ALBERT

Description: Despite its role in Arabia-Eurasia convergence between the Black and Caspian Seas, the Caucasus region lacks a comprehensive catalog. To address the issue, the Lawrence Livermore National Laboratory and the Institute of Earth Sciences (IES) at Ilia State University generated a new, comprehensive seismic catalog for the Caucasus region by combining data in the IES bulletin with bulletins of the Republic Seismic Survey Center of Azerbaijan, monitoring centers in Turkey and Armenia, and the ISC covering the period 1951 to 2019. We present the bulletin that contains some 20,000 relocated events. We first relocated each event using the single-event location algorithm iLoc and RSTT predictions and identified GT events. Then we relocated the entire seismicity of the Caucasus region with the multiple-event location algorithm Bayesloc, using the iLoc results as initial locations and the GT events as constraints. We show that each relocation step leads to significant improvements, as indicated by tightening of event clusters. The improved view of the seismicity reveals a narrow band of crustal events along the southern flank of the Greater Caucasus we interpret as a megathrust, and confirms both a region of deep seismicity beneath the northeastern Caucasus and a possible area of slab detachment in the central part of the range.

Description: The Central and Eastern European Infrasound Network (CEEIN) established in 2018 as the collaboration between the Zentralanstalt für Meteorologie and Geodynamik, Vienna, Austria; the Institute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic; the Research Centre for Astronomy and Earth Sciences of the Eötvös Loránd Research Network, Budapest, Hungary; the National Institute for Earth Physics, Magurele, Romania and the Main Centre of Special Monitoring National Center for Control and Testing of Space Facilities, State Agency of Ukraine. Waveform data of the CEEIN stations are archived at the NIEP EIDA node, and can be downloaded from www.ceein.eu. We show that CEEIN improves infrasound event detection capabilities in Southern and Eastern Europe, and demonstrate that adding infrasound observations to seismic data in the location algorithm improves location accuracy. We identify coherent noise sources observed at CEEIN stations. We present the bi-annual CEEIN bulletin of infrasound and seismo-acoustic events, our contribution to the European infrasound catalogue. Many of the events in the CEEIN bulletin are ground truth events that can be used in the validation of atmospheric models and infrasound raytracing algorithms.

Description: The huge volume of infrasound detections asks for machine learning techniques for the automatic classification of signals. Our objective was to assess machine learning algorithms in identifying signals. Since 2017, the Hungarian infrasound array has collected approximately one million detections, processed with the Progressive Multi Channel Correlation method. Of these, we categorised some 14,000 detections from quarry blasts, storms and a power plant. These detections constitute the dataset for machine learning training, validation and testing. After pre-processing, features were extracted from the waveforms both in the time and frequency domain, to characterize the physical properties of the signals. We also defined PMCC related features to measure the similarity between the detections. For training, two classifiers were selected, Random Forests and Support Vector Machines. Hyperparameter tuning was performed with three-fold cross-validation using grid search. As a metric, f1 score was selected, and the confusion matrices were analysed. The goal was to separate the detections labelled as quarry blasts from the storm and power plant classes. The results reach 0.88 f1 scores, and high true positive rate for the quarry blasts, which show promising step in the direction of infrasound signal classification via machine learning.

Description: We perform a comprehensive P-to-S and S-to-P receiver function analyses to determine the depth of lithospheric discontinuities in the Eastern Alps, Pannonian Basin, Carpathians, and the Dinarides. The Pannonian Basin of Central Europe hosts thick sedimentary deposits of up to 7 km thickness in extensional half-graben geometries overlying the crystalline orogenic basement. Prior to this study, the mapping of the seismic discontinuities in the lithosphere beneath the investigated area was not uniform and the estimated depth values bore non-negligible uncertainties. Owing to the combined, dense station coverage of more than 380 seismological stations we can achieve hitherto unprecedented spatial resolution. Our study is based on two decades (2002–2022) of broadband waveforms with uniform automatic waveform processing and quality control procedures. This detailed procedure provides new geological and geophysical information about the lithosphere of the region. The obtained results allow us to infer a 3D lithospheric structural model of the region. We have developed a new interpolation and visualization algorithm. We mapped the thickness of the main crustal layers and the lithosphere, together with an estimate of their uncertainties. We present the sedimentary thickness map, the first Conrad depth map and an improved, detailed Moho map, the first upper and lower crustal thickness maps, as well as the lithospheric (Lithosphere-Asthenosphere-Boundary and Mid-Lithospheric-Discontinuity) thickness map obtained from receiver function analysis. We show migrated Common Conversion Point cross-sections beneath the Pannonian Basin and Carpathians, and the Eastern Alps–Pannonian Basin transition zone. Finally, we compare and jointly interpret the results of the receiver functions with previous geophysical investigations and seismic tomography models.