Abstract
Ambient seismic noise has proven to be a particularly effective tool for subsurface imaging in the last decades, with applications ranging from near surface imaging, to crustal or upper mantle tomography. Fundamentally, it relies on the cross correlations of continuous recordings of ground motion data at pairs of seismic stations. Processing steps have become more refined and promising in extracting meaningful signals that can further be used in a range of classic seismology tools. The processing, however, is usually cumbersome, time- and memory-consuming, as it requires years of continuous noise recorded at broadband seismic stations, to obtain high signal-to-noise ratio empirical Green’s functions. In order to ease the research effort, we built a database of ambient seismic noise cross correlations between pairs of broadband seismic stations that operated in Central and Eastern Europe between 1999 and 2020. The database is part of the Eastern European Ambient Seismic Noise (EENSANE) research project hosted by the National Institute of Earth Physics in Romania and will progressively grow as more stations become available, such as those provided by the new AdriaArray network. Based on this database and using state-of-the-art inversion techniques, we developed a series of near-surface and crustal tomography models of the Eastern European craton, the Trans-European Suture Zone and younger accreted terranes from Central Europe. Our integrated models provide both isotropic and azimuthally anisotropic seismic velocities from surface wave dispersion and attenuation parameters from the decay envelopes of Rayleigh waves. Using horizontal-to-vertical ratios of ambient noise, we also recovered the fundamental frequency of resonance and near surface shear wave velocity models beneath stations located across the Carpathian Orogen. Based on cross-correlation functions, we were also able to retrieve the seismic wavefield and peak ground displacement amplitudes from past earthquakes decades after their occurrence, offering a chance for improving seismic hazard and risk models in seismically vulnerable and developing regions of Europe. Our multidisciplinary results prove the versatility of ambient noise uses and the importance of the EENSANE database for a wide range of seismological imaging and hazard applications.
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Data availibility
The Supplementary Material contains tables of network and station details, their archiving centers and overlapping data periods. Access to raw seismic data was made using FDSN (International Federation of Digital Seismograph Networks) Web Services (https://www.fdsn.org/webservices/). Access to the ambient noise cross-correlation database and further results can be found on the project’s website (https://eensane.infp.ro/) and in the Mendeley data repository at https://data.mendeley.com/datasets/scr529r5bk/1. Most codes for processing ambient noise data are freely available: the continuous wavelet transform (https://github.com/SwiftHickory/bc_denoise.git, accessed Aug 2021), the ambient noise cross-correlation and automatic phase velocity dispersion analysis (https://github.com/ekaestle/amb_noise_tools, accessed Aug 2021), and the Markov-chain Monte Carlo surface wave inversion (https://github.com/jenndrei/BayHunter, accessed Sep 2021), modeling virtual earthquake wavefields (https://github.com/mdenolle/vea—accessed Feb 2022) and inverting HVSR curves (https://w3.ual.es/GruposInv/hv-inv/, accessed Aug 2022). Most figures were plotted with the GMT (Generic Mapping Tools) software (Wessel et al. 2013).
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Acknowledgements
We thank Emanuel Kastle for making their ambient noise processing codes available and for providing help with their usage. We are also grateful to Oleksandr Ivanovich Liashchuk for providing data for some stations operated by the Main Center of the Special Monitoring of Ukraine which greatly improved the seismic velocity model resolution in the East European Craton. We thank two anonymous reviewers and Editor György Hetényi for constructive comments that served to improve the original manuscript.
Funding
The present study was funded by the EENSANE (East European Ambient Seismic Noise https://eensane.infp.ro/) Project PN-III-P4-ID- PCE-2020-2972 supported by UEFISCDI (Executive Agency for Higher Education, Research, Development and Innovation Funding), Romania.
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LP was responsible for initial funding acquisition, formal analysis, visualisation of results and writing of the original manuscript. AP helped with data curation and analysis and original manuscript writing. FB helped with results visualisation, formal analysis, methodology, software, and manuscript writing and editing. AM, MR, and MP carried out routine data analysis and manuscript editing. AC and CC contributed to manuscript review.
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Petrescu, L., Plăcintă, A.O., Borleanu, F. et al. The EENSANE (Eastern European Seismic Ambient Noise) project: providing a new free database of ambient noise cross-correlations and crustal seismic models in the Carpathian-Pannonian Region and beyond. Acta Geod Geophys (2024). https://doi.org/10.1007/s40328-024-00438-x
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DOI: https://doi.org/10.1007/s40328-024-00438-x