| Popis: |
The Carpathian-Pannonian region (CPR) is one of the geotectonically most exciting areas of Europe due to a diversity of tectonic processes activating in close proximity: extensional basin evolution, oceanic subduction, post-collisional volcanism, as well as active crustal deformation associated with the push of the Adria plate or the pull of the actively detaching Vrancea slab. This makes CPR an excellent natural laboratory to study the behavior of the lithosphere-asthenosphere system in a special tectonic setting. To emphasize the lateral heterogeneity and physical properties of the crust in the CPR we investigate noise data recorded by the vertical components of broadband stations that have been operational in 2007, 2009, 2010, 2011 and 2020 in Eastern Europe, kindly provided by the Romanian Seismic Network and EIDA-European Integrated Data Archive. With the advent of this large amount of data and by applying a new processing method of ambient seismic noise field based on the continuous wavelet transform, we computed cross-correlations between various station pairs to transform every available seismic station into a virtual source. The inter-station cross-correlograms were used to determine the coda quality factors (Qc) in three different period ranges (2.5–5 s, 5–10 s and 10–20 s) and invert them using a modified version of the open-access code MURAT2D to construct the highest resolution attenuation tomography of the region. By mapping the attenuation features, within the study region, our results reveal high attenuation features throughout the Bohemian Massif, Alcapa unit, and Vrancea area, as well as a strong difference in attenuation between the Pannonian Basin, and stable platform regions located in front of the Carpathians. In addition, Qc variations are larger at short period in agreement with the strong heterogeneities in the uppermost crust. Finally, our findings demonstrate that noise correlation approaches are more efficient in analyzing Qc at lower frequencies than those previously proposed for earthquake data analyses. |
