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Surface wave tomography is a powerful tool for resolving crustal and upper mantle structures without the need of local sources. In this study, we present a 3D model of the Southern Italy and Central Mediterranean region based on the joint inversion of ambient noise and earthquake data. The input data consists of 11 900 phase velocity dispersion curves between 2 and 100 seconds obtained from ambient noise cross correlations and 81 000 phase velocity curves between 8 and 250 seconds obtained from averaging earthquake measurements using the two-station method. The two quality controlled datasets are merged using a correction factor that is derived from inter-station paths where both types of measurements are available.Azimuthally anisotropic Rayleigh wave phase velocity maps are calculated using a regularized least square approach. The phase velocity maps are inverted for a 3D model by applying a stochastic particle swarm optimization algorithm.The resulting 3D velocity model reveals several important features of the subsurface structure, including the subducted Calabrian and Hellenic slabs as well as a slab tear beneath Sicily. Moreover, the model images for example the transition from the Ionian Lithosphere to the Calabrian Slab, deformation of the Adriatic Lithosphere and aesthenospheric flow beneath the Tyrrhenian Sea. These results provide valuable insights into the evolution of the subduction zones in the Adriatic and Central Mediterranean region., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The ongoing activity of Mount Etna and the proximity to the nearby population requires constant monitoring. Infrasound recordings play an important role in volcanic observation because explosive activity near or above ground as well as shallow tremor processes are easier to identify with airborne sound waves than with seismic waves that are significantly scattered and refracted in the volcano edifice. However, infrasound signals are often blurred by noise, in case of Mount Etna, mostly wind induced noise. manual distinction of noisy data from real volcanogenic signals brings along a considerable effort and requires expert knowledge. At Mount Etna five summit craters are currently known with fluctuating levels of activity. This leads to a wide variety of infrasound signal patterns interfered by changing noise levels. In order to distinguish waveforms of noise from signals of volcanic origin we apply unsupervised pattern recognition techniques. We show that by extracting features from the amplitude spectrum different infrasound regimes can be distinguished with Self-Organizing maps (SOMs). This technique provides an option to color-code the results for an intuitive interpretation and allows even for a more detailed recognition of transitional activity regimes. We create a reference data set from multiple months of infrasound waveforms to include as many activity regimes as possible to train the SOM. This enables a fast classification of new data., poster

Villarrica Volcano (Chile) is one of the most active volcanoes in South America. Its low-frequency (≤5 Hz) seismicity consists of a continuous tremor, overlain by impulsive transient events of higher amplitude in 60-s intervals. This signal was recorded in March 2012 by an extensive local network, comprising 75 stations and including 6 subarrays. It allowed us to apply and compare three techniques to locate the origin of the seismicity: intersection of propagation directions determined by array analysis, mapping amplitudes, and modeling of amplitude decay. All methods yield almost identical, temporally stable, epicenters inside the summit crater, which confirms earlier attributions of the seismicity to volcanic activity inside the conduit. The discrete transients and the interevent tremor share the same source location. From the dominance of surface waves and the obvious scattering, we infer a source near the surface. For two arrays at the northern and western flank, a dispersion relation was derived, which allowed for the determination of S wave velocity-depth functions. At both locations, the velocity structure can be modeled by three layers with interfaces at 100 and 400m depths. The velocities (300 to 3,000 m/s) correspond to pyroclastic material at different states of consolidation. The modeling of the amplitude decay reveals a quality factor around 50.