GNGTS 2019 - Atti del 38° Convegno Nazionale

GNGTS 2019 S essione 3.1 547 parameter of their inversions. Similar to Tsai (2011), we have derived an analytical expression for it, and evaluate it numerically based on our estimates for α and phase velocity. In out setup, its numerical values (Fig. 2) range between ~2.5 and. 3, and we infer that neglect of this factor would result in a significant underestimate of α. After establishing our theoretical approach, we formulate a non-linear inverse problem, with Rayleigh-wave dispersion and attenuation α as its unknown parameters. In practice, the dispersion curve is first inverted for through a robust method that bypasses amplitude information and only accounts for phase (Kaestle et al. , 2016), then a cost function based on our newly derived relationship between cross-correlation and α is defined and minimized. Ambient signal in the frequency range 0.05-0.5 Hz (2-20 s period) is inverted. Our inferred values of α are comparable to independently obtained estimates found in the literature. We find that allowing α to vary with respect to frequency results in a reduction of misfit between observed and predicted cross correlations. References Boschi, L., Magrini, F., Cammarano, F. & van der Meijde, M., 2019. On seismic ambient-noise cross correlation and surface-wave attenuation. Geophys. J. Int., 219 , 1568—1589. Boschi, L. & Weemstra, C., 2015. Stationary-phase integrals in the cross-correlation of ambient noise, Rev. Geophys., 53, doi:10.1002/2014RG000455. Cupillard, P. & Capdeville, Y., 2010. On the amplitude of surface waves ob-tained by noise correlation and the capability to recover the attenuation: a numerical approach, Geophys. J. Int., 181, 1687–1700. Harmon, N., Rychert, C. & Gerstoft, P., 2010. Distribution of noise sources for seismic interferometry, Geophys. J. Int., 183, 1470–1484. Kaestle, E., Soomro, R., Weemstra, C., Boschi, L. & Meier, T., 2016. Two-receiver measurements of phase velocity: cross-validation of ambient- noise and earthquake-based observations, Geophys. J. Int., 207, 1493– 1512. Lawrence, J.F. & Prieto, G.A., 2011. Attenuation tomography of the west- ern United States from ambient seismic noise, J. Geophys. Res., 116, doi:10.1029/2010JB007836. Prieto, G.A., Lawrence, J.F. & Beroza, G.C., 2009. Anelastic earth structure from the coherency of the ambient seismic field, J. Geophys. Res., 114, doi:10.1029/2008JB006067. Tsai, V.C., 2011. Understanding the amplitudes of noise correlation mea-surements, J. Geophys. Res., 116, doi:10.1029/2011JB008483. Weemstra, C., Boschi, L., Goertz, A. & Artman, B., 2013. Seis- mic attenuation from recordings of ambient noise, Geophysics, 78, Q1–Q14. Weemstra, C., Westra, W., Snieder, R. & Boschi, L., 2014. On estimating attenuation from the amplitude of the spectrally whitened ambient seismic field, Geophys. J. Int., 197, 1770–1788. LOBSTER - LIGURIAN OCEAN BOTTOM SEISMOLOGY AND TECTONICS RESEARCH A. Dannowski 1 , H. Kopp 1,2 , I. Grevemeyer 1 , D. Lange 1 , M.Thorwart 2 ,W. Crawford 3 , G. Caielli 4 , R. de Franco 4 , A. Paul 5 , F. Wolf 1 , F. Petersen 1 , B. Schramm 1 , the AlpArray Working Group 1 GEOMAR Helmholtz Centre for Ocean Research Kiel, Marine Geodynamics, Kiel, Germany 2 CAU, ChristianAlbrechtsUniversität zu Kiel, Germany 3 IPGP, Institut de Physique du Globe de Paris, Laboratoire de Géosciences Marines, Paris, France 4 IGAG-CNR, Istituto di Geologia Ambientale e Geoingenieria, Sezione di Milano, Milano, Italy 5 ISTerre, Institut des Sciences de la Terre, Université Grenoble, Grenoble, France Introduction. The LOBSTER project comprises the offshore component of the AlpArray seismic network using ocean bottom seismometers (OBS) to record teleseismic and local events in order to define subsurface structures at the transition from the Western Alps to the Apennines and to improve our understanding of the 3D-geometry of the system and its kinematics. The LOBSTER network consists of 23 OBS that recorded continuously over a period of 8 month