Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/16038
Authors: Artale Harris, Pietro* 
Scognamiglio, Laura* 
Magnoni, Federica* 
Casarotti, Emanuele* 
Tinti, Elisa* 
Title: Centroid Moment Tensor Catalog With 3D Lithospheric Wave Speed Model: The 2016–2017 Central Apennines Sequence
Journal: Journal of Geophysical Research: Solid Earth 
Series/Report no.: /127 (2022)
Publisher: Wiley-AGU
Issue Date: 2022
DOI: 10.1029/2021JB023068
Abstract: Moment tensor inversions of broadband velocity data are usually managed by adopting Green's functions for 1D layered seismic wave speed models. This assumption can impact on source parameter estimates in regions with complex 3D heterogeneous structures and discontinuities in rock properties. In this work, we present a new centroid moment tensor (CMT) catalog for the Amatrice-Visso-Norcia (AVN) seismic sequence based on a recently generated 3D wave speed model for the Italian lithosphere. Forward synthetic seismograms and Fréchet derivatives for CMT-3D inversions of 159 earthquakes with Mw ≥ 3.0 are simulated using a spectral-element method (SEM) code. By comparing the retrieved solutions with those from time domain moment tensor (TDMT) catalog, obtained with a 1D wave speed model calibrated for Central Apennines (Italy), we observe a remarkable degree of consistency in terms of source geometry, kinematics, and magnitude. Significant differences are found in centroid depths, which are more accurately estimated using the 3D model. Finally, we present a newly designed parameter, τ, to better quantify and compare a-posteriori the reliability of the obtained MT solutions. τ measures the goodness of fit between observed and synthetic seismograms accounting for differences in amplitude, arrival time, percentage of fitted seconds, and the usual L2-norm estimate. The CMT-3D solutions represent the first Italian CMT catalog based on a full-waveform 3D wave speed model. They provide reliable source parameters with potential implications for the structures activated during the sequence. The developed approach can be readily applied to more complex Italian regions where 1D models are underperforming and not representative of the area.
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