A merged, high-quality waveform dataset from different seismic networks has been used to improve our understanding of lateral seismic attenuation for Northern Italy. In a previous study on the same region, Morasca et al. (Bull Seismol Soc Am 98: 1936-1946, 2008) were able to resolve only a small area due to limited data coverage. For this reason, the interpretation of the attenuation anomalies was difficult given the complexity of the region and the poor resolution of the available data. In order to better understand the lateral changes in the crustal structure and thickness of this region, we selected 770 earthquakes recorded by 54 stations for a total of almost 16,000 waveforms derived from seismic networks operating totally or partially in Northern Italy. Direct S-wave and coda attenuation images were obtained using an amplitude ratio technique that eliminates source terms from the formulation. Both direct and early-coda amplitudes are used as input for the inversions, and the results are compared. Results were obtained for various frequency bands ranging between 0.3 and 25.0 Hz and in all cases show significant improvement with respect to the previous study since the resolved area has been extended and more crossing paths have been used to image smaller scale anomalies. Quality-factor estimates are consistent with the regional tectonic structure exhibiting a general trend of low attenuation under the Po Plain basin and higher values for the Western Alps and Northern Apennines. The interpretation of the results for the Eastern Alps is not simple, possibly because our resolution for this area is still not adequate to resolve small-scale structures.
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China Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
Zhejiang Streamrail Intelligent Control Technol Co, Jiaxing 314001, Peoples R ChinaChina Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
Wang, Qinxia
Qiu, Yue
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China Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R ChinaChina Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
Qiu, Yue
Qu, Weiqiang
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Zhejiang Streamrail Intelligent Control Technol Co, Jiaxing 314001, Peoples R China
Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Peoples R ChinaChina Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
Qu, Weiqiang
Wang, Dianhui
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China Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R ChinaChina Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China