Constraining the focal mechanism of the Lushan earthquake with observations of the Earth’s free oscillations

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• 作者：Ying Jiang ; XiaoGang Hu ; ChengLi Liu ; HePing Sun
• 关键词：Lushan earthquake ; focal mechanism solutions ; Earth’s free oscillations ; superconductive gravimeter observations ; broadband seismograph observations
• 刊名：Science China Earth Sciences
• 出版年：2014
• 出版时间：September 2014
• 年：2014
• 卷：57
• 期：9
• 页码：2064-2070
• 全文大小：1,334 KB
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• 作者单位：Ying Jiang (1) (2)
  XiaoGang Hu (1)
  ChengLi Liu (1) (2)
  HePing Sun (1)
  
  1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, 430077, China
  2. University of Chinese Academy of Sciences, Beijing, 100049, China
  
• ISSN：1869-1897

文摘

The amplitudes of the Earth’s free oscillations have a close relationship to earthquake focal mechanisms. Focal mechanisms of large earthquakes can be well analyzed and constrained with observations of long period free oscillations. Although the 2013 Lushan earthquake was only moderately sized, observable spherical normal modes were excited and clearly observed by a superconductive gravimeter and a broadband seismometer. We compare observed free oscillations with synthetic normal modes corresponding to four different focal mechanisms for the Lushan earthquake. The results show that source parameters can be analyzed and constrained by spherical normal modes in a 2.3- mHz frequency band. The scalar seismic moment M 0 has a major influence on the amplitudes of free oscillations; additionally, the strike, dip, rake and depth of the hypocenter have minor influences. We found that the synthetic modes corresponding to the focal mechanism determined by the Global Centroid Moment Tensor show agreement to the observed modes, suggesting that earthquake magnitudes predicted in this way can readily reflect the total energy released by the earthquake. The scalar seismic moment obtained by far-field body wave inversion is significantly underestimated. Focal mechanism solutions can be improved by joint inversion of far- and near-field data.