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Revised Accelerated Moment Release Under Test: Fourteen Worldwide Real Case Studies in 2014-2018 and Simulations

机译:经修订的加速时刻被测释放:2014 - 2018年全球真正案例研究和模拟

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Periods of accelerated seismicity have been observed during the preparation process of many large earthquakes. This accelerating seismicity can be detected by the Accelerated Moment Release (AMR) method and its recent Revised version (R-AMR) when the two techniques are applied to earthquake catalogues. The main aim of this study is to investigate the seismicity preceding large mainshocks and possibly increase our comprehension of the underlying physics. In particular, we applied both the AMR and R-AMR to the seismicity preceding 14 large worldwide shallow earthquakes, i.e. with focal depth less than 40 km, with magnitude M > 6 for Mediterranean area, and M >= 6.4 in the rest of the world, occurred from 2014 to 2018. Twelve case studies were analysed in the framework of SwArm For Earthquake study project funded by ESA, comprising the period 2014-2016; two additional cases were also considered to confirm the goodness of the methodology outside the period of the project catalogues. In total, R-AMR shows better performances than AMR, in 11 cases out of 14. In particular, in four out of 14 cases (i.e. 28.6%), the R-AMR method shows that acceleration exists due to an evident clustering in time-space on the faults, thus guiding the convergence of the fit; in seven cases (i.e. 50%) the R-AMR discloses acceleration, although no clustering around the fault is present; the remaining three cases (i.e. 21.4%) show no emerging acceleration from background. Finally, when R-AMR is compared with simulations, we verify that in most of the cases the acceleration is real and not casual.
机译:在许多大地震的制备过程中观察到加速地震性的时期。当两种技术应用于地震目录时,通过加速时刻释放(AMR)方法和其最近的修订版(R-AMR)可以检测到这种加速的地震性。本研究的主要目的是调查在大型主斯克的地震性,并且可能会增加我们对潜在物理学的理解。特别是,我们将AMR和R-AMR应用于14个大型全球浅地震的地震性,即焦距小于40公里,地中海地区的幅度为M> 6,其余部分世界,从2014年到2018年发生。在由ESA资助的地震研究项目框架中分析了12项案例研究,包括2014 - 2016年期间;还考虑了两种额外的案例,以确认项目目录期外的方法的善良。总共,R-AMR显示出比AMR更好的表现,在14个中的11例中,特别是在14例(即28.6%)中,R-AMR方法表明,由于时间明显的聚类,加速存在 - 空间在故障上,从而引导拟合的收敛;在七种情况下(即50%)R-AMR公开了加速,尽管存在故障周围的聚类;剩下的三种情况(即21.4%)显示了背景下的新兴加速度。最后,当R-AMR与仿真进行比较时,我们验证在大多数情况下,加速是真实的,而不是随意的。

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