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Nowcasting Earthquakes in Southern California With Machine Learning: Bursts, Swarms, and Aftershocks May Be Related to Levels of Regional Tectonic Stress
Earth and Space Science ( IF 3.1 ) Pub Date : 2020-09-16 , DOI: 10.1029/2020ea001097
John B. Rundle 1, 2, 3 , Andrea Donnellan 4
Affiliation  

Seismic bursts in Southern California are sequences of small earthquakes strongly clustered in space and time and include seismic swarms and aftershock sequences. A readily observable property of these events, the radius of gyration (RG), allows us to connect the bursts to the temporal occurrence of the largest M ≥ 7 earthquakes in California since 1984. In the Southern California earthquake catalog, we identify hundreds of these potentially coherent space‐time structures in a region defined by a circle of radius 600 km around Los Angeles. We compute RG for each cluster then filter them to identify those bursts with large numbers of events closely clustered in space, which we call “compact” bursts. Our basic assumption is that these compact bursts reflect the dynamics associated with large earthquakes. Once we have filtered the burst catalog, we apply an exponential moving average to construct a time series for the Southern California region. We observe that the RG of these bursts systematically decreases prior to large earthquakes, in a process that we might term “radial localization.” The RG then rapidly increases during an aftershock sequence, and a new cycle of “radial localization” then begins. These time series display cycles of recharge and discharge reminiscent of seismic stress accumulation and release in the elastic rebound process. The complex burst dynamics we observe are evidently a property of the region as a whole, rather than being associated with individual faults. This new method allows us to improve earthquake nowcasting, which is a technique to evaluate the current state of hazard in a seismically active region.

中文翻译:

借助机器学习在南加利福尼亚州临近预报地震:爆发,爆炸和余震可能与区域构造应力水平有关

南加州的地震爆发是在时空上强烈聚集的小地震序列,包括地震群和余震序列。这些事件的容易观察到的财产,回转半径([R g ^),可以让我们的阵阵连接到最大的时间发生中号 ≥在加州地震7自1984年以来在南加州地震目录,我们确定数百这些潜在的时空结构位于洛杉矶周围半径为600 km的圆所定义的区域中。我们计算R G对于每个聚类,然后对其进行过滤,以识别具有大量紧密聚集在空间中的事件的突发,我们称之为“紧凑”突发。我们的基本假设是,这些紧凑的爆发反映了与大地震有关的动力学。过滤了突发目录后,我们将使用指数移动平均值来构建南加州地区的时间序列。我们观察到,在大地震之前,这些爆发的R G会系统地减小,这一过程可以称为“径向定位”。的ř ģ然后在余震序列中迅速增加,然后开始一个新的“径向定位”周期。这些时间序列显示的充放电循环使人想起了弹性回弹过程中地震应力的累积和释放。我们观察到的复杂的爆发动力学显然是整个区域的一个属性,而不是与单个断层有关。这种新方法使我们能够改进地震临近预报,这是一种评估地震活跃地区当前灾害状态的技术。
更新日期:2020-09-16
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