Analyzing earthquake clustering features by using stochastic reconstruction
Analyzing earthquake clustering features by using stochastic reconstruction
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DOI:
10.1029/2003jb002879
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发表时间:
2004-05-04
影响因子:
3.9
通讯作者:
Vere-Jones, D
中科院分区:
文献类型:
--
作者:
Zhuang, JC;Ogata, Y;Vere-Jones, D
[1] On the basis of the epidemic-type aftershock sequence ( ETAS) model and the thinning procedure, this paper gives the method about how to classify the earthquakes in a given catalogue into different clusters stochastically. The key points of this method are the probabilities of one event being triggered by another previous event and being a background event. Making use of these probabilities, we can reconstruct the functions associated with the characteristics of earthquake clusters to test a number of important hypotheses about the earthquake clustering phenomena. We applied this reconstruction method to the shallow seismic data in Japan and also to a simulated catalogue. The results show the following assertions: ( 1) The functions for each component in the formulation of the space-time ETAS model are good enough as a first-order approximation for describing earthquake clusters; ( 2) a background event triggers less offspring in expectation than a triggered event of the same magnitude; ( 3) the magnitude distribution of the triggered event depends on the magnitude of its direct ancestor; ( 4) the diffusion of the aftershock sequence is mainly caused by cascades of individual triggering processes, while no evidence shows that each individual triggering process is diffusive; and ( 5) the scale of the triggering region is still an exponential law, as formulated in the model but not the same one for the expected number of offspring.