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Cumulative rate analysis (CURATE): A clustering algorithm for swarm dominated catalogs
Author(s) -
Jacobs Katrina M.,
Smith Euan G. C.,
Savage Martha K.,
Zhuang Jiangcang
Publication year - 2013
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2012jb009222
Subject(s) - cluster analysis , sequence (biology) , aftershock , poisson distribution , swarm behaviour , computer science , selection (genetic algorithm) , seismology , data mining , statistics , mathematics , geology , artificial intelligence , biology , genetics
We present a new cumulative rate (CURATE) clustering method to identify earthquake sequences especially in regions with swarm activity. The method identifies sequences by comparing observed rates to an average rate. It is distinct from previous clustering techniques in that no direct assumptions about physical processes relating to temporal decay or earthquake‐earthquake interaction are made. Instead these assumptions are replaced by a more general one, that earthquakes occurring within a sequence likely share a common physical trigger, which is manifested by a change in rate. The use of rate as the primary selection parameter emphasizes that temporal proximity is the main commonality among different sequence types. To investigate catalog‐scale earthquake sequence characteristics, we apply the method along with four standard (de‐)clustering methods to a catalog of 4845 M ≥ 2.45 earthquakes from 1993 through 2007 in the Central Volcanic Region of New Zealand. Despite the distinct focus of the method on sequence formation, the declustered catalog of the CURATE method sits within the suite of declustered catalogs produced by other methods. A stochastic reconstruction based on epidemic‐type aftershock sequence parameters is also presented to test the differences between catalogs that exclusively contain mainshock‐aftershock sequences and areas that exhibit multiple physical processes. We test the declustered catalogs produced by all methods for a Poisson temporal distribution and propose that this be used to ensure reasonable selection parameters. The CURATE method will be especially useful for identifying swarms, creating likelihoods of the size and duration of sequences, and refining earthquake forecasts that include swarms at regional and local scales.

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