Scaling behaviour in temporal fluctuations of crustal seismicity in Taiwan

Telesca, Luciano; Chen, C.-C.; Lee, Y.-T.

doi:10.5194/nhess-9-2067-2009

Cited by 13 publications

(30 citation statements)

References 20 publications

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“…Due to the nonlinear and non-stationary nature of seismicity, the conventional Fourier power spectra could be contaminated by, for example, a large number of aftershocks (Telesca et al, 2009) and thus may not be appropriate for investigating the effect of tidal triggering. The occurrence of large earthquakes and their aftershocks can obviously increase the number of daily earthquakes, thus producing spikes in the time series (Fig.…”

Section: Discussionmentioning

confidence: 99%

Effect of tidal triggering on seismicity in Taiwan revealed by the empirical mode decomposition method

Chen

Tseng

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. The effect of tidal triggering on earthquake occurrence has been controversial for many years. This study considered earthquakes that occurred near Taiwan between 1973 and 2008. Because earthquake data are nonlinear and non-stationary, we applied the empirical mode decomposition (EMD) method to analyze the temporal variations in the number of daily earthquakes to investigate the effect of tidal triggering. We compared the results obtained from the nondeclustered catalog with those from two kinds of declustered catalogs and discuss the aftershock effect on the EMD-based analysis. We also investigated stacking the data based on inphase phenomena of theoretical Earth tides with statistical significance tests. Our results show that the effects of tidal triggering, particularly the lunar tidal effect, can be extracted from the raw seismicity data using the approach proposed here. Our results suggest that the lunar tidal force is likely a factor in the triggering of earthquakes.

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Section: Discussionmentioning

confidence: 99%

Effect of tidal triggering on seismicity in Taiwan revealed by the empirical mode decomposition method

Chen

Tseng

et al. 2012

Nat. Hazards Earth Syst. Sci.

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“…Earthquake sequencing may be considered a non-linear and non-stationary process (Kanamori, 2003;Telesca et al, 2001Telesca et al, , 2009Telesca et al, , 2011Telesca and Lovallo, 2008;FloresMarquez and Valverde-Esparza, 2012). In earthquake sequencing, earthquakes are viewed as part of a point process, with earthquake events occurring at some random locations in time.…”

Section: S Cavers and K Vasudevan: Earthquake Sequencing: Analysmentioning

confidence: 99%

“…This means that the earthquake sequencing is dictated by the set of event times, and can also be expressed by the set of time intervals between events. The time series of earthquakes for any time interval can be analysed in many ways (Bohnenstiehl et al, 2001;Telesca et al, 2001Telesca et al, , 2009Telesca et al, , 2011Telesca and Lovallo, 2008).…”

Section: S Cavers and K Vasudevan: Earthquake Sequencing: Analysmentioning

confidence: 99%

“…Earthquake sequencing has been the subject of detailed research (Nava et al, 2005;Ünal and Çelebioglu, 2011;Ünal et al, 2014;Telesca et al, 2001Telesca et al, , 2009Telesca et al, , 2011Telesca and Lovallo, 2008;Vasudevan, 2013, 2015;Cavers, 2012, 2013) both in the regional and global sense in recent years. Nava et al (2005) have introduced the Markov chain model to study the earthquake sequencing in a seismogenically active region where the region is partitioned into zones.…”

Section: Introductionmentioning

confidence: 99%

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Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model

Cavers

Vasudevan

2015

Nonlin. Processes Geophys.

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Abstract. Directed graph representation of a Markov chain model to study global earthquake sequencing leads to a time series of state-to-state transition probabilities that includes the spatio-temporally linked recurrent events in the recordbreaking sense. A state refers to a configuration comprised of zones with either the occurrence or non-occurrence of an earthquake in each zone in a pre-determined time interval. Since the time series is derived from non-linear and nonstationary earthquake sequencing, we use known analysis methods to glean new information. We apply decomposition procedures such as ensemble empirical mode decomposition (EEMD) to study the state-to-state fluctuations in each of the intrinsic mode functions. We subject the intrinsic mode functions, derived from the time series using the EEMD, to a detailed analysis to draw information content of the time series. Also, we investigate the influence of random noise on the data-driven state-to-state transition probabilities. We consider a second aspect of earthquake sequencing that is closely tied to its time-correlative behaviour. Here, we extend the Fano factor and Allan factor analysis to the time series of state-to-state transition frequencies of a Markov chain. Our results support not only the usefulness of the intrinsic mode functions in understanding the time series but also the presence of power-law behaviour exemplified by the Fano factor and the Allan factor.

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“…A clusterized process qualifies earthquakes that at both short and long timescales are correlated with each other, and whose density varies over time featuring the whole sequence as an ensemble of clusters (Telesca et al, 2000). Clusterization in seismic sequences was investigated at regional and local levels (Telesca et al, 2001(Telesca et al, , 2009, and was used to reveal a nontrivial relationship with hypocentral depth (Telesca et al, 2001) and to identify spatial (Telesca et al, 2003) and temporal patterns (Telesca et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Temporal clustering of the seismicity of the Absheron-Prebalkhan region in the Caspian Sea area

Telesca

Babayev

Kadirov

2012

Nat. Hazards Earth Syst. Sci.

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Abstract. The historical and instrumental catalog of the Absheron-Prebalkhan region in the Caspian Sea area was analyzed in order to reveal the existence of temporal clustering in the time dynamics of the seismicity. The timespan of the catalog is from 1842 to 2012 and the magnitude of the events ranges from 2.5 to 6.8. The Gutenberg-Richter analysis indicates 4.0 as the completeness magnitude of the catalog. The temporal clustering analysis was performed over the sequence of events with magnitude M ≥ 4 by using the methods of the Allan Factor and the coefficient of variation. Both the methods have revealed the presence of timeclusterized structures in the time dynamics of large events in the Absheron-Prebalkhan region. Such findings, which suggest a non-Poissonian behavior of the seismicity of the investigated area, could contribute to a deeper knowledge of the time dynamics of the seismicity and to a better assessment of the relative seismic hazard.

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Scaling behaviour in temporal fluctuations of crustal seismicity in Taiwan

Cited by 13 publications

References 20 publications

Effect of tidal triggering on seismicity in Taiwan revealed by the empirical mode decomposition method

Effect of tidal triggering on seismicity in Taiwan revealed by the empirical mode decomposition method

Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model

Temporal clustering of the seismicity of the Absheron-Prebalkhan region in the Caspian Sea area

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