Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability

Barani, Simone; Mascandola, Claudia; Riccomagno, Eva; Spallarossa, Daniele; Albarello, Dario; Ferretti, Gabriele; Scafidi, Davide; Augliera, P.; Massa, Marco

doi:10.1038/s41598-018-23709-4

Cited by 16 publications

(7 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A3 of the Appendix). Since D app is composed of the recordings of the 2016-2017 central Italy sequence, for which the earthquakes show spatial and temporal clustering (Barani et al 2017(Barani et al , 2018, the actual temporal order of occurrence of the recordings could show a large path-correlation among elements close located in the temporal From top to bottom: model calibrated in this study considering δP2S, without considering δP2S, model of (Caruso et al 2017), model of (Wu et al 2007) and model of (Zollo et al 2010). The mean residual is indicated by the red vertical line, and the normal distributions with mean and standard deviation computed from each histogram are shown in black.…”

Section: A P P L I C At I O N T O N E W E a Rt H Q Ua K E S A N D S Tmentioning

confidence: 99%

On-site earthquake early warning: a partially non-ergodic perspective from the site effects point of view

Spallarossa

Kotha

Picozzi

et al. 2018

Geophysical Journal International

View full text Add to dashboard Cite

We introduce in the on-site earthquake early warning (EEW) a partially non-ergodic perspective from the site effects point of view. We consider the on-site EEW approach where the peak ground velocity (PGV) for S waves is predicted from an early estimate, over the P waves, of either the peak-displacement (PD) or cumulative squared velocity (IV2). The empirical PD-PGV and IV2-PGV relationships are developed by applying a mixed-effect regression where the site-specific modifications of ground shaking are treated as random effects. We considered a large data set composed of almost 31 000 selected recordings in central Italy, a region struck by four earthquakes with magnitude between 6 and 6.5 since the 2009 L'Aquila earthquake. We split the data set into three subsets used for calibrating and validating the on-site EEW models, and for exemplifying their application to stations installed after the calibration phase. We show that the partially non-ergodic models improve the accuracy of the PGV predictions with respect to ergodic models derived for other regions of the world. Moreover, considering PD and accounting for site effects, we reduce the (apparent) aleatory variability of the logarithm of PGV from 0.31 to 0.36, typical values for ergodic on-site EEW models, to about 0.25. Interestingly, a lower variability of 0.15 is obtained by considering IV2 as proxy, which suggests further consideration of this parameter for the design of on-site EEW systems. Since being site-specific is an inherent characteristic of on-site EEW applications, the improved accuracy and precision of the PGV predicted for a target protection translate in a better customization of the alert protocols for automatic actions.

show abstract

Section: A P P L I C At I O N T O N E W E a Rt H Q Ua K E S A N D S Tmentioning

confidence: 99%

On-site earthquake early warning: a partially non-ergodic perspective from the site effects point of view

Spallarossa

Kotha

Picozzi

et al. 2018

Geophysical Journal International

View full text Add to dashboard Cite

show abstract

“…The Hurst exponent H is a measure of the secular memory of a time series. It has been widely used in the study of many natural phenomena, such as geology (Barani et al 2018), geomagnetism (Wanliss & Reynolds 2003), solar activity (Oliver & Ballester 1996;Lepreti et al 2000;Zhou et al 2014), and so on. A value of H = 0.5 indicates that the behavior of the time series corresponds to a stochastic process with no memory.…”

Section: Introductionmentioning

confidence: 99%

Repeating Fast Radio Bursts Reveal Memory from Minutes to an Hour

Wang

Dai

2023

ApJL

View full text Add to dashboard Cite

Fast radio bursts (FRBs) are brief, luminous pulses with unknown physical origin. The repetition pattern of FRBs contains essential information about their physical nature and emission mechanisms. Using the two largest samples of FRB 20121102 and FRB 20201124A, we report that the sources of the two FRBs reveal memory over a large range of timescales, from a few minutes to about an hour. The memory is detected from the coherent growths in burst-rate structures and the Hurst exponent. The waiting time distribution displays an approximate power-law tail, which is consistent with a Poisson model with a time-varying rate. From cellular automaton simulations, we find that these characteristics can be well understood within the physical framework of a self-organized criticality system driven in a correlation way, such as random walk functions. These properties indicate that the triggers of bursts are correlated, preferring the crustal failure mechanism of neutron stars.

show abstract

“…The Hurst exponent H is a measure of the secular memory of a time series. It has been widely used in the study of the memory of many natural phenomena, such as geology (Barani et al 2018), geomagnetism (Wanliss & Reynolds 2003), solar activity (Oliver & Ballester 1996;Lepreti et al 2000;Zhou et al 2014) and so on. A value of H = 0.5 indicates that the behavior of the time series corresponds to a stochastic process with no memory.…”

Section: Introductionmentioning

confidence: 99%

Repeating fast radio bursts reveal memory from minutes to an hour

Wang¹,

Wu²,

Dai³

2023

Preprint

View full text Add to dashboard Cite

Fast radio bursts (FRBs) are brief, luminous pulses with unknown physical origin. The repetition pattern of FRBs contains essential information about their physical nature and emission mechanisms. Using the two largest samples of FRB 20121102A and FRB 20201124, we report that the sources of the two FRBs reveal memory over a large range of timescales, from a few minutes to about an hour. This suggests that bright bursts are very likely to be followed by bursts of similar or larger magnitude, allowing for the prediction of intense bursts. The memory is detected from the coherent growths in burst-rate structures and the Hurst exponent. The waiting time distribution displays a power-law tail, which is consistent with a Poisson model with a time-varying rate. From cellular automaton simulations, we find that these characteristics can be well understood within the physical framework of a self-organized criticality system driven in a correlation way, such as random walk functions. These properties indicate that the triggers of bursts are correlated, preferring the crustal failure mechanism of neutron stars.

show abstract

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability

Cited by 16 publications

References 51 publications

On-site earthquake early warning: a partially non-ergodic perspective from the site effects point of view

On-site earthquake early warning: a partially non-ergodic perspective from the site effects point of view

Repeating Fast Radio Bursts Reveal Memory from Minutes to an Hour

Repeating fast radio bursts reveal memory from minutes to an hour

Contact Info

Product

Resources

About