Natural time analysis: On the deadly Mexico M8.2 earthquake on 7 September 2017

Sarlis, N. V.; Skordas, E. S.; Varotsos, P.; Ramírez-Rojas, Alejandro; Márquez, Elsa Leticia Flores

doi:10.1016/j.physa.2018.04.098

Cited by 46 publications

(59 citation statements)

References 39 publications

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“…the natural time count of small earthquakes after the last large earthquake in a defined, seismically active geographic region. Natural time has been discussed extensively in Varotsos et al (2004Varotsos et al ( , 2005Varotsos et al ( , 2006, Sarlis et al (2011Sarlis et al ( , 2018, Vallianatos et al (2012), and Holliday et al (2006).…”

Section: Reports: Methodsmentioning

confidence: 99%

Global Seismic Nowcasting With Shannon Information Entropy

Rundle

Giguere

Turcotte

et al. 2019

Earth and Space Science

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Seismic nowcasting uses counts of small earthquakes as proxy data to estimate the current dynamical state of an earthquake fault system . The result is an earthquake potential score that characterizes the current state of progress of a defined geographic region through its nominal earthquake “cycle.” The count of small earthquakes since the last large earthquake is the natural time that has elapsed since the last large earthquake (Varotsos et al., 2006, https://doi.org/10.1103/PhysRevE.74.021123 ). In addition to natural time, earthquake sequences can also be analyzed using Shannon information entropy (“information”), an idea that was pioneered by Shannon (1948, https://doi.org/10.1002/j.1538‐7305.1948.tb01338.x ). As a first step to add seismic information entropy into the nowcasting method, we incorporate magnitude information into the natural time counts by using event self‐information. We find in this first application of seismic information entropy that the earthquake potential score values are similar to the values using only natural time. However, other characteristics of earthquake sequences, including the interevent time intervals, or the departure of higher magnitude events from the magnitude‐frequency scaling line, may contain additional information.

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Section: Reports: Methodsmentioning

confidence: 99%

Global Seismic Nowcasting With Shannon Information Entropy

Rundle

Giguere

Turcotte

et al. 2019

Earth and Space Science

View full text Add to dashboard Cite

show abstract

“…Recent research suggests that these earthquakes should not be unexpected. An entropy change of seismicity under time reversal, considered as a non-seismic precursor of earthquakes, was identified several months before the occurrence of the major earthquake [34,35]. In this study, we developed a model of extreme values with censoring data for the earthquakes on the Pacific coast of southern Mexico using a robust and solidly-based theory.…”

Section: Resultsmentioning

confidence: 99%

Facing Missing Observations in Data—A New Approach for Estimating Strength of Earthquakes on the Pacific Coast of Southern Mexico Using Random Censoring

et al. 2019

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We introduced a novel spatial model based on the distribution of generalized extreme values (GEV) to analyze the maximum intensity levels of earthquakes with incomplete data (randomly censored) on the Pacific coast of southern Mexico using a random censorship approach. Spatiotemporal trends were modeled through a non-stationary GEV model. We used a multivariate smoothing function as a linear predictor of GEV parameters to approximate nonlinear trends. The model was fitted using a flexible semi-parametric Bayesian approach and the parameters are estimated via Markov chain Monte-Carlo (MCMC). Through a rigorous simulation study, we showed the robustness of both the model and the estimation method used. Maps of the location parameter on the spatial plane for different periods of time show the existence of local variations in the extreme values of seismicity in the study area. The results indicate strong evidence of an increase in the magnitude of earthquakes over time. A spatial map of risk with maximum intensity of earthquakes in a period of 25 years was elaborated.

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“…Following the two deadly 2017 earthquakes in Mexico (i.e., M8.2 on 7 September and M7.1 on 19 September) [2], there has been a debate on the "unusual cause" of these events [3][4][5]. However, what is less debatable is the fact that earthquakes occur at "unpredicted times in unpredicted places" [6].…”

Section: Unpredictability Of Earthquakesmentioning

confidence: 99%

Introductory Chapter: Earthquakes - Impact, Community Vulnerability, and Resilience

Santos‐Reyes¹

2019

Earthquakes - Impact, Community Vulnerability and Resilience

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Earthquakes may be regarded as one of the most devastating and terrifying natural forces on earth. Past earthquake disasters (including tsunamis triggered by earthquakes) have demonstrated that literally within a few or a fraction of seconds, many people can be killed or injured; further, the psychological impact on communities can last for years. Furthermore, due to its force of destruction, any physical infrastructure could be (and have been) damaged or destroyed. But what are the trends? In the UNISDR report [1], some of the key conclusions relevant to earthquakes during a 20-year period (i.e., 1998-2017) were the following (Figure 1):

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Natural time analysis: On the deadly Mexico M8.2 earthquake on 7 September 2017

Cited by 46 publications

References 39 publications

Global Seismic Nowcasting With Shannon Information Entropy

Global Seismic Nowcasting With Shannon Information Entropy

Facing Missing Observations in Data—A New Approach for Estimating Strength of Earthquakes on the Pacific Coast of Southern Mexico Using Random Censoring

Introductory Chapter: Earthquakes - Impact, Community Vulnerability, and Resilience

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