Synchronization of atmospheric indicators at the last stage of earthquake preparation cycle

Пулинец, С. А.; Morozova, L. I.; Yudin, Ilya A.

doi:10.4081/rg.2014.4898

Cited by 14 publications

(11 citation statements)

References 12 publications

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“…These differences in lead times can be acknowledged using a robust earthquake precursor's mechanism. Hypotheses exist on the seismo-lithospheric, atmospheric and ionospheric mechanisms based on geophysical and geochemical processes (Qiang et al, 1991;Freund, 2009;Pulinets and Ouzounov, 2011;Pulinets et al, 2014). However none of them have been accepted among the majority of the seismologists.…”

Section: Discussionmentioning

confidence: 97%

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Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

Akhoondzadeh

2015

Advances in Space Research

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Section: Discussionmentioning

confidence: 97%

“…There are scientific reports investigating aerosols variations to detect the abnormal behaviors around the time of the some large earthquakes using ground stations such as Aeronets (Pulinets and Ouzounov, 2011;Pulinets et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

Akhoondzadeh

2015

Advances in Space Research

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“…The model described in [26] is related to atmospheric changes due to air ionization by radon, water molecules attachment to these ions, and at the end, a heat increase. More generally, these phenomena are associated to the so-called Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) described for example in [28] [32], and to the change in the global electric circuit which exists between the Earth's surface and the bottom of the ionosphere at the time of earthquakes [33] [34].…”

Section: Discussionmentioning

confidence: 99%

Is There an Earthquake Weather?

Parrot¹,

Pinçon²

2020

OJER

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The aim of this study is to check if there is a relationship between the seismic activity and the whistlers observed by the micro-satellite DEMETER. Whistlers are the waves emitted by lightning strokes during thunderstorm activity. They use to propagate in the Earth-ionosphere waveguide but also in the ionosphere and the magnetosphere mainly along the magnetic field lines. Due to this reason we have checked the whistler occurrence not close to earthquake epicenters but close to the magnetically conjugate point of these epicenters at the satellite altitude. The number of whistlers is given by a neural network in operation onboard the satellite. It appears that the whistler amplitude is attenuated at the satellite altitude around the magnetic equator. It is why we have removed the earthquakes occurring at low geomagnetic latitudes in the statistic. The whistler rate is normalized with a background value to take into account the seasons and the epicenter locations. A superposed epoch method is used to display the results between −15 and +5 days around the earthquake day and up to 1000 km from the conjugate point of the epicenters. It is shown that the whistler rate is higher the day before the earthquake at a distance less than 200 km. It would be unrealistic to believe in the possibility to use this study for earthquake prediction because everyday thunderstorm activity reliably masks seismic effects. But it is further evidence that there is a lithosphere-atmosphere-ionosphere coupling at the time of the seismic activity.

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“…In published research, the spatial extent of detected anomalies is often not clear. For example, Akhoondzadeh et al [7,19] and Pulinets et al [59] study the 6.4 Mw earthquake of Ahar, NW Iran (2012) using data from meteorological stations. Such data have very limited spatial cover and cannot describe the full extent of detected anomalies.…”

Section: Spatial Extent Of Anomaliesmentioning

confidence: 99%

Time Series Analysis of Land Surface Temperatures in 20 Earthquake Cases Worldwide

et al. 2018

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Earthquakes are reported to be preceded by anomalous increases in satellite-recorded thermal emissions, but published results are often contradicting and/or limited to short periods and areas around the earthquake. We apply a methodology that allows to detect subtle, localized spatio-temporal fluctuations in hyper-temporal, geostationary-based land surface temperature (LST) data. We study 10 areas worldwide, covering 20 large (Mw > 5.5) and shallow (<35 km) land-based earthquakes. We compare years and locations with and without earthquake, and we statistically evaluate our findings with respect to distance from epicentra and temporal coincidence with earthquakes. We detect anomalies throughout the duration of all datasets, at various distances from the earthquake, and in years with and without earthquake alike. We find no distinct repeated patterns in the case of earthquakes that happen in the same region in different years. We conclude that earthquakes do not have a significant effect on detected LST anomalies.Remote Sens. 2019, 11, 61 2 of 25 in [25]). Furthermore, anomalies are often found to relate to atmospheric influences and artefacts due to data processing [26].The objective of this study is to make use of the advantages provided by geostationary-based LST data and of a recently published methodological approach, in order to examine the presence of thermal anomalies shortly before large, shallow, land-based earthquakes. We consider that an earthquake is large when it has magnitude larger than Mw 5.5 and that an earthquake is shallow when it has focal depth <35 km. We study 20 earthquake cases in 10 study areas around the world, with different local environmental and climatic conditions. We apply a methodology which suppresses large-scale patterns in the satellite signal time series and isolates only spatially localized fluctuations [27]. This methodology allows to constrain the spatial extent of detected anomalies and the time of their occurrence. Thermal anomalies may appear for a variety of reasons other than earthquakes, including spatiotemporal variations of surface spectral emissivity [28] and local atmospheric conditions, like atmospheric inversions [29]. We therefore test the hypothesis that more anomalies would be detected at closer distances to the earthquake, shortly prior or during the earthquake, and only in years with earthquake occurrence. This hypothesis is supported by published research [30], concluding that anomalies increase with increasing earthquake magnitude; anomalies are found predominantly near the epicenter, one day before and on the day of the earthquake; and anomalies are more easily observed during shallow earthquakes than the deep ones. We statistically evaluate our findings, taking into account the spatial and temporal occurrence of detected anomalies and earthquakes. Materials and Methods Input DataResearch suggests that the use of satellite-derived land surface temperature (LST) data can provide significant advantages in this field of study [6,31,32]. LST products are esti...

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Synchronization of atmospheric indicators at the last stage of earthquake preparation cycle

Abstract: We consider the dynamics of different parameters in the boundary layer of atmosphere and low level cloud structure around the time of three recent moderate and strong earthquakes: Virginia M 5.8 earthquake on

Cited by 14 publications

References 12 publications

Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

Is There an Earthquake Weather?

Time Series Analysis of Land Surface Temperatures in 20 Earthquake Cases Worldwide

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