Special case of ionospheric day-to-day variability associated with earthquake preparation

doi:10.1016/j.asr.2006.04.032

Advances in Space Research

Volume 39, Issue 5, 2007, Pages 970-977

https://doi.org/10.1016/j.asr.2006.04.032 Get rights and content

Abstract

The problem of ionospheric variability is regarded from the point of view of spatial and temporal correlations between the GPS TEC variations derived from the neighboring GPS receiver records. It is demonstrated that the technique of the spatial correlation coefficient developed earlier to reveal the ionospheric variations induced by seismic activity sometimes is not very reliable. The new index of the local ionospheric variability is proposed describing the spread of GPS TEC within the given area. It is tested for periods of geomagnetic disturbances and periods of several days preceding the strong (M ⩾ 6) earthquakes occuring within the area of GPS receiver’s network. It is shown that the new index is a promising indicator of the earthquake preparation process, it increases few (5–10) days before the seismic shocks and comes back to normal state after the earthquake. During the periods of increased geomagnetic activity the index does not show such variability.

Introduction

Day-to-day ionospheric variability still remains among the subjects of the ionospheric physics which are not studied thoroughly enough. Attempts to classify the terminology of ionospheric variability can be found in the review of Bradley and Cander (2002). Usually the variability is expressed as a deviation (in %) from the mean or median value. The quantitative estimations of the ionosphere variability are given in the papers of Forbes et al., 2000, Rishbeth and Mendillo, 2001, Mendillo et al., 2002 showing that day-to-day variability of the critical frequency foF2 lies within the limits 10–30%.

The effect on the ionosphere from below is regarded as a main source of the day-to-day variability and it is demonstrated in the reviews of Kazimirovski, 2002, Kazimirovsky et al., 2003. Pulinets (1998) proposed the effects of seismic activity through the electromagnetic coupling with the ionosphere as one of the sources of the ionospheric variability. The detailed aspects of the physical mechanism and main morphological features of the ionospheric variability associated with seismic activity are described in Pulinets and Boyarchuk (2004).

In modern applications (for example, navigation with GPS system), the correlation radius of the ionosphere is a very important parameter (Hansen et al., 2001). But the correlation model developed by Hansen et al. does not take into account the nature of the ionosphere variability source. The present paper intends to demonstrate that the ionospheric variability character is different for different sources of this variability.

Section snippets

The correlation index

The idea to use the correlation between the neighbor ionospheric stations to reveal the seismogenic variations in sporadic E-layer of the ionosphere was proposed by Liperovskaya et al. (1994) and reviewed in Liperovsky et al. (2000). The similar technique for the F-layer parameters of the ionosphere was developed by Gaivoronskaya and Pulinets (2002). This technique was extended for the GPS TEC measurements (Pulinets et al., 2004a). To determine the radius of correlation associated with the

Spatial distribution complications

The correlation technique was developed for the seismic areas where not too many geophysical equipments were installed. It permits, regardless the poor instrumentation, to obtain quite reliable results on the earthquake precursors. Of course, in Japan or California where the GPS receiver’s density is very high, the mapping is the optimal instrument for the monitoring of precursory activity in the ionosphere.

Why the correlation technique may fail. Because it implies the circle-like distribution

Regional variability index

The 2D GPS TEC distribution in the form of map may not be very reliable because of the possible constant bias of some stations in relation to another, which can introduce the errors in absolute GPS TEC maps. We found the following way to describe the variability within the area of analysis: the special index of variability was introduced as the difference between the maximal and minimum values of TEC for every given moment for all the stations under our study and calculated for the time of the

Discussion

For every earthquake from the presented four cases one can observe the enhancement of regional variability of the ionosphere (in vertical TEC) starting 10–5 days before the seismic shock. The index demonstrates the tendency to spread the TEC over the area few hundred kilometers in diameter. Usually, the receivers register very similar data (with the spread not exceeding few TEC units). In the considered cases the spread reached the value up to 40 TEC units. The smaller value of the variability

Conclusion

Three different techniques for determination of the ionosphere variability over the area of the earthquake preparation were developed: cross-correlation analysis, regional mapping, and regional variability index. We argued the possibility of failure of the first-mentioned techniques because of the complex spatial distribution of the electron concentration over the area of the earthquake preparation within the time interval of seismically induced variability. The proposed variability index shows

Acknowledgements

This work was supported by the grants of PAPIIT IN 126002 and CONACYT 40858-F. The authors thank the Mexican National Institute of Statistics, Geography and Informatics (INEGI) for providing GPS data.

References (15)

J.M. Forbes et al.
Variability of the ionosphere
J. Atm. Sol.-Ter. Phys.
(2000)
M. Mendillo et al.
Modelling F2-layer seasonal trends and day-to-day variability driven by coupling with the lower atmosphere
J. Atm. Sol.-Ter. Phys.
(2002)
S.A. Pulinets
Seismic activity as a source of the ionospheric variability
Adv. Space Res.
(1998)
H. Rishbeth et al.
Patterns of ionospheric variability
J. Atm. Sol.-Ter. Phys.
(2001)
P.A. Bradley et al.
Proposed terminology for the classification and parameters for the quantification of variability in ionosphere morphology
Ann. Geophys.
(2002)
I.R. Dobrovolsky et al.
Estimation of the size of earthquake preparation zones
Pure Appl. Geophys.
(1979)
Gaivoronskaya, T.V., Pulinets, S.A., Analysis of the F2-layer variability in the areas of seismic activity, Preprint...

There are more references available in the full text version of this article.

Cited by (65)

Probing the upper atmosphere using GPS
2021, GPS and GNSS Technology in Geosciences
The Global Positioning System satellites provide an extensive array of beacon signals at L-band frequencies (1.2 and 1.6 GHz), which are used for satellite-based navigation, communication, and ground positioning. Before being received at the ground, these signals have to pass through the ionosphere. The ionosphere is a dispersive medium, whose variability affects the quality of the received signal, and is a matter of grave concern for civilian as well as military applications that rely on these signals. The ionospheric plasma density drastically changes during various solar (solar flare, corona mass ejection), astronomical (solar eclipse), and seismological (earthquake) phenomena. Understanding these processes is of great scientific value and has practical benefits in satellite-based communication and navigation. In this chapter, a brief overview on ionospheric weather and outcomes of studies on solar, astronomical, and terrestrial phenomena employed worldwide is discussed.
Detection of the ionospheric disturbances on GPS-TEC using Differential Rate Of TEC (DROT) algorithm
2020, Advances in Space Research
Citation Excerpt :
These vertical TEC enhancements lasted longer than the duration of the EUV emission. Recent studies in the literature have shown that seismic waves can couple to the atmosphere (Karatay et al., 2010; Pulinets et al., 2005, 2007; Liu et al., 2004; Chen et al., 2004). The earthquake precursors can be observed a few hundred kilometers of the epicenter of the earthquake occurred up to a few days later.
The solar, geomagnetic, gravitational and seismic activities can cause spatial and temporal (hourly, diurnal, seasonal and annual) variabilities of the ionosphere. Main observable ionospheric parameters such as Total Electron Content (TEC) can be used to quantify these. TEC is the total number of electrons on a ray path crossing the atmosphere. The network of world-wide Global Positioning System (GPS) receivers provide a cost-effective solution in estimating TEC over a significant proportion of global land mass. This study is focused on the analysis of the variations of ionosphere over a midlatitude region using GPS-TEC estimates for three Sun Spot Numbers (SSN) periods. The investigation is based on a fast and automatic variability detection algorithm, Differential Rate Of TEC (DROT). The algorithm is tested using literature data on disturbances generated by a geomagnetic activity, a Solar Flare, a Medium Scale Travelling Ionospheric Disturbance (MSTID), a Large Scale TID (LSTID) and an earthquake. Very good agreement with the results in the literature is found. DROT is applied to IONOLAB-TEC estimates from nine Turkish National Permanent GPS Network (TNPGN Active) stations over Turkey to detect the any wave-like oscillations, sudden disturbances and other irregularities during December, March, June, September months for 2010, 2011, 2012 years. It is observed that DROT algorithm is capable of detecting both small and large scale variability due to climatic, gravitational, geomagnetic and solar activities in all layers of ionosphere. The highest DROT values are observed in 2010 during winter months. In higher solar activity years of 2011 and 2012, DROT is able to indicate both seasonal variability and severe changes in ionosphere due to increased number of geomagnetic storms and local seismic activities.
On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes
2019, Advances in Space Research
Anomalous behavior of ionospheric total electron content (TEC) prior to earthquake has been observed in many studies. Evidence of such seismo-ionospheric coupling effects suggests that it is plausible to rely on TEC signatures for early earthquake warning. However, the detection of pre-earthquake TEC anomalies (PETA) has not been adopted in practice due to two pertinent issues. Firstly, the effects of space weather activity can affect TEC levels and cause anomalous behavior in the TEC. Usually arbitrary thresholds are set for space weather indices to eliminate TEC anomaly due to space weather effects. Secondly, the choice regarding moving time-window length used to characterise background variation of TEC within the statistical envelope approach has an effect on detection of PETA. While the rule-of-thumb in selecting the moving window length is to have a time window capable of capturing background variability and short-term fluctuations, the length of the time window used in the literature varies with little justification. In this study, a critical examination is conducted on the statistical envelope approach and in particular, to eliminate the effect of space weather activity without the use of arbitrary space indices to detect PETA. A two-part PETA identification procedure is proposed, consisting of wavelet analyses isolating non-earthquake TEC contributions, followed by the statistical envelope method using a moving window length standardized based on observed periodicities and statistical implications is suggested. The approach is tested on a database of 30 large earthquakes (M ≥ 7.0). The proposed procedure shows that PETA can be detected prior to earthquakes at higher confidence levels without the need to separately check for space weather activity. More importantly, the procedure was able to detect PETA for studies where it was previously reported that PETA could not be detected or detected convincingly.
An electric field penetration model for seismo-ionospheric research
2017, Advances in Space Research
We investigate the electric field penetration of the lithosphere–atmosphere–ionosphere coupling (LAIC) problem to study abnormal seismo-ionospheric disturbance. By directly solving the LAIC electric field penetration model at the high-latitude region, we find that the additional current induced at the ground surface flows into the ionosphere completely and further generates an abnormal ionospheric electric field. Therefore, we reasonably suggest that the electric field penetration of LAIC at middle- and low-latitude regions can be solved from the perspective of the ionospheric electric field model. The current from the downward atmosphere is treated as the source term. The simulation results demonstrate the following principal findings: (a) for the high-latitude region, the horizontal electric field in the ionosphere does not change with height and the vertical electric field can be neglected; (b) for the middle- and low-latitude regions, the intensity of the total horizontal electric field increases with the latitude and the vertical electric field is more obvious at low latitudes; and (c) the penetration height of the LAIC electric field in the ionosphere is lower at low latitudes than at high latitudes. We also find that according to the diurnal change of the ionospheric conductivity, the most efficient time for electric field penetration is between 00:00 and 04:00 local time.
One sliding PCA method to detect ionospheric anomalies before strong Earthquakes: Cases study of Qinghai, Honshu, Hotan and Nepal earthquakes
2017, Advances in Space Research
Citation Excerpt :
The earthquake impact on the Earth's environment is not only focused on the ground surface, but also the upper atmosphere and ionosphere (Sorokin et al., 2005). Since Leonard and Barnes (1965) for the first time found the ionospheric anomalies prior to Alaska earthquake, many researchers devoted to the study of ionospheric precursor anomalies before strong earthquakes (e.g. Liu et al., 2000; Pulinets and Boyarchuk, 2004; Pulinets et al., 2007, 2011; Kuo et al., 2014; Tojiev et al., 2014; Guo et al., 2016). The electromagnetic anomalies over the lithosphere, atmosphere and ionosphere have been all detected before great earthquakes.
A sliding principal component analysis (PCA) method is proposed to detect pre-earthquake ionospheric anomalies. We analyzed the precision of this new method with different length of time window in detecting the reference background total electron content (TEC). The results showed that the most suitable window length is 27 days which is consistent with the solar rotation period. We compared the precision of this new method with the sliding inter quartile range (IQR) method and the sliding average method in detecting the background TECs, and found that the precision of sliding PCA is better than those of the traditional methods in the middle and low latitudes because the detected background TEC residual errors by the sliding PCA method are less than that by the traditional methods. We adopted a more reasonable method to calculate the background value’s upper and lower bounds and then take four strong earthquakes (Qinghai earthquake, Honshu earthquake, Hotan earthquake and Nepal earthquake) as examples to prove the effectiveness of the sliding PCA method. From the detection results of the sliding PCA we found that obvious ionospheric anomalies appeared on April 1, 2010, March 8, 2011, February 2, 2014, April 11, 23, year 2015. After the further analysis of the solar-terrestrial environment and the distribution of TEC anomaly area, it can be considered that the pre-earthquake anomalies on these days before the earthquake may have a large correlation with the following earthquake. In addition, the TEC anomaly area spans largely in the longitude direction along the bound of equator anomalous zone, and the anomalous morphology has the conjugate structure. This regular can provide a valuable reference for the short-impending earthquake prediction in the future.
Classification of the Ionospheric Disturbances Caused by Geomagnetic and Seismic Activity with K-Nearest Neighbors Algorithm
2024, Wireless Personal Communications

View all citing articles on Scopus

View full text

Special case of ionospheric day-to-day variability associated with earthquake preparation

Abstract

Introduction

Section snippets

The correlation index

Spatial distribution complications

Regional variability index

Discussion

Conclusion

Acknowledgements

J. Atm. Sol.-Ter. Phys.

J. Atm. Sol.-Ter. Phys.

Adv. Space Res.

J. Atm. Sol.-Ter. Phys.

Proposed terminology for the classification and parameters for the quantification of variability in ionosphere morphology

Ann. Geophys.

Estimation of the size of earthquake preparation zones

Pure Appl. Geophys.