Study of Ionospheric Perturbations during Strong Seismic Activity by Correlation Analysis Method
Santosh Kumar Jain,
In this study, we report the variation in foF2 (critical frequency of F2 layer) parameter by correlation method at the time of strong seismic event. Ionosonde data installed at different locations were used for analysis purpose of four cases of earthquakes. Considering two ionosonde recorders, where one ionosonde is in the earthquake preparation zone and the other is out side of it. By correlation analysis method Karls Pearson coefficients have been calculated. Results of the study showed the anomaly in the Karls Pearson coefficient related to foF2 parameter, few days before the seismic activity. This fact can be regarded as precursory phenomena. The changes in the F-layer density may be interpreted as a result of associated seismic electric field generated by internal gravity waves. It may be due to the inflow of energy from the earth and then propagated upward which perturb the F-region of ionosphere. Hence, ExB drift in the ionospheric region get changed. This study may be beneficial for prediction of earthquake.
Received: November 06, 2011;
Accepted: December 14, 2011;
Published: February 22, 2012
The responses of the ionosphere to seismic activity have been studied by many
workers (Pulinets et al., 2002; Liu
et al., 2004; Chen et al., 2004).
Earthquakes are capable of inducing large scale perturbations in the global
ionospheric dynamics and related parameters. Day-to-day ionospheric variability
still remains the subject of the ionospheric physics related to seismic activity
which are not studied thoroughly enough. Attempts to classify the terminology
of ionospheric variability can be found in the review (Davies
and Baker, 1965; Depuev and Zelenova, 1989; Chuo
et al., 2002). Usually the variability is expressed as a deviation
(in percent) from the mean or median value. The quantitative estimations of
the ionospheric variability are given in the papers (Kim
and Hegai, 1997; Pulinets et al., 2003; Forbes
et al., 2000; Rishbeth and Mendillo, 2001)
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 Pulinets (1998) and Pulinets
et al. (2004a, 2005) who proposed the effects
of seismic activity through the electromagnetic coupling with the ionosphere
which is 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 (Pulinets
and Boyarchuk, 2004; Pulinets et al., 2005).
|| Characteristics of earthquakes
In present applications, the correlation radius of the ionosphere is a very
important parameter (Tronin et al., 2002). But
the correlation technique developed does not take into account the nature of
the ionosphere variability source. In present study, one of the most important
things which is associated with earthquake precursor is their local character.
There are numbers of methods by which we can prove the localness of seismo-ionospheric
variations. Three important methods to demonstrate the ionospheric variability
in the earthquake preparation area: regional variability index, regional mapping
and correlation method. In these three methods correlation method is more reliable;
so, we are using here correlation method.
The characteristics of earthquakes considered in the present study are summarized
in Table 1 with their onset date and time, epicenter latitude/longitude,
focal depth and the distance from concerned observing station. The magnitude
of all earthquakes are >5 and the focal depth varied from 10 to 40 km. This
study includes four earthquake events. The radius of earthquake preparation
zone is calculated for each earthquake by using the formula given by Dobrovolsky
et al. (1979).
MATERIALS AND METHODS
To get precursors two measuring points are used in very simple arrangements, first receiver that is located inside the earthquake preparation zone is called receiver ionosonde. The second receiver which is located out side the earthquake preparation zone is control receiver. To localize the receivers generally two things must be taken care of, first is to get similar reaction to geomagnetic disturbances receiver ionosonde must be posted in the same geomagnetic latitude, and second is as the local time dependence of the ionospheric reaction to the geomagnetic storm, there should not be much difference in the longitude of the receiver ionosonde.
The idea to use the correlation between the neighboring ionospheric stations
to review the seismo-genic variations in sporadic E-layer of the ionosphere
was proposed by Liperovskaya et al. (1994) and
reviewed in Liperovsky et al. (2000). 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., 2004b). To determine the radius
of correlation associated with the seismic activity the conception of the earthquake
preparation zone was used (Dobrovolsky et al., 1979):
where, ρ is the radius of the earthquake preparation zone and M is the
earthquake magnitude on Richter scale.
|| Values of earthquake preparation zone radius
The value of earthquake preparation zone radius in accordance with Eq.
1 is shown in Table 2. It is supposed that ionospheric
variability associated with seismic activity will be observed over the earthquake
preparation zone (Dobrovolsky et al., 1979).
According to the earthquake preparation zone conception the character of the
ionospheric variability is different within the earthquake preparation area
in comparison with the variability out side of it. In general case, it is not
obligatory to put the control station out side the earthquake preparation
zone, it is sufficient if it will be quite far from the epicenter. The daily
Karls Pearson coefficient of correlation calculated for these two stations
in the form:
Here, indices 1 and 2 correspond to the first and second ionosonde stations, respectively, foF2 (Critical frequency of F2 layer) is represented by time series, the foF2 values are calculated from the ionosonde measurements, k = 24 (or 96 or 144) points is the number of samples per day (traditionally k = 24 for t = one hour sampling interval is used for ionospheric soundings, k = 96 for 15 min interval is used), the mean value <foF2> and standard deviation σ are determined by the following expression:
where, <foF2> is the daily mean value of the critical frequency and σ is the standard deviation. We applied this method on the series of earthquakes in the different areas of earth. As an example we will consider the data of two stations: Athens (38°N and 24°E) and San-Vito (40°N and 17°E). The first one is inside the main seismo-active area. Cross-correlation study for these stations is shown in Fig. 3. Similar pattern is applied for other earthquakes.
In this study, ionospheric variations are examined before the all four earthquakes that occurred during December 2005 to June 2009. The results related to these earthquakes are described below.
Major earthquake of January 08, 2006 that occurred at Greece-Southern:
The major earthquake of magnitude 6.2 (on Richter scale) occurred January 08,
2006 at Greece-Southern [36°N, 23°E]. The observed results are presented
in Fig. 1-3. This earthquake was much severe
and destructive. For this event the observed foF2 data for the entire period
of December 2005 and January 2006 are analyzed using Eq. 1-4
and results plotted are shown in Fig. 1-3.
In the Fig. 1 variation of foF2 for Athens station is shown.
Athens station is a receiver station which is very close to epicenter. Figure
2 shows the variation of foF2 for San-Vito station [40°N and 17°E]
which is control station and far from epicenter of earthquake.
|| Study of variation of foF2 (earthquake occurred on January
|| Study of variation of foF2 (earthquake occurred on Janunary
|| Cross-correlation study for Athens and San-Vito station
Figure 3 shows the cross-correlation study for Athens and
San-Vito station. It shows that the cross correlation-coefficient decreases
three days before the main shock of earthquake. Which shows the precursory phenomena.
In Fig. 1-3 E mark the time
of occurrence of main shock of earthquake and P marks the precursory
Earthquake March 25, 2007 that occurred at Greece-Argostolion: During
the month of March 2007, an earthquake of magnitude 5.9 (on Richter scale) occurred
at Greece-Argostolion on March 25. For correlation analysis the foF2 data of
the month of March 2007 analyzed. The correlation results of foF2 variations
for this case are shown in Fig. 4-6. In
the Fig. 4, some major variations in foF2 values recorded
prior to one day from the main shock of earthquake.
Earthquake of December 26, 2007 that occurred at Turkey-Ankara: The
major earthquake of magnitude 6.9 (on Richter Scale) occurred on December 26,
2007 at Turkey-Central-Ankara [39°N, 33°E].
||Study of variation of foF2, earthquake occurred on March 25,
2007 data used from March 1, 2007 to March 30, 2007
|| Study of variation of foF2 earthquake occurred on March 25,
|| Correlation study for Athens and San-Vito station earthquake
occurred on March 25, 2007
The observed results are presented in Fig. 7-9.
This earthquake was much severe and destructive. For this event the observed
foF2 data for the entire period of December 2007 are analyzed using Eq.
1-4 and results plotted are shown in Fig.
7-9. In the Fig. 7 variation of foF2
for Athens [38°N, 24°E] station is shown. Athens station is a receiver
station which is very close to epicenter. Figure 8 shows the
variation of foF2 for San-Vito [39°N and 33°E] station.
San-Vito [39°N and 33°E] is the control station which is so far from epicenter of earthquake. Figure 9 shows the cross-correlation study for Athens [38°N, 24°E] and San-Vito [39°N and 33°E] station. It shows that the cross correlation-coefficient decreases before two days from the main shock of earthquake.
Earthquake May 24, 2009 that occurred at Balkans:Nw:Macedonia: During
the month of May 2009, an earthquake of magnitude 6.1 (on Richter Scale) occurred
at Balkans:Nw:Macedonia on May 24. For correlation analysis the foF2 data of
the month of May 2009 analyzed.
|| Study of variation of foF2, earthquake occurred on December
||Study of variation of foF2, earthquake occurred on Dec. 26,
2007 data used from December 1, 2007 to Dec. 30, 2007
|| Correlation study for Athens and San-Vito station earthquake
occurred on Dec. 26, 2007
|| Study of variation of foF2, for Athens station earthquake
occurred on May 24, 2009
The correlation results of foF2 variations for this case are shown in Fig.
10-12. Figure 11 shows the variation
of foF2 for San-Vito Station. In the Fig. 12 some major variations
in foF2 values recorded prior to two days from the main shock of earthquake.
This Fig. 12 also indicates the breaking of mutual correlation
after one day from the main shock.
|| Study of variation of foF2, for San-vito station
|| Study of variation of cross-correlation coefficient (earthquake
occurred on May 24, 2009)
The observed perturbations in the ionosphere during seismic activity reveal
a coupling between the lithosphere and the ionosphere. The changes in the F
layer density may be interpreted as a result of associated seismic electric
field generated by internal gravity waves (Boyarchuk, 1999;
Bolt, 1964; Calais and Minster,
1995). Such field can penetrate the F region of the ionosphere and move
the layer up or down due to ExB drift and bring out the changes in plasma density.
The enhancement in density may be the result of earthquake associated ExB drift
when the density can increase if an electric field of sufficient magnitude develops
at ionospheric height. The main goal of this study is the detection of significant
precursors. In all four cases presented in the paper one can observe the decrease
of correlation coefficient of the related ionospheric stations before the seismic
shock. The index demonstrates the spread of the ITEC over the area few hundred
kilometers in diameter. If we look at the problem from the position of the physical
mechanism, the variability intensity will depend on the extend of the atmospheric
changes. The modification of these parameters is provided by the air ionization
produced by energy released from the active tectonic fault before the earthquake.
In this study technique of cross- correlation index applied for determination
of the ionospheric variability over the earthquake preparation area. It is well
known that on short- term basis, i.e., day-to-day or hour-to-hour basis, the
earths ionosphere is strongly dependent on magnetic influences. Which
are originated from the Sun. Hence, during magnetic disturbances, it is very
difficult to separate significance changes in ionosphere related to earthquake.
In this study, we choose the position of receiver station and control station
hence, perturbations related to magnetic activity filtered out.
In this study, we have shown the variation in foF2 data prior to earthquake. The result discussed in the above section shows significant ionospheric perturbations over the related ionosonde stations several days before the main shock of earthquake. The observed anomalous variation might be correlated with the seismic effect due to isolation from any known solar or magnetic activities. From the above observations it is found that the pre-earthquake ionospheric disturbances are observed for each earthquake. Summary of the ionospheric perturbations depletion in correlation index, before the main shock of the four earthquakes discussed above, is shown in Table 1. The results presented above shows a very strong coupling between receiver ionosonde station and control ionosonde station. For better understanding the foF2 data of two ionosonde stations used.
Authors are thankful to Department of Commerce NOAA, Space Environment Center for providing Ionospheric Data and also thankful to WDC Kyoto Japan for data of Dst index one of the author (A.K. Gwal) thankful to SAP (UGC) of financial support.
1: Boyarchuk, K.A., 1999. Kinetics of elementary ions in the lower atmosphere acted upon by ionization radiation. Izv. Atmos. Ocean. Phys., 33: 236-240.
2: Bolt, B.A., 1964. Seismic air waves from the great 1964 Alaskan earthquake. Nature, 202: 1094-1095.
3: Calais, E. and J.B. Minster, 1995. GPS detection of ionospheric TEC perturbations following the January 17, 1994, Northirdge Earthquake. Geophys. Res. Lett., 22: 1045-1048.
4: Chen, Y.I., J.Y. Liu, Y.B. Tsai and C.S. Chen, 2004. Statistical tests for pre-earthquake ionospheric anomaly. Terr. Atm. Ocean Sci., 15: 385-396.
Direct Link |
5: Chuo, Y.J., J.Y. Liu, M. Komogawa and Y.I. Chen, 2002. The Anomalies in the foEs Prior to M 6.0 Taiwan Earthquakes. In: Seismo Electromagnetics: Lithosphere-Atmosphere-Ionosphere Coupling, Hayakawa, M. and O.A. Molchanov (Ed.). TERRAPUB, Tokyo, pp: 309-312
6: Davies, K. and D.M. Baker, 1965. Ionospheric effects observed around the time of the Alaskan earthquake of March 28, 1964. J. Geophys. Res., 70: 2251-2253.
7: Depuev, V. and T. Zelenova, 1989. Electron density profile changes in a pre earthquake period. Adv. Space Res., 18: 115-118.
8: Dobrovolsky, I.P., S.I. Zubkov and V.I. Miachkin, 1979. Estimation of the size of earthquake preparation zones. Pure Applied Geophys., 117: 1025-1044.
CrossRef | Direct Link |
9: Forbes, J.M., S.E. Palo and X. Zhang, 2000. Variability of the ionosphere. J. Atm. Sol. Ter. Phys., 62: 685-693.
10: Gaivoronskaya, T.V. and S.A. Pulinets, 2002. Analysis of the F2-layer variability in the areas of the seismic activity. Preprint IZMIRAN No. 2 (1145), Moscow, 20.
11: Kim, V.P. and V.V., Hegai, 1997. On possible changes in the mid latitude upper ionosphere before strong earthquakes. J. Earthquake Pre. Res., 6: 275-280.
12: Liu, J.Y., Y.J. Chuo, S.J. Shan, Y.B. Tsai and S.A. Pulinets, 2004. Pre- earthquake ionospheric anomalies monitored by GPS TEC. Ann. Geophys., 22: 1585-1593.
13: Liperovskaya, E.A., N. Christakis, V.A. Liperovsky and M.A. Oleinik, 1994. Seismic and anthropogenic activity effects in the night time sporadic E layer of the ionosphere. Geomag. Aeron., 34: 311-314.
14: Liperovsky, V.A., O.A. Pokhotelov, E.V. Liperovskaya, M. Parrot, C.V. Meister and A.O. Alimov, 2000. Modification of sporadic E-layers caused by seismic activity. Surveys Geophys., 21: 449-486.
CrossRef | Direct Link |
15: Pulinets, S.A., 1998. Seismic activity as a source of the ionosphere variability. Adv. Space Res., 22: 903-906.
16: Pulinets, S.A., K.A. Boyarchuk, V.V. Hegai, V.P. Kim and A.M. Lomonosov, 2000. Quasielectrostatic model of atmosphere-thermosphere-ionosphere coupling. Adv. Space Res., 26: 1209-1218.
CrossRef | Direct Link |
17: Pulinets, S.A., K.A. Boyarchuk, A.M. Lomonosov, V.V. Khegai and J.Y. Liu, 2002. Ionospheric precursors to earthquake: A preliminary analysis of the foF2 critical frequencies at Chung-Li ground based station for the vertical sounding of the ionosphere (Taiwan Island). Geomag. Aeron., 42: 508-513.
18: Pulinets, S.A. and K.A. Boyarchuk, 2004. Ionospheric Precursors of Earthquakes. Springer-Verlag, Berlin, Germany, Pages: 315
19: Pulinets, S.A., T.B. Gaivoronska, A.L. Contreas and L. Ciraolo, 2004. Correlation analysis technique revealing ionospheric precursors of earthquakes. Nat. Hazard. Earth Syst. Sci., 4: 697-702.
20: Pulinets, S.A., J.Y. Liu and I.A. Safronova, 2004. Interpretation of a statistical analysis of variations in the foF2 critical frequency before earthquakes based on data from Chung-Li ionospheric station (Taiwan). Geomag. Aeron., 44: 102-106.
Direct Link |
21: Pulinets, S.A., A. Leyva and L. Ciraolo, 2005. GPS TEC variations around the time of the Colima, earthquake of 21 January 2003. Geofis. Int., 44: 369-377.
22: Tronin, A.A., M. Hayuakawa and O.A. Molchanov, 2002. Thermal IR satellite data application for earthquake research in Japan and China. J. Geodyn., 33: 519-534.
23: Rishbeth, H. and M. Mendillo, 2001. Patterns of ionospheric variability. J. Atm. Sol.-Ter. Phys., 63: 1661-1680.