Earthquakes may disturb the lower ionosphere through various coupling mechanisms during the seismogenic and coseismic periods. The VLF (very low-frequency) signal radiated from ground-based transmitters will be affected when it penetrates the disturbed ionosphere above the epicenter area, and this anomaly can be recorded by low-Earth orbit satellites under certain conditions. In this paper, the temporal and spatial variation of the signal-to-noise ratio (SNR) of the VLF transmitter signal in the ionosphere over the epicenter of 2010 Yushu Ms 7.1 earthquake in China is analyzed using DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquake Regions) satellite observation. The results show that SNR over the epicenter of the Yushu earthquake especially in the southwestern region decreased (or dropped) before the main shock, and a GPS–TEC (Global Positioning System; total electron content) anomaly accompanied, which implies that the decrease in SNR might be caused by the enhancement of TEC. A full-wave method is used to study the mechanism of the change in SNR before the earthquake. The simulated results show SNR does not always decrease before an earthquake. When the electron density in the lower ionosphere increases by 3 times, the electric field will decrease about 2 dB, indicating that the disturbed-electric-field decrease of 20 % compared with the original electric field and vice versa. It can be concluded that the variation of electron density before earthquakes may be one of the important factors influencing the variation of SNR.
The VLF (very low-frequency) radio waves radiated by the powerful ground-based VLF transmitters have been used for long-distance communication and submarine navigation because of the efficient reflection within the Earth–ionosphere waveguide. However, there is still a small fraction of the wave energy that can leak into the higher ionosphere and magnetosphere after being absorbed intensively by the lower ionosphere. The signals from transmitters observed by the LEO (low-Earth orbit) satellites can be used to study the propagation of VLF waves in the Earth–ionosphere waveguide and ionosphere, as well as wave–particle interaction in the radiation belt (Inan et al., 2007; Inan and Helliwell, 1982; Lehtinen and Inan, 2009; Parrot et al., 2007).
It is gradually confirmed that earthquake precursors not only appear near the ground but also may couple with the atmosphere and ionosphere through some mechanisms, resulting in plasma disturbances in the ionosphere and recorded by various instruments like ionosonde or GPS (Global Positioning System) receivers measuring TEC (total electron content) (Liu et al., 2009, 2001, 2006; Pulinets et al., 2000; Stangl et al., 2011; Zhao et al., 2008). Therefore, the amplitude of the VLF signals from the ground-based VLF transmitter observed on the ground and from satellites will change when encounter the disturbed area in the ionosphere (Hayakawa, 2007; Maurya et al., 2016; Molchanov et al., 2006; Píša et al., 2013). Molchanov et al. (2006) have found the signal-to-noise ratio (SNR) of the electric field from VLF transmitters recorded by the DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquake Regions) satellite decreased near the epicenters during a series of earthquakes. The spatial size of an SNR reduction zone increases with the magnitude of the earthquake. However, it is hard to distinguish the coseismic anomaly and precursor from their results.
Two devastating earthquakes, the 2008 Ms 8.0 Wenchuan earthquake and the 2010 Ms 7.1 Yushu earthquake, occurred successively in southwestern China during the operation period (2004–2010) of the DEMETER satellite. Some research have also focused on the SNR variation of VLF transmitters using DEMETER satellite observation to extract the earthquake-related anomalies before the two strong earthquakes (He et al., 2009; Shen et al., 2017; Yao et al., 2013). The results all illustrated the decrease in SNR before the earthquakes. Since the earthquake-related ionospheric disturbance zone is not right over the epicenter, the relative position of the SNR anomaly and the epicenter should be further studied. The factors which influence SNR and the possible mechanism also needs to be comprehensively illustrated.
The Alpha VLF transmitters in Russia transmit three frequencies in each station which provide us opportunities to study the influence of the ionosphere on different wave frequencies. The devastating earthquake nearest the transmitters in China is the 2010 Ms 7.1 Yushu earthquake. In this paper we investigate the temporal and spatial SNR variation of the VLF transmitter signal in the ionosphere near the epicenter of the Yushu earthquake using DEMETER observation. The background variations of SNR in the same period of 2007–2010 have also been studied to distinguish whether the SNR reduction is caused by an earthquake or just ionospheric background changes. The mechanism of how the seismo-ionospheric disturbance affects the variation of SNR is discussed in this paper.
Regarding the mechanism of the VLF radio wave variations in the altitude of a LEO satellite (presented as SNR variation) before the earthquakes, Hayakawa (2007) and Píša et al. (2013) suggest the VLF anomalies exist because the lower ionosphere is lowered before earthquake. Molchanov et al. (2006) declared that the variation of SNR of satellite data is attributed to the ionospheric disturbance, especially the lower-ionospheric disturbance. Furthermore, it has been found that the electron density variation could exist in the lower ionosphere according to the computer ionosphere tomography (CIT) results based on GPS–TEC data before the Nepal Ms 8.1 earthquake in 2015 (Kong et al., 2018). The electric-field-penetrating model has shown that the electron density and height of the lower ionosphere can be changed by the additional current in the global electric circuit before the earthquake. On the other hand, Marshall et al. (2010) construct a 3D finite-difference time domain model to simulate that lightning could also cause the disturbance of the electron density in the lower ionosphere, which has a similar mechanism to the earthquake. Many studies also have found that the main loss of VLF wave power mainly occurs in the D–E region of the ionosphere when the wave penetrates into the ionosphere (Cohen and Inan, 2012; Liao et al., 2017; Starks et al., 2008; Tao et al., 2010; Zhao et al., 2017, 2015). In sum, the electron density variation in the lower ionosphere might be one main factor causing the SNR anomaly of VLF transmitter signal in the ionosphere. Based on these results, the full-wave calculation model was utilized to study the influence of the electron density disturbance of the lower ionosphere on the variation of VLF radio signals.
In this paper, a brief description of the DEMETER data and full-wave method used in this study are presented in Sect. 2. The temporal and spatial variations of SNR over the epicenter have been investigated before the Yushu earthquake with 4 years (2007–2010) of data; the full-wave model is used to simulate how the variation of electron density in the lower ionosphere affects the SNR of the electric field from a VLF transmitter at the altitude of a satellite in Sect. 3. The discussion and conclusions of this study are presented in Sects. 4 and 5 separately.
At the local time of 07:49:37.9 on 14 April 2010, a Ms 7.1 earthquake hit the
city of Yushu, Qinghai province, with an epicenter at 33.2
The locations of transmitters and the Yushu earthquake. The blue
squares represent the locations of the three transmitters (KRA, NOV, and KHA) in
Russia. The epicenter of Yushu earthquake is denoted by the black star. The
black square covers the region of the epicenter
The DEMETER satellite was launched on 29 June 2004 as a sun-synchronous
orbit at an altitude of 710 km, which then was changed to 660 km in December 2005 (Parrot et al., 2006), and the operation was ended in
December 2010. The scientific objective of DEMETER is to detect and
characterize the electromagnetic signals associated with natural phenomena
(such as earthquakes, volcanic eruptions, and tsunamis) or anthropogenic
activities. It operated in the region from invariant latitude
According to the formula of Dobrovolsky et al. (1979) the
preparation zone of the earthquake can reach
According to the method of Molchanov et al. (2006), the SNR
of the electric field was calculated as follows:
A full-wave method has been used to seek a solution of Maxwell equations for
waves varying as
Eliminating the
The evolution of SNR evolution VLF radio waves frequencies 11.9 kHz (top panel), 12.6 kHz (middle panel), 14.9 kHz (bottom panel) with
The SNR five revisit periods before and one revisit period after the earthquake
in 2010 were calculated to study the evolution of SNR above the epicenter.
The SNR distributions of three frequencies (11.9, 12.6, and 14.9 kHz) within the
region of the epicenter
The average SNR variation with revisit periods inside the square
region with the center of the epicenter. Panels
To minimize the impact of other factors and confirm whether the SNR anomaly
is caused by the earthquake and not the variation of the ionospheric background, we
focus on SNR in the black square (shown in Fig. 1) of the same period
in 2007–2009 as the background, when there are no large earthquakes and the data
when the transmitter was turned off or affected by geomagnetic storms are
eliminated. The mean value of all the data in each period has been obtained
to get the time sequence shown in Fig. 3. In Fig. 3, the black dashed
line represents the occurrence date of the earthquake. The black and red solid
lines represent the average values in the five periods before the earthquake and one
period after the earthquake within the region of the epicenter
The above results use the average value within the region of the epicenter
A time series of SNR right above the Yushu epicenter. The Ms 7.1
Yushu earthquake occurred at the local time of 07:49:37.9 on 14 April 2010.
The red, gray, and two black curves denote the currently observed SNR,
associated median, and upper and lower bound (UB and LB), respectively. Blue and
green sign represent the upper and lower anomalous days identified by the
computer routine, respectively. The LB and UB are constructed by the previous 1–11 d moving median (M), lower quartile (LQ), and upper quartile
(UQ), and the LB and UB are calculated by LB
The result in Fig. 4 shows the anomalies of SNR during the successive 20 d before the Yushu earthquake. However, the 20 d orbital data may be carried into the ionospheric background noise of different space. To avoid this kind of ionospheric background noise, we select the three revisit orbits to analyze the anomalies of SNR before the Yushu earthquake further (the revisit orbit on 9 April overhead the epicenter, the revisit orbit on 13 April which is 550 km away from epicenter, and the revisit orbit on 10 April which is 750 km away from the epicenter are selected). The quartile-based process is also performed for every revisit's orbital data, but the 6 d sliding-mean value (including 3 d before the current day and 2 d after the current day) have been analyzed. The green and blue bar represent negative and positive anomalies in one orbit, respectively, in Fig. 5. As we can see in the top and middle panel, on 9 and 10 April, the negative and positive anomalies both occurred like other days in the same two revisit orbits. These anomalies could be induced by the daily variation. In the bottom panel, there are no obvious anomalies in other days with the same revisit orbit of 13 April, but the SNR values have obvious negative anomalies for all orbits on 13 April. These results further confirm that the anomalies of SNR occurred on 13 April.
A revisit orbital SNR of 9, 10, and 13 April 2010. The red, gray, and
two black curves denote the currently observed SNR, associated median, and
upper and lower bound (UB and LB), respectively. Blue and green bars represent the positive and negative anomalies in one orbit, respectively. The LB and UB
are constructed by the 6 d moving median (M, including 3 d before
the current day and 2 d after the current day), lower quartile (LQ), and upper
quartile (UQ), and the LB and UB are calculated by LB
We speculate that the anomalies of SNR may be related to the anomalies of
electron density. To confirm our conjecture, we used GPS–TEC map data distributed by CODE (Center for Orbit Determination in Europe) to check out
whether the total electron content (TEC) showed similar anomalies. The
resolution of TEC data from CODE is
The spatial distribution of the GPS–TEC map
In Sect. 3.1, we analyzed the spatial and temporal characteristics of SNR
during the five revisit periods before and one revisit period after the Yushu
earthquake. It can be found that SNR decreased significantly before the
earthquake over the epicenter area of the Yushu earthquake, especially in the
southwestern direction. After excluding the influence of geomagnetic storms,
we further explored the possible mechanism of SNR abnormal variation in
this section. As mentioned in the Sect. 1, the electron density in the
lower ionosphere can be disturbed through various mechanisms before
earthquakes. The electron density before the Nepal earthquake was obtained from a
computer ionosphere tomography method by using GPS data (Kong et al.,
2018). Their results shows that the abnormal variation of electron density
occurred at a height of 150 km before the Nepal earthquake and the range of
variation reached about 30 %. However the electron density hardly changed
at a height of 450 km. Marshall et al. (2010) have shown
that 60 horizontal discharge pulses of 7 V m
The electron density obtained from COSMIC data on 13 April in the TEC abnormal region.
As mentioned in the introduction, the major VLF wave energy almost lost in
the D–E region; after that, the radio waves penetrate the topside of the ionosphere and
even magnetosphere with a minor linear reduction because of the mode conversion
(Lehtinen and Inan, 2009; Shao et al., 2012). The data of COSMIC
also illustrate that the anomaly of electron density not only occurred in the F region (represented by the anomaly of TEC) but also occurred in the D–E region, so the full-wave method (FWM) (Lehtinen and Inan, 2009) was utilized
to simulate the electric field between altitudes of 0 and 120 km induced by
the NOV transmitter, which is the closest transmitter to the epicenter of the Yushu
earthquake. Considering that the study area is much smaller than the radius
of the earth, the earth's curvature was neglected in this study. A Cartesian
coordinate system was established with
The electron density profiles during nighttime. IRI represents the original electron density predicted by the IRI model; IRI+ represents the electron-density-added Gaussian shape perturbation; IRI- represents the electron-density-subtracted Gaussian shape perturbation.
We set a Gaussian shape perturbation at 110 with 20 km standard deviation in the ionosphere. The magnitude of the perturbation was set to a maximum of 1.3 and 4 times both the increase and decrease compared to the original electron density of nighttime (the average electron density above the NOV transmitter on 2–14 April 2010 at 22:00 LT calculated from the IRI-2016 model). The perturbation patterns are shown in Fig. 8 using 4 times the increase and decrease compared to the original electron density as an example. The electron collision frequency is modeled by the exponential-decay law described in Sect. 2.3. The geomagnetic-field intensity and inclination at the location of the NOV transmitter are calculated by the IGRF model.
The electric field only from the ground surface to 120 km has been calculated by
the full-wave model because the electromagnetic wave at VLF band will propagate
upward as the whistler mode. The group velocities of the upward-radiated
whistler mode are almost parallel, and these waves form a narrow-collimated
beam, which does not have much lateral spread. The direction of group
velocities is determined by the refractive-index surface. The refractive-index
surface of the upgoing whistler mode at 120 km is shown in Fig. 9. A ducted
propagation is adopted at this
The refractive-index surface at 120 km. Red line shows a slice of
the refractive-index surface at
The simulated results of the electric field at 120 km height with a different
electron density along the magnetic meridian plane within 1000 km area
around the transmitter NOV with 11.9 kHz transmitting frequency are shown in
Fig. 10. The simulated results are similar when the transmitting frequency
is 12.6 and 14.9 kHz. It can be seen that the wave mode interference in
the waveguide has been mapped into the ionosphere in the electric field
(Lehtinen and Inan, 2009), and the electric field increases when the
electron density decreases, and vice versa (Fig. 10a, c). Furthermore, the
maximum value of the electric field varying with height is collected to
study the influence of the electron disturbance. At nighttime, when
The total electric field excited by the ground-based VLF transmitter
NOV with a transmitting frequency of
Which coupling mechanism is effective to induce electron density anomalies
in the D–E layer by earthquakes is still an open question.
Molchanov et al. (2006) declared that the lower-ionospheric
disturbance is caused by acoustic gravity waves triggered by earthquakes. At
present, the coupling mechanism of the electric field proposed by Pulinets
(2009) is widely accepted because it has been demonstrated by a series of
models (Kuo et al., 2011; Namgaladze et al., 2013; Zhou et al., 2017) and
observations (Gousheva et al., 2006, 2008; Li et al.,
2017). As for the 2008 Wenchuan Ms 8.0 earthquake in China, Li et al. (2017) reported continuous observations about the anomalous electric field
which lasted longer but weaker than the electric field induced by lightning
during 1 month before the Wenchuan earthquake, which suggests that the
abnormal electric field might be caused by the seismogenic activity of the
Wenchuan earthquake. Xu et al. (2011) also found about 2 mV m
The Kp and Dst index in April 2010
The lightning, geomagnetic storms, and other natural sources may induce
disturbance in the lower ionosphere (Marshall et al., 2010; Maurya et
al., 2016; Peter et al., 2006; Zigman et al., 2007). As known, the intensive
TEC change occurs during geomagnetic storms, and the change in TEC is affected intensively during the main phase of the geomagnetic storm,
gradually returning to normal accompanying the recovery phase. To avoid the
effect of geomagnetic storms, the data which Kp
In this paper, the SNR of the electric field from a ground-based VLF transmitter
observed by the DEMETER satellite was analyzed before and after the 2010 Ms 7.1
Yushu earthquake. The VLF signals from Russian VLF transmitters can be
clearly observed at frequencies of 11.9, 12.6, and 14.9 kHz over the epicenter
from the electric-field spectrum data. To determine whether the SNR
variation is related to the Yushu earthquake, the data in quiet space weather
conditions (Kp
The electron density in the lower ionosphere may change abnormally before an earthquake through some coupling mechanisms. The full-wave simulation result on NOV transmitter, which is the nearest transmitter next to the Yushu earthquake, indicates that the electric field at the altitude of a satellite will change when we add a disturbance of electron density in the lower ionosphere. That is to say that the SNR of the electric field will also change when the background noise is considered to be invariable a few days before the earthquake. The simulated results show SNR does not always decrease before an earthquake like some previous reports show (He et al., 2009; Molchanov et al., 2006; Yao et al., 2013), which depends on the change in electron density. The SNR of the electric field will decrease with the increase in electron density in the lower ionosphere; SNR will increase with the decrease in electron density in the lower ionosphere. It can be concluded that the variation of electron density before earthquakes may be one important factor influencing the variation of SNR.
We will continually explore the law of SNR change and verify the mechanism we proposed with more seismic events by utilizing the newly launched LEO electromagnetic satellite (China Seismo-Electromagnetic Satellite) (Shen et al., 2018; Zhao et al., 2019) in upcoming work.
The DEMETER satellite data were provided by the DEMETER scientific mission
center (
SZ conceptualized the project, performed the formal analysis and investigation, supervised the project, created the visualizations, and wrote the original draft of the paper. SZ, RZ, and XS conceptualized the methodology and secured the project's resources. SZ, RZ, CZ, and XS reviewed and edited the paper.
The authors declare that they have no conflict of interest.
This article is part of the special issue “Satellite observations for space weather and geo-hazard”. It is not associated with a conference.
This paper benefited from constructive review comments by two anonymous reviewers and the editor. Thanks for their advice and help.
This research has been supported by the National Science Foundation of China (grant nos. 41704156, 41574139, and 41874174), the National Key R&D Program of China (grant no. 2018YFC1503501), the Special Fund of the Institute of Earthquake Forecasting, China Earthquake Administration (grant nos. 2015IES010103 and 2018CSES0203), and the APSCO Earthquake Research Project Phase II.
This paper was edited by Mirko Piersanti and reviewed by two anonymous referees.