Relationship between the equatorial electrojet and global Sq currents at the dip equator region
© Hamid et al.; licensee Springer. 2014
Received: 31 March 2014
Accepted: 16 October 2014
Published: 29 October 2014
The equatorial electrojet (EEJ) is a strong eastward ionospheric current flowing in a narrow band along the dip equator. In this study, we examined the EEJ-Sq relationship by using observations at six stations in the South American, Indian, and Southeast Asian sectors. The analysis was carried out with data on geomagnetically quiet days with Kp ≤3 from 2005 to 2011. A normalization approach was used because it yields more accurate results by overcoming the uncertainties due to latitudinal variation of the EEJ and Sq. A weak positive correlation between the EEJ and Sq was obtained in the Southeast Asian sector, while weak negative correlations were obtained in the South American and Indian sectors. EEJ-Sq relationship is found to be independent of the hemispheric configuration of stations used to calculate their magnetic perturbations, and it also only changed slightly during low and moderate solar activity levels. These results demonstrate that the Southeast Asian sector is indeed different from the Indian and South American sectors, which is indicative of unique physical processes particularly related to the electro-dynamo. Furthermore, we also demonstrate that the definition of the EEJ, that is, the total current or enhanced current, can significantly affect the conclusions drawn from EEJ-Sq correlations.
The horizontal magnetic field lines at the equator produce a unique current system like that described below. In the dayside equatorial ionosphere, currents driven by tidal wind through the dynamo mechanism cause an accumulation of charges, which are positive at dawn and negative at dusk terminators, and this results in an eastward electric field, , along the magnetic equator. The cross fields of this electric field and northward magnetic field results in an eastward Pedersen current and downward Hall current. The Pedersen current, , flows dominantly at about 130-km altitude in response to the peak Pedersen conductivity there. The downward Hall current leads to an accumulation of charges at the upper and lower edges of the dynamo layer, which results in the formation of an upward polarized electric field, , with a magnitude about 20 times larger than . This vertical polarization electric field induces a strong eastward Hall current, . This Hall current flows and peaks around 110-km altitude in response to the peak Hall conductivity there (Forbes, ; Onwumechili, [1992a]; Prölss, ).
A rocket study by Onwumechili ([1992b]) has revealed the existence of an intense lower current layer and a weak upper current layer that peak at altitudes of 107 ± 2 km and 136 ± 8 km, respectively. The eastward lower current layer, which consists mainly of a Hall current, is defined as the equatorial electrojet (EEJ), and it practically corresponds to . The upper current layer, which consists mainly of a Pedersen current, is thought to be part of the global Sq current and essentially corresponds to . The global Sq current system is characterized by dayside vortices that are counterclockwise in the northern hemisphere and clockwise in the southern hemisphere. Both currents overlap to give the total current at the dip equator: , where σ3 is the Cowling conductivity (Hirono, , ) that perturbs the geomagnetic northward (H) component of equatorial ground magnetometer observations. Detailed studies of both currents can be found in Onwumechili ([1992b]); Stening (), and Onwumechili ().
The relationship between the EEJ and Sq current has been studied for many years, but until now, agreement still appears to be lacking on this topic. Some previous studies found a good correlation between them, while others have showed nonexistent or only weak correlations. This conflict likely results from the lack of good continuous data and the difficulty of isolating global Sq and EEJ at dip equator stations. Most studies have used the two-station method to calculate the EEJ as the difference between measurements taken at a dip equator station and at an off-dip equator station, and data from the off-dip equator station are typically used directly to represent the global Sq contribution at the dip equator. In many cases, no significant correlation is obtained as shown in Ogbuehi et al. (), Okeke et al. (), and Okeke and Hamano (). In contrast, studies by Kane () and Yamazaki et al. (), which used the total H component at the dip equator to represent the EEJ (which we hereafter refer to as the total current), revealed a good correlation with Sq at off-dip equator stations. This discrepancy might be understood by the insight that the correlation coefficient between two time series x 1 and x1 + x2 will usually be different from that between x1 and x2 (Mann and Schlapp, ).
One also needs to keep in mind that the EEJ current varies drastically with latitude, especially within ±6° across the dip equator. This fact introduces some uncertainty in the EEJ estimation from ground-based data as it is often impossible to locate the station exactly at the dip latitude. So far, this problem was encountered by all previous researchers on this topic. Furthermore, the Sq current at the dip equator also differs from the one outside this region as the Sq current is also known to vary with latitude. Most previous studies directly used the Sq measured at off dip-equator stations, and this will certainly affect the study of the EEJ-Sq relationship at the dip equator.
In the present study, we reexamined the EEJ-Sq relationship by using long-term ground-based magnetometer data simultaneously from station pairs in three longitude sectors. Furthermore, to overcome the above-mentioned uncertainties due to the latitudinal variation of EEJ and Sq, we normalized the observation data to the dip equator using the CM4 model by estimating peak EEJ and Sq values at the dip equator to yield more accurate results. Additionally, we compared the EEJ-Sq relationship with the total current-Sq relationship. Possible mechanisms are then discussed to explain the results obtained.
Data description and method of analysis
Geographic and geomagnetic coordinates of the stations used
For this study, we used the EUEL index (Yumoto and the MAGDAS Group, ; Uozumi et al.). The hourly EUEL index was obtained from the H component at all stations. In the construction of this index, the median value of the H component was first subtracted from the original magnetic data to obtain ER S for each available equatorial station, S. The average value of ER S observed at the nightside (LT = 18-06) stations along the magnetic equatorial region gives the equatorial disturbance storm time index, EDst. This index represents global magnetic variation including disturbances in the equatorial region, particularly those from sudden storm commencement (SSC) and ring currents, and part of magnetospheric origin disturbances such as substorms and DP2 effects. The EUEL index used in this study is given by the subtraction of the EDst index from ER S . More details on the EUEL index can also be found in Hamid et al. (). The analysis was carried out using the maximum EUEL index during noontime for days with Kp ≤3 during the years of 2005 to 2011. By taking data around noontime, we limited our analysis to the period when the EEJ current is strongest and avoided the morning and evening effects such as the counter-electrojet effect.
Relationship between the EEJ and Sq
t -test analysis, t( df ) = t , and p <0.05 or p >0.05 results for both the slope, β , and correlation coefficient, R , where df is the degree of freedom, p is the p-value, t is the t-value
t-test; t(df) = t,p<0.05 orp>0.05
t(1508) = −1.2985 × 103, p <0.05
t(1675) = −1.3122 × 103, p <0.05
t(1154) = 0.8900 × 103, p <0.05
t(1508) = −13.332, p <0.05
t(1675) = −7.6737, p <0.05
t(1154) = 5.4390, p <0.05
t(1537) = 1.1513 × 103, p <0.05
t(1746) = 1.6122 × 103, p <0.05
t(1166) = 1.3268 × 103, p <0.05
t(1537) = 4.2502, p <0.05
t(1746) = 18.9416, p <0.05
t(1166) = 26.5052, p <0.05
We also examined the relation between the total current and Sq as illustrated in the bottom panels of Figure 5. As expected from the definition of the total current itself, this current showed a positive linear relation (slope) with Sq for all longitude sectors. The correlation between the total current and Sq was found to be higher than the correlation between the EEJ and Sq in both the Indian and Southeast Asian sectors, and the R value for the total current and Sq relation was more than 0.5 in the Southeast Asian sector. The t-test results showed that both the β and R values obtained were significant, and the results are shown in Table 2. These correlation coefficients are consistent with the fact that the Sq component was more significant in the total current for both the Southeast Asian and Indian sectors compared to the South American sector (see Figure 4). Figure 5 thus demonstrates how the definition of EEJ affects the conclusion drawn for the EEJ-Sq relationship. In the rest of this paper, we use the EEJ defined by the two-station method for further investigation.
In this paper, with the use of long data set during 2005 to 2011, we reexamined the EEJ-Sq relationship by using appropriate station pairs and a normalization approach. The results obtained revealed a weak correlation between the EEJ and Sq at the dip equator in all three sectors, which included South America, India, and Southeast Asia. We also found longitudinal dependence in this EEJ-Sq relationship as the relationship in the Southeast Asian sector was different from that in the South American and Indian sectors.
Some previous studies have also reported a weak correlation between the EEJ and Sq. Okeke and Hamano () performed an analysis using data from three dip equator stations located in the South American (−75.2°) and Pacific sectors (−157.5° and 158.33°). They found small correlation coefficient values between the EEJ and Sq when the calculations were performed during five quiet days of each month in 1998. Their results are in agreement with work of Okeke et al. (), which used data in the Indian sector during the quiet year of 1986. Conversely, a study by Ogbuehi et al. () showed that the correlation coefficient between EEJ and Sq reached −0.6 during the December solstice in 1958. By using the different northern-southern station configurations with the dip equator station located in the western Pacific Ocean, they concluded that the EEJ tends to be negatively correlated with Sq currents measured from stations equatorward of the global Sq current focus. The different results obtained are due to the large longitude separation of the station pairs used in their study, which was quite significant; the separation was about 30°, as the north and south off-dip equator stations were located in Vietnam and Papua New Guinea, respectively. Furthermore, the latitude separations of off-equator stations were remarkable and amounted to 15° and 17° for the north and south stations, respectively, and these certainly affected the calculated EEJ current. In general, the longitude and latitude separations of ground stations used in all previous studies were quite big and therefore their results are not conclusive. The new technique applied in this study allowed us to overcome these uncertainties and therefore provides more precise results.
Other previous studies that reported high correlations between EEJ and Sq are Kane () and Yamazaki et al. (). However, it should be noted that both of these studies used the total current instead of the EEJ defined by the two-station method, thus their conclusion is essentially about the total current-Sq relationship. Kane () reported a high positive correlation between the total current and Sq during equinoxes and winter using Indian data from quiet days in 1964. Yamazaki et al. () also reported a high positive correlation in the Southeast Asian sector using quiet day data from 1996 to 2005. The results from these two studies are consistent with our results on the total current-Sq relationship shown in the lower row of Figure 5. However, we have also shown how different the EEJ-Sq relationship is from the total current-Sq relationship, with the latter having a generally much higher correlation. The fact that the correlation value between two time series, x1 and x2, is usually different from that between x1 and x1 + x2 can be used to explain the conflict encountered by the previous researchers in this area. Therefore, it is apparent that the definition of the EEJ significantly affects the conclusion regarding the ‘EEJ-Sq’ relation. We have adopted the EEJ obtained by the use of the two-station method for our study.
There are several factors that might contribute to the weak correlation between the EEJ and Sq. Rocket measurements by Onwumechili ([1992b]) showed that the EEJ and Sq at the dip equator flow at different altitudes where the effective conductivities, electric fields, and winds are different. This suggests that Sq and EEJ are driven by different factors, which could naturally result in a weak correlation between the two. Fang et al. () has demonstrated using a Thermosphere Ionosphere Mesosphere Electrodynamic General Circulation Model (TIME-GCM) simulation that local wind could significantly affect the EEJ. We also know that Sq is affected by large-scale global wind, while EEJ is affected by both global and local wind. At longer time scales (seasonal and solar cycles), the local effect averages out and leads to a similar trend between Sq and EEJ as can be seen in Figure 4. But at shorter time scales, local wind could significantly contribute to the EEJ and lead to a weak correlation between EEJ and Sq. Therefore, the weak correlation obtained in our study implies that the local wind contribution to the EEJ was large. Furthermore, since our analysis used daily values, the weak correlation also implies that day-to-day variability in Sq and EEJ is largely uncorrelated. In addition, some studies have suggested that the EEJ has its own circuit whose return paths and intensity variations are different from the global Sq current (Ogbuehi et al. ; Onwumechili, [1992b]). This could further contribute to the weak correlation observed at the dip equator.
This study has shown that the EEJ-Sq relationship varies with longitude. In particular, the Southeast Asian sector shows a positive weak correlation, which is opposite to that in the South American and Indian sectors. Since the declination angle in the Southeast Asian sector is similar to that in the Indian sector, it cannot be the cause for the difference. Thus, the difference is likely caused by the wind. The archipelagic state of Southeast Asia causes a warm pool there, which drives intense deep convection activity. This consequently generates excessively strong atmospheric waves (Tsuda and Hocke, ), some of which can propagate upward to the dynamo regions to disturb the neutral wind there and hence the electric field and currents. This meteorological aspect may significantly contribute to the unique EEJ-Sq relationship in this sector. Model simulations should be carried out to confirm these findings. Further studies using data from other longitude sectors such as the African sector are also necessary (El Hawary et al.).
Weak correlations between the EEJ and Sq at the dip equator were obtained with a positive value in the Southeast Asian sector and negative values in the South American and Indian sectors.
These relations were independent of the hemispheric configuration of stations used to calculate them and also showed little change during low and moderate solar activity levels.
These results demonstrate that the Southeast Asian sector is indeed different from the Indian and South American sectors, which is indicative of unique physical processes particularly related to the electro-dynamo. This aspect should be explored in future studies.
Finally, we suggest that when studying this type of relationship, one needs to isolate the global Sq contribution from the total current at the dip equator to obtain the EEJ, as we have shown how different the results can be when using the total current.
We thank all the members of the MAGDAS project for their cooperation and contribution to this study. Financial support was provided by the Japan Society for the Promotion of Science (JSPS) (No. 25800274) and a Shisedo Science Grant (2013). We are also grateful to JSPS for supporting the Overseas Scientific Survey (Nos. 15253005 and 18253005) and publications of the scientific research results (Nos. 188068, 198055, 208043). We acknowledge the National Oceanic and Atmospheric Administration (NOAA) for providing Kp index data, Goddard Space Flight Center/Space Physics Data Facility (GSFC/SPDF) OMNIWeb at http://omniweb.gsfc.nasa.gov for providing F10.7 data, and the National Geophysical Data Center (NGDC) for the estimated values of the magnetic inclination component.
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