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Longitudinal Dependence and Seasonal Effect on Equatorial Electrojet Using MAGDAS Data
Journal of Geology & Geophysics

Journal of Geology & Geophysics
Open Access

ISSN: 2381-8719

+44 20 3868 9735

Research Article - (2016) Volume 5, Issue 1

Longitudinal Dependence and Seasonal Effect on Equatorial Electrojet Using MAGDAS Data

Ibrahim Khashaba A* and Essam Ghamry
National Research Institute of Astronomy and Geophysics, Geomagnetism, Egypt
*Corresponding Author: Ibrahim Khashaba A, researcher, National Research Institute of Astronomy and Geophysics, Geomagnetism, Egypt, Tel: +201006177040 Email:

Abstract

EE-index (EDst, EUEL), has been used to study the longitudinal dependence and seasonal variation of the equatorial electrojet (EEJ). The EUEL data eliminates many sources of disturbances by subtracting the median value of horizontal component (H) and the E Dst from H component data. EUEL data at a chain of stations along the dip equator have been analyzed to provide a detailed study on the equatorial electrojet. Data from eight stations (ANC, ILR, AAB, TIR, LKW, BCL, DAV and YAP stations) have been used for a period of three years (2009, 2010 and 2011). The longitudinal dependence has been studied for each year, a very good agreement between each year results has been found. This study shows that the magnetic signature of the EEJ is stronger in South America with a maximum at about longitude 77°W; and weaker in Asia, with a minimum in India, between longitudes 70°E and 90°E. The seasonal variations of the equatorial electrojet have been studied by both the whole data set (disturbed and quiet days) and quiet days’ data. It has been proved that there is a semiannual variation in the equatorial electrojet with equinoctial maxima.

Keywords: EEJ-MAGDAS, Equatorial electrojet, Ground magnetic stations, EE index

Introduction

Egedal [1,2] discovered an electric current that flows in a narrow zone of approximately 600 km in width above the magnetic dip equator. This intense electric current, which in daytime flows in an eastward direction was named the “equatorial electrojet” by Chapman [3]. The EEJ represents a rather large enhancement of the diurnal variation in the horizontal or surface component of the geomagnetic field at and in the vicinity of the dip equator. The enhanced current was explained as being because of an abnormally large electrical conductivity [4,5]. Features of EEJ have been described for longitude regions of 75°W (Forbush and Casaverde 1961), 15°–19°E, 75°E, 5°W [6-12].Most of the first studies were carried out to explain the generating mechanism of EEJ [5,13]. Since the 1970s, some theories and physical models of the ionospheric dynamo have been developed in order to explain the mechanism of the EEJ flow and its main features (day to day, seasonal variability, counter-electrojet, electrodynamic processes of coupling with global scale current systems, etc.,) [14-19]. Another approach to simulate the EEJ has been done through the analysis of EEJ magnetic effects assuming simple current configurations. These configurations are the line current the thin-band current with different modes of latitudinal dependence: the uniform and parabolic and the “fourth degree” current distribution as well as the thick current distribution incorporating latitude and height dependence [3,6,7,20].

In the present study, the EEJ has been estimated using simultaneous ground based geomagnetic data recorded at 8 stations from MAGnetic Data Acquisition System (MAGDAS) at different longitudes (Figure 1 and Table 1). Also, the data of the three quietest days in each month during three years (2009, 2010 and 2011) has been analyzed. The obtained results have been used to study the longitudinal dependence and the seasonal variation of EEJ.

Stations inside the equatorial region
Abbrev. Station name Country GG Lat. GG Long. GM Lat. GM Long.
ILR Ilorin Nigeria 8.50 4.68 -1.82 76.80
AAB Adis Ababa Ethiopia 9.04 38.77 0.18 110.47
TIR Tirunelveli India 8.70 77.80 0.21 149.30
LKW Langkawi Malaysia 6.30 99.78 -2.32 171.29
BCL Bac Lieu Vietnam 9.32 105.71 -0.66 177.96
DAV Davao Philippine 7.00 125.40 -1.02 196.54
YAP Yap Island FSM 9.50 138.08 1.49 209.06
ANC Ancon Peru -11.77 -77.15 0.77 354.33

Table 1: Stations under investigation.

geology-geosciences-geomagnetic-stations

Figure 1: Location map of the geomagnetic stations used in the present work.

Data Analysis

At first, the three years (2009, 2010 and 2011) for 8 stations have been analyzed (Table 1). Here we deal with the whole data then focus on the three quietest days in each month for the whole period (Table 2).

Months Quiet days in 2009 Quiet days in 2010 Quiet days in 2011
January 12 22 23 07 09 17 05 23 30
February 02 08 17 20 21 27 03 09 27
March 02 07 09 21 22 23 15 16 26
April 02 04 23 10 18 26 10 26 27
May 12 25 27 23 24 27 08 12 20
June 01 12 17 08 12 20 03 28 29
July 17 18 19 10 17 18 16 27 28
August 15 16 24 21 22 30 18 19 31
September 23 24 29 11 12 30 01 19 23
October 10 14 20 01 02 14 22 28 29
November 06 23 29 06 19 26 09 14 19
December 01 03 04 10 11 22 16 26 27

Table 2: The three international quietest days.

The data used in the present work has been taken from the International Center for Space Weather Science and Education ICSWSE, Kyushu University, Japan. The data are in three forms H, ER, and EUEL data; where:

1 H component data: Variation in the North-South component at a certain magnetic station.

2 ER data (ΔH): The median value of the H component data, which is determined for the period from the start time of the observation to the end time, is subtracted from the H component data for each station.

3 EUEL data: Is calculated by subtracting the EDst index from the ER data.

The EE-index (EDst (Equatorial Disturbance in storm time), EU (index for equatorial electrojet), and EL (index for counter electrojet)), is proposed by Uozumi [21] to monitor temporal and long-term variations of the equatorial electrojet by using the MAGDAS/CPMN real-time data.

In the present study we deal with EUEL data in most cases.

Figures 2 and 3 represent the EUEL data for all magnetic observatories under investigation. The gaps that appear in most plots are due to problems in the measuring instrument.

geology-geosciences-TIR-stations-during-Years

Figure 2: EUEL data for ANC, ILR, AAB and TIR stations during Years 2009, 2010 and 2011.

ogy-geosciences-EUEL-data

Figure 3: EUEL data for LKW, BCL, DAV and YAP stations during Years 2009, 2010 and 2011.

Estimation of the EEJ

In this part, the EEJ has been estimated by measuring the maximum value of the EUEL for each quiet day at 12 Local Time at each station. Tables 3-5 represent the values of EEJ in the three quietest days each month during years 2009, 2010 and 2011 for the equatorial stations ANC, ILR, AAB, TIR, LKW, BCL, DAV and YAP.

Dates ANC ILR AAB TIR LKW BCL DAV YAP
12/01/2009 128.4 41.7 -- 39.5 43.7 -- 55.6 51.9
22/01/2009 55.3 21.8 53.9 66 46.7 -- 84.6 67.1
23/01/2009 55.5 32 -- 53.7 64.3 -- 82.7 66.5
02/02/2009 170 51.8 67.5 69 84.5 -- 89.8 74.7
08/02/2009 93.5 59.6 92.9 68.6 51 -- 90.1 --
17/02/2009 118.3 72 82.4 68.9 65.7 -- 74.5 74.6
02/03/2009 132.1 -- 59.1 70.4 91 -- 94.2 96.4
07/03/2009 76.9 -- 55.9 60.4 66 -- -- 65.6
09/03/2009 132.9 -- 69.1 77.5 68.8 -- -- 105
02/04/2009 77.4 50.5 -- 76.2 97.7 107.2 113.6 98
04/04/2009 93.3 38.3 88.3 -- 91.3 93.2 92.1 66.5
23/04/2009 -- 39.4 -- 63.1 54 65.7 82 75.1
12/05/2009 -- 43.2 49.6 65.7 76 76.1 83.9 59.5
25/05/2009 -- 61.7 100.4 -- 93.2 92.5 85.4 79.2
27/05/2009 -- 54.6 74.3 77.1 74.8 76.8 70.6 60.2
01/06/2009 -- 58.5 -- 41.1 -- 51.2 35.3 28.6
12/06/2009 -- 52.4 81.8 57 -- 59.4 48.9 34.7
17/06/2009 -- 42.6 35.9 48.8 -- 61.3 59.7 46
17/07/2009 -- 38.8 54.2 61.9 -- 53.6 58.9 51.1
18/07/2009 -- 51.8 55.7 45.4 -- 42.6 39.1 31.5
19/07/2009 -- 38.7 35 44.4 -- 54.9 47.9 40.9
15/08/2009 -- 56.9 74.5 -- -- 94.7 73.2 47.6
16/08/2009 -- 45.2 48 -- -- 62.7 58 35.9
24/08/2009 -- 45.3 -- -- -- 78.7 66.4 53.2
23/09/2009 160.2 66.6 -- -- 80.8 85.7 94.1 --
24/09/2009 159.5 53.2 83.7 -- 89.9 94 107.1 --
29/09/2009 147.9 57.9 69.2 -- 75.1 71.1 64.1 --
10/10/2009 108.7 58.4 -- -- 76.4 82.5 98 82.2
14/10/2009 99.9 39.5 -- -- 56.3 61.2 73.3 61.7
20/10/2009 137.5 67.5 -- -- -- 115.1 108.1 81
06/11/2009 115.6 -- -- -- -- 87.1 97.2 83.1
23/11/2009 83.5 -- -- -- -- 58 53 45.9
29/11/2009 104 -- -- -- -- 39.9 45 48
01/12/2009 88.9 -- -- -- -- 23.7 24.8 39.3
03/12/2009 128.4 -- -- -- -- -- 24.2 22.7
04/12/2009 111.7 -- -- -- -- -- 51.7 41.4

Table 3: Estimated EEJ in 2009.

Dates ANC ILR AAB TIR LKW BCL DAV YAP
07/01/2010 114.4 -- -- -- -- 105.8 138.7 106.2
09/01/2010 80.4 -- -- -- -- -- 81.7 78.4
17/01/2010 131.5 -- -- -- -- 48.5 69.4 60.3
20/02/2010 115.4 -- -- -- -- 101.6 123 102.5
21/02/2010 78.5 -- -- -- -- 87.8 104 92.4
27/02/2010 122.1 -- -- -- -- 86.7 102.7 91.6
21/03/2010 119.6 -- -- 87.3 75.2 -- 97.9 93.6
22/03/2010 109.1 -- -- 87 80.7 -- 104.1 101.8
23/03/2010 106.4 -- -- 74.3 76.5 -- 87.2 86.8
10/04/2010 72.5 60.2 -- 78 -- -- 95.1 98
18/04/2010 123.9 75.9 -- -- -- -- 90.4 74.5
26/04/2010 -- 64.4 -- -- 98.9 93.9 98.4 95.9
23/05/2010 59.7 41.1 -- -- -- 77 83 --
24/05/2010 127.2 51.7 -- -- -- 54.3 71.8 --
27/05/2010 90.7 54.1 -- 72.2 -- 71.8 75.1 --
08/06/2010 57.9 40.2 -- 71.8 -- 83,7 78.8 --
12/06/2010 87.8 53.8 -- 66.8 -- 68.6 74.1 --
20/06/2010 71.1 30.1 -- 43.8 -- 64.5 36.6 22.6
10/07/2010 76.7 52.4 -- 53.7 -- -- 61.4 35.7
17/07/2010 82.6 44 -- 69 82.3 -- 71.6 53.4
18/07/2010 104.9 34.4 -- 66.5 90.7 -- 81.9 57.8
21/08/2010 99.9 48.7 58.7 50.9 -- -- 86.4 62.3
22/08/2010 69.3 44.6 41.9 66.9 -- 71.6 72.2 56.6
30/08/2010 138.5 -- 75.8 70.5 -- 63.2 64.6 50
11/09/2010 156.3 -- 103.3 102.6 -- 103 101.1 72.1
12/09/2010 155.8 -- 72.6 91.3 -- 94.2 91.5 71
30/09/2010 134.9 53.7 95 99.5 -- 107 118.2 102.5
01/10/2010 136 55.3 44.1 67.6 -- 86.3 105.3 93.6
02/10/2010 160 43.8 67.1 74.1 -- 89.5 86 74
14/10/2010 120.8 59.8 71.4 64.6 -- 80.2 99.4 84.3
06/11/2010 109.2 70.2 99.2 69.9 -- 92.5 116.2 91.7
19/11/2010 121.9 46.1 69.9 74.9 -- 76.7 86.5 80.3
26/11/2010 93.9 62.2 95.2 64.9 -- 89.2 99.3 92.7
10/12/2010 110.7 80.1 99.3 76.8 -- 105.7 125.1 110.6
11/12/2010 104.4 59.5 53.4 28.6 47.6 50.2 68.4 71.6
22/12/2010 79.9 61.1 87.3 78.4 95.9 97 89.6 80.9

Table 4: Estimated EEJ in 2010.

  ANC ILR AAB TIR LKW BCL DAV YAP
05/01/2011 84.1 57.8 66.6 -- 58.7 52.5 81.2 --
23/01/2011 131.9 61.5 69.3 -- 98.1 95 114.1 --
30/01/2011 99.7 34.3 62.1 -- 72.1 71 80.3 --
03/02/2011 83.2 60 89.7 -- 53.4 47.5 66.9 --
09/02/2011 133.1 70.6 79.5 -- 91.3 94 113.6 --
27/02/2011 -- 43.4 77.3 -- 71.7 73.4 89.5 --
15/03/2011 -- 53.6 82.8 -- 121.7 123.9 149.5 --
16/03/2011 -- 63.8 99.1 -- 111.1 -- 110.2 --
26/03/2011 169 78.6 118.2 -- -- 106.2 98.7 --
10/04/2011 129.1 79.3 131 -- 116.2 -- 117.7 95.7
26/04/2011 110.2 75.7 93.7 109.2 119.3 117.4 129.3 105.2
27/04/2011 155.3 77.3 104.9 106.9 114.6 -- 135 106.5
08/05/2011 111.3 61.3 77 82.2 93 -- 106.3 80.3
12/05/2011 106.2 72.8 90.1 80.3 75.5 -- 95 73.8
20/05/2011 129.7 71.3 117.3 88.6 94 -- 91.9 70.2
03/06/2011 75.2 57.6 -- 56.7 75.5 -- 74.8 65.8
28/06/2011 102.9 -- -- 74.3 -- -- 74.6 29.9
29/06/2011 128.1 -- -- 88.2 -- -- 86 69.7
16/07/2011 91.6 -- -- 75.3 -- -- -- 59.7
27/07/2011 -- -- -- 74.9 77.3 -- 68.5 59.4
28/07/2011 -- -- -- 67.3 85.3 -- 99.9 76.8
18/08/2011 -- 62.1 -- 67.5 -- -- 123.6 110.8
19/08/2011 -- 73.6 -- 85.6 107.5 -- 93.6 69.4
31/08/2011 -- 55.5 -- 60.5 74 -- 80.1 74.3
01/09/2011 -- 72.9 -- -- 111.8 -- 119.7 97.7
19/09/2011 177.8 60.1 -- 141.3 143.3 -- 159.5 127.5
23/09/2011 -- -- -- 95.5 118.6 -- 146.7 116.5
22/10/2011 -- 91.8 112 123.7 141 -- 121.6 104.8
28/10/2011 -- 83 120 116.3 -- -- 156.7 126.2
29/10/2011 -- 80.1 106.4 106.4 -- -- 162 138.8
09/11/2011 -- 84.7 -- -- -- -- 106.6 110.2
14/11/2011 -- 94.9 -- 106.8 -- -- 177.3 145.2
19/11/2011 -- 53.3 45.7 52 81.6 -- 97.6 79.3
16/12/2011 -- 50.5 75.5 54.6 76.9 -- 115.7 112.8
26/12/2011 -- 49 72.5 67 90.9 -- 119.6 109
27/12/2012 153.9 81.7 82 -- 80 -- 94 100.6

Table 5: Estimated EEJ in 2011.

Longitudinal dependence during years 2009, 2010 and 2011

The longitudinal dependence of the EEJ is estimated through surface measurements of EUEL along the dip-equator. We use available magnetic data recorded at different longitudinal sectors.

In order to reduce the variables that may affect the strength of the EEJ, we will analyze simultaneous records from available stations for each year. The EEJ is given by the mean value of the conjoint days of EUEL.

In year 2009, there were only three conjoint days (22/01/2009, 02/02/2009 and 17/02/2009) between seven stations (ANC, ILR, AAB, TIR, LKW, DAV and YAP), while in year 2010 there were eleven conjoint days (22/08/2010, 30/09/2010, 01/10/2010, 02/10/2010, 14/10/2010, 06/11/2010, 19/11/2010, 26/11/2010, 10/12/2010 11/12/2010 and 22/12/2010) between seven stations (ANC, ILR, AAB, TIR, BCL, DAV and YAP). In year 2011, there were five conjoint days (26/04/2011, 27/04/2011, 08/05/2011, 12/05/2011 and 20/05/2011) between seven stations (ANC, ILR, AAB, TIR, LKW, DAV and YAP).

As shown in Figure 4, there is a very good agreement between the trends of the equatorial electrojet strength in the three studied years.

geology-geosciences-dependence-EEJ

Figure 4: Longitudinal dependence of EEJ in years 2009, 2010 and 2011.

Mean longitudinal dependence

The longitudinal dependence of the EEJ is expressed by a numerical spline function estimated by calculating the mean value of the three years for each station.

Figure 5 shows that the magnetic signature of the EEJ is stronger in South America with a maximum at about 77°W. It is followed by a minimum in West Africa at about 4°E. The EEJ magnetic signature is weak in Asia-except Philippine, with a minimum in India, between 70°E and 90°E. A secondary maximum is at about 125°E. These longitude variations of the EEJ magnetic effect roughly follow variations of the inverse main field (1/B) at the dip equator.

geology-geosciences-Longitudinal-dependence

Figure 5: Mean longitudinal dependence.

Seasonal variation using whole data set

Figure 6 shows 30 day running means of the daily EUEL values for DAV station. These reveal clearly the presence of semiannual variation of the EEJ that maximizes during equinoctial months.

geology-geosciences-Seasonal-variation

Figure 6: Seasonal variation at DAV (30 days running means of daily EUEL data), two cycles of current are clearly obvious with maximum at equinoctial months.

The seasonal variation of equatorial electrojet at DAV station reveals two cycles a year, each cycle reach maximum at equinoctial months. In year 2009 the EEJ started increasing until reaches maximum in March then decreased till midyear, the next cycle started from midyear then reached maximum in September and again started decreasing till end of the year. The same trend reoccurred in year 2010. In year 2011 the EEJ reached maximum in April and October.

Seasonal variation using quiet days

In this section we study the stations that almost have no or at least few missing days each year. These are, in 2009 DAV and YAP stations, in 2010 ANC station, DAV station and YAP station, in 2011 ILR station, LKW station and DAV station.

The number of day in the year is plotted against its EUEL value then a 4th degree polynomial fitting is performed for each station.

Figures 7-14 show clearly the semiannual variation of the equatorial electrojet.

geology-geosciences-polynomial-fitting

Figure 7: Seasonal variation at DAV in 2009, the EUEL values in quiet days are represented by red dots, the blue line represents a 4th degree polynomial fitting in order to view the trend of EUEL values, there is two cycles of current reaching their maximum during spring and autumn (equinoctial months).

geology-geosciences-Seasonal-variation

Figure 8: Seasonal variation at DAV in 2010.

geology-geosciences-variation-DAV

Figure 9: Seasonal variation at DAV in 2011.

geology-geosciences-variation-YAP

Figure 10: Seasonal variation at YAP in 2009.

geology-geosciences-Seasonal-variation-YAP

Figure 11: Seasonal variation at YAP in 2010.

geology-geosciences-variation-ANC

Figure 12: Seasonal variation at ANC in 2010.

geology-geosciences-variation-ILR

Figure 13: Seasonal variation at ILR in 2011.

geology-geosciences-variation-LKW

Figure 14: Seasonal variation at LKW in 2011.

Discussion and Conclusion

In the present study geomagnetic data from a chain of stations along the dip equator have been analyzed to provide detailed study in this region on the equatorial electrojet. Data from eight stations (ANC, ILR, AAB, TIR, LKW, BCL, DAV and YAP) have been used. Most of the analyzed data are EUEL data for a period of three years (2009-2011).

The strength of EEJ has is found to vary both from day to day for a single station and from station to another. The maximum value of EEJ in the period of study at ANC is 177.8 nT and the minimum is 55.3 nT, ILR maximum 94.9 nT and minimum 21.8 nT, AAB maximum 131 nT and minimum 35 nT, TIR maximum 141.3 nT and minimum 28.6 nT, LKW maximum 143.3 nT and minimum 43.7 nT, BCL maximum 123.9 nT and minimum 23.7 nT, DAV maximum 177.3 nT and minimum 24.2 nT, and YAP maximum 145.2 nT and minimum 22.6 nT.

As expected there is a local time dependence of EEJ. EEJ-related magnetic effects in the daily variations of the horizontal component appear at about 6 LT, reach a maximum near local noon and vanish after 18 LT.

Simultaneous surface magnetic records from eight stations in different longitude sectors have been used to study the longitudinal dependence of EEJ. Three years have been analyzed separately. There is a very good agreement between the results of the three years, which makes the obtained results as one of the reliable results to discuss the longitudinal dependence of EEJ. The intensity of EEJ is found to be stronger in South America with a maximum at about 77°W. It is followed by a minimum in West Africa at about 4°E. The EEJ magnetic signature is relatively weak in Asia with a minimum in India, between 70° and 90°E. A secondary maximum is at about 125°E. These longitude variations of the EEJ magnetic effect roughly follow variations of the inverse main field (1/B) at the dip equator.

The seasonal variations of the equatorial electrojet have been studied by both the whole data set (disturbed and quiet days) and quiet days’ data. It has been proved that there is a semiannual variation in the equatorial electrojet with equinoctial maxima.

References

Citation: Ibrahim Khashaba A, Ghamry E (2015) Longitudinal Dependence and Seasonal Effect on Equatorial Electrojet Using MAGDAS Data. J Geol Geophys 5:235.

Copyright: © 2015 Ibrahim Khashaba A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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