Large-scale ionospheric irregularities occurrence at Ilorin, Nigeria

Authors


Abstract

Ionospheric irregularities are a regular occurrence at the equatorial latitude during the postsunset hours especially during high-solar activity. These irregularities could pose serious challenges to satellite-based navigation and positioning applications by causing fading and degradation of transionospheric signals passing through these irregularities. We have investigated large-scale ionospheric irregularity occurrence at Ilorin, Nigeria (latitude = 8.48°N, longitude = 4.67°W, dip = 4.1°S), a station located within the equatorial region in the African sector. The index used in this study is the rate of change of total electron content (rate of change) derived from 30 s receiver-independent exchange data obtained using a dual frequency GPS receiver (i.e., NovAtel GPStation-2). The study covers a period of 4 years (2009–2012). The results obtained showed that large-scale irregularities occur between March and November and are more pronounced between 1900 LT and 2400 LT. The irregularities were observed to show two peaks: one in March and the other in September. Solar activity trend was also observed. The irregularity level around the peaks seems to increase with solar activity. Although the study covered a period of 4 years, the period could be regarded as the increasing phase of the solar cycle 24.

1 Introduction

Postsunset equatorial ionosphere has been observed to show electron density irregularities of scale sizes varying from centimeters to kilometers, which are generated by plasma instability processes [Rishbeth, 1981; Fejer, 1996; Kelley, 1985, 1989; Abdu, 2001]. These irregularities are capable of causing fading and loss of lock of Global Navigation Satellite System (GNSS) signals (e.g., GPS L1 and L2 signals) with significant impact on GPS positioning accuracy [e.g., Skone et al., 2001; Knight et al., 1999; Doherty et al., 2004; Seo et al., 2011]. It is well known that 400 m small-scale ionospheric irregularities are responsible for the amplitude scintillation of the transionospheric radio waves at GNSS frequencies. These 400 m small-scale irregularities coexist with large-scale ionospheric irregularities [Basu et al., 1999]. Large-scale ionospheric irregularities are the focus of the current study.

Various authors have reported the seasonal dependency of ionospheric irregularities in the American sector of the equatorial region [e.g., Chu et al., 2005; Sobral et al., 2002; Kintner et al., 2007; Seemala and Valladares, 2011]. The study of Chu et al. [2005] was on ionospheric irregularities and ionospheric plasma bubbles over Brazil. The results showed that ionospheric irregularities and ionospheric plasma bubbles are more pronounced between 20:00 and 01:00 LT in October to March. The results of Sobral et al. [2002] are similar to those of Chu et al. [2005]; i.e., in the American sector of the equatorial region, scintillation occurs from September to March. Similarly, the study of Kintner et al. [2007] over the Brazilian sector, where magnetic north is about 13° west of geodetic north, showed that irregularities exhibit seasonal dependency with a maximum in December to January and a minimum near May to June. Results on irregularity studies in the African sector have also been reported [e.g., Susnik and Forte [2011]; Paznukhov et al., 2012; Oladipo and Schuler, 2013]. Paznukhov et al. [2012] used GPS data from 11 Scintillation Network Decision Aid (SCINDA) stations in Africa, including Ilorin, for 2010. Their results showed that the strongest and most frequent plasma bubbles occur in the equinox periods. Similarly, Oladipo and Schuler [2013] studied large-scale ionospheric irregularities at Franceville, Gabon, an equatorial station in the African sector for a year (i.e., i.e. 2001 / 2002) during the last high-solar activity. Their results also showed seasonal dependency of the occurrence of ionospheric irregularities. Irregularities occur at Franceville from March to November with a kind of minimum around June.

These two studies on the equatorial stations in the African sector were based on 1 year worth of data (i.e., 2001/2002 for the study of Oladipo and Schüler [2013] and 2010 for the study of Paznukhov et al. [2012]). The results from these stations in the African sector are different from those of the American sector as reported in the studies mentioned above. Since the previous studies were based on 1 year worth of data, it is worthwhile to use longer-term data in order to investigate the long-term trend in the occurrence of ionospheric irregularities. The current study covers a period of 4 years, i.e., from 2009 to 2012; hence, it is expected that the results obtained in this study will show the trend of the irregularities over Ilorin during the rising phase of the solar activity 24.

2 Data and Methods of Analysis

For the current study, we have used receiver-independent exchange (RINEX) data from a dual frequency GPS receiver located at Ilorin, Nigeria (latitude = 8.48°N, longitude = 4.67°W, geomagnetic latitude = 4.1°S). The receiver is a part of a network of receivers called Scintillation Network Decision Aid (SCINDA) [Groves et al., 1997]. SCINDA is a network of ground-based receivers dedicated for monitoring ionospheric scintillation at the UHF and L-band frequencies. The study covers a period of 4 years (i.e., 2009 to 2012).

The leveled carrier phase measurements from 30 s GPS data were used to obtain relative total electron content (TEC). It is well known that the phase measurements are affected by cycle slips, which manifest as jump/discontinuity in the carrier phase values. The Blewitt [1990] algorithm was used for the detection and correction of any cycle slip in the phase measurement data used for this study. Butterworth filter of order 4 was also used to remove the trend from the data.

Multipath effect could be mistaken for scintillation activity especially at low-elevation angles. In order to avoid this, different authors have used observation data of above certain cutoff mask ranging from 15° to 35° [e.g., Chu et al., 2005; Mushini et al., 2011; Meggs et al., 2006]. We have used an elevation cutoff mask of 25° in the current study.

The time variation of TEC also known as rate of change of TEC (ROT) and its derived indices are a good proxy for the phase fluctuation, which is a measure of large-scale ionospheric irregularities. These kinds of indices can be used to characterize all the known features of equatorial spread F (ESF) [Mendillo et al., 2000].

Based on the idea of Mendillo et al. [2000], Oladipo and Schüler [2013] derived the average rate of change of TEC index (ROTIAVE). The ROTIAVE is the average of ROTI over 30 min interval for a satellite and then the average over all satellites in view. ROTIAVE gives the average level of irregularities (phase fluctuation) for half an hour, and the value is valid over the station. According to Pi et al. [1997], the rate of change of TEC index is given as

display math(1)

where ROTI is the rate of change of TEC based on standard deviation of ROT over 5 min interval. According to Oladipo and Schüler [2013], ROTIAVE is defined as

display math(2)

where n is the satellite number, 0.5 h is the half an hour (0, 0.5, 1,…23.5, 24 UT), i is the 5 min section within half an hour (i  =  1,  2,  3,  4,  5, and 6),  nSat(0.5 h) is the number of satellites observed within half an hour, and k is the number of ROTI values available within half an hour for a particular satellite. The value of ROTIAVE may be categorized as follows: ROTIAVE  <  0.4 indicates no ionospheric irregularities, 0.4  <  ROTIAVE  <  0.8 indicates moderate ionospheric irregularities, and ROTIAVE > 0.8 indicates high or severe ionospheric irregularities. The ROTIAVE has been demonstrated to capture the irregularity level over a station and was used for statistical occurrence study over Franceville (latitude = −1.63°, longitude = 13.55°, dip latitude = −15.94) for a year (2001/2002) during the last high-solar activity. In the current study, ROTIAVE is used for statistical occurrence study of large-scale ionospheric irregularities over Ilorin, Nigeria.

In order to be able to quantify the extent of occurrence, the percentage occurrence has been defined as

display math(5)

where Nirreg is as the number of days in a month with irregularities, and NALL is the number of days in a month for which data are available.

3 Results and Discussions

Figure 1 is a typical diurnal plot showing the occurrence of ionospheric irregularities for pseudo random noise (PRN) 29 on 7 April 2012 (day of year (DOY) = 98) at Ilorin. Figure 1a shows the relative slant TEC in total electron content unit (TECU), Figure 1b is the ROT in TECU/min, and Figure 1c is the ROTI in TECU/min. As shown in Figure 1a, TEC depletion was observed around 2100 LT for this particular satellite. This is well known to be a signature of large-scale ionospheric irregularities, and it usually accompanies small-scale ionospheric irregularities, which cause scintillation of transionospheric signals at GNSS frequencies. These irregularities were captured by both the ROT index and the ROTI index as indicated by their values (i.e., the increase in the fluctuation of ROT and also the increase in the value of ROTI) around 2100 LT.

Figure 1.

Large-scale irregularities as manifested in (a) relative slant TEC in TECU, (b) ROT in TECU/min, and (c) ROTI after Pi et al. [1997] in TECU/min for PRN 29 at Ilorin on 7 April 2012 (1 TECU  =  1016 electrons m− 2). Elevation cutoff mark of 25° was used. The plots indicate the depletion of ionization (shown in Figure 1a) due to large-scale ionospheric irregularities, and these irregularities are captured by ROT index and ROTI.

As mentioned earlier in section 2, ROTIAVE has been shown to capture large-scale ionospheric irregularities over a station. Figure 2 shows sample diurnal plots for (a) a day with irregularities and (b) a day without irregularities. As clearly shown in Figure 2a, both ROTIAVE and ROTI captured the irregularity level over the station. Figure 2b is for a day without irregularities as indicated by the two indices. It is important to mention here that ROTI plots in Figure 2 are for all the satellites in view for the day. Although the two indices captured the irregularity level at the station, the advantage of the ROTIAVE over the ROTI has been shown in the paper of Oladipo and Schüler [2013]. For example, ROTIAVE eliminates the noise spikes or extreme values that are usually present in ROTI values.

Figure 2.

Diurnal panel plot of irregularity level at Ilorin, Nigeria, for (a) 1 April 2012 (DOY = 92) and (b) 10 January 2012 (DOY = 10). (top row) ROTI in TECU/min and (bottom row) ROTIAVE in TECU/min. The figure showed the level of irregularities as indicated by the two indices for 2 days at Ilorin.

Figure 3 shows the annual plots of ROTIAVE at Ilorin from 2009 to 2012. ROTIAVE values are indicated in color scale. The white space in each of the plots indicates data gap. Ionospheric irregularities occurrence at Ilorin, as indicated by ROTIAVE values, is a postsunset phenomenon. As shown in the plots for 2011 and 2012, irregularities are observed mainly between 1900 LT and 2400 LT. The implication of this is that the large-scale ionospheric irregularities that usually accompany small-scale ionospheric irregularities, which are responsible for the scintillation of transionospheric signals at GNSS frequencies, are more pronounced during postsunset hours. A seasonal trend is also observed. Irregularities were observed between March and November with a minimum around June/July. This is clearly seen in the plots for 2011 and 2012. During this period, especially at the two peaks (i.e., in March and in September), irregularities occur between 1900 LT and 2400 LT.

Figure 3.

Ionospheric irregularity occurrence at Ilorin, Nigeria, for 2009–2012. The ROTIAVE value in TECU/min is indicated in color code. The white space in each plot indicates data gap.

Similarly, solar activity trend is observed in the occurrence of irregularities at this station. An increase in both the frequency and level of irregularities with solar activity can be seen in Figure 4, i.e., from 2009 to 2012. In a more quantifiable way, Figure 4 shows the percentage occurrence of irregularities for each month of the year for (a) 2010, (b) 2011, and (c) 2012. The plot for 2009 is not included because of a very low irregularity occurrence (see Figure 3). In Figure 4, just as shown in the annual plots (i.e., in Figure 3), the number of months with irregularities centered around the equinoxes was observed to increase with solar activity. In terms of the percentage occurrence, this is also obvious except for April, October, and November during which the occurrence levels for 2011 were greater than that of 2012. However, the observation in October and November can still be explained in terms of solar activity level, as the observed monthly average sunspot number (SSN) for 2011 for these two months are higher than those of 2012. The observed monthly average SSN for October is 88.0 and 53.3 for 2011 and 2012, respectively, and 96.7 and 61.4 for 2011 and 2012, respectively, for November.

Figure 4.

Percentage occurrence of large-scale ionospheric irregularities at Ilorin, Nigeria, for (a) 2010, (b) 2011, and (c) 2012.

The two peaks of irregularity seasons were observed at this station during these years, as seen in the plots for 2011 and 2012 in Figures 3 and 4. The peaks occur around the middle of the equinoxes (i.e., one in March and the other in September).

Ionospheric irregularities responsible for GPS scintillations at low latitude are primarily associated with equatorial spread F (ESF) [Kintner et al., 2007]. The occurrence of ESF has been studied, and the frequency of occurrence of equatorial spread F has been found to be higher during solar maximum [e.g., Abdu et al., 1998; Hysell and Burcham, 2002; Mendillo et al., 2000]. The results of Mendillo et al. [2000] showed that ESF occurrence pattern is solar cycle dependent and also that the strength of this pattern does increase with solar activity. Similarly, the results of Kintner et al. [2007], using the data from Sao Jose des Campos, Brazil, showed the dependency of S4 index (scintillation) on F10.7 (solar activity index) and season.

4 Summary and Conclusions

We have used ROTIAVE obtained from 30 s RINEX data to study the occurrence of large-scale ionospheric irregularities at Ilorin, Nigeria. The GPS receiver at Ilorin is a part of a network of receivers called SCINDA. The data used covered a period of 4 years, i.e., between 2009 and 2012. The period is from low-solar activity toward the next solar maximum of the solar cycle 24 expected in 2013. The results obtained in this study showed that the irregularities occur at Ilorin between March and November and that during this period, irregularities occur between 1900 LT and 2400 LT. We observed two peaks of the irregularities, one in March and the other in September. Solar cycle trend is also observed. The number of months for which irregularities occur around the two peaks seems to increase with solar activity. Although the study covered 4 years, the period spanned from solar minimum toward the solar maximum of the solar cycle 24. The results of this study give a picture of the irregularities in the increasing phase of the solar cycle 24. The implication of the results obtained in this study to GNSS application users is that fading, degradation, and, in severe cases, complete loss of GNSS signals should be expected in the equatorial region of the African sector, most especially around Ilorin, during the equinoxes between 1900 LT and 2400 LT. These could increase with the level of solar activity.

In terms of seasonal trend, the results obtained in the current study agrees quite well with those of the other authors for the African sector and is different from those of the American sector as mentioned in section 1. The occurrence season in the African sector is between March and November, while it is from October to March in the American sector. On the solar cycle trend, results of the current study agree quite well with those of the American sector, i.e., irregularities increase with solar activity. This could not be seen in the previous studies in the African sector, as each of the studies mentioned in section 1 used 1 year worth of data.

Acknowledgments

The authors would like to thank Institute for Scientific Research, Boston College, and the U.S. Air Force Research Laboratory for the donation of a dual frequency GPS receiver (as a part of SCINDA) and for their continuous support toward keeping the station running. The authors also appreciate the authority of the University of Ilorin for their support in maintaining the GPS research station located at the Physics Department, University of Ilorin. O.A. Oladipo would like to appreciate Alexander von Humboldt for the foundation for supporting his research by granting him return fellowship during which the work presented in this paper was carried out.

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