Analysis of ionosphere variability over low-latitude GNSS stations during 24th solar maximum period

Accepted Manuscript Analysis of Ionosphere Variability over Low-latitude GNSS Stations during 24th Solar Maximum Period D. Venkata Ratnam, G. Sivavaraprasad, N.S.M.P. Latha Devi PII: DOI: Reference:

S0273-1177(16)30494-X http://dx.doi.org/10.1016/j.asr.2016.08.041 JASR 12894

To appear in:

Advances in Space Research

Received Date: Revised Date: Accepted Date:

28 December 2015 29 August 2016 30 August 2016

Please cite this article as: Venkata Ratnam, D., Sivavaraprasad, G., Latha Devi, N.S.M.P., Analysis of Ionosphere Variability over Low-latitude GNSS Stations during 24th Solar Maximum Period, Advances in Space Research (2016), doi: http://dx.doi.org/10.1016/j.asr.2016.08.041

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Analysis of Ionosphere Variability over Low-latitude GNSS Stations during 24th Solar Maximum Period 1

D. Venkata Ratnam, 2G. Sivavaraprasad and 3N.S.M.P. Latha Devi 1 [email protected] ; [email protected]; [email protected] 1,2 Department of ECE, KLEF, KL University, Vaddeswaram, Guntur Dt, Andhra Pradesh, India 3 Department of Physics, KLEF, KL University, Vaddeswaram, Guntur Dt, Andhra Pradesh, India Corresponding Author: D.Venkata Ratnam, [email protected], Department of ECE, KLEF, KL University, Vaddeswaram, Guntur Dt, Andhra Pradesh, India Abstract— Global Positioning System (GPS) is a remote sensing tool of space weather and ionospheric variations. However, the interplanetary space-dependent drifts in the ionospheric irregularities cause predominant ranging errors in the GPS signals. The dynamic variability of the low-latitude ionosphere is an imperative threat to the satellite-based radio communication and navigation ranging systems. The study of temporal and spatial variations in the ionosphere has triggered new investigations in modelling, nowcasting and forecasting the ionospheric variations. Hence, in this paper, the dynamism in the day-to-day, month-tomonth and seasonal variability of the ionospheric Total Electron Content (TEC) has been explored during the solar maximum period, January-December 2013, of the 24th solar cycle. The spatial and temporal variations of the ionosphere are analysed using the TEC values derived from three Indian low-latitude GPS stations, namely, Bengaluru, Guntur and Hyderabad, separated by 13-18 degrees in latitude and 77-81 degrees in longitude. The observed regional GPS-TEC variations are compared with the predicted TEC values of the International Reference Ionosphere (IRI-2012 and 2007) models. Ionospheric parameters such as Vertical TEC (VTEC), relative TEC deviation index and monthly variations in the grand-mean of ionosphere TEC and TEC intensity, along with the upper and lower quartiles, are adopted to investigate the ionosphere TEC variability during quiet and disturbed days. The maximum ionospheric TEC variability is found during March and September equinoxes, followed by December solstice while the minimum variablitity is observed during June solstice. IRI models are in reasonable agreement with GPS TEC but are overestimating during dawn hours (01:00-06:00 LT) as compared to the dusk hours. Higher percentage deviations are observed during equinoctial months than summer over EIA stations, Guntur and Hyderabad. GPS TEC variations are overestimated during dawn hours for all the seasons over Bengaluru. It has also been observed that positive storm effect (enhancement of TEC) is observed during the main phase of the March storm, 2013 (March 16-18, 2013) while both positive and negative storm effects (depletion of TEC) are registered during the main phase of the June storm, 2013 (June 28-30, 2013) at Bengaluru and Guntur, respectively. IRI-2012 model has slightly large discrepancies with the GPS-VTEC compared with the IRI2007 model during the June storm, 2013 over Guntur station. This analysis highlights the importance of upgrading the IRI models due to their discrepancies during quiet and disturbed states of the ionosphere and developing an early warning forecast system to alert about ionosphere variability. Keywords— GNSS, GPS, Ionosphere, TEC, Ionosphere Variability, IRI Model. 1. INTRODUCTION The Global Navigation Satellite Systems (GNSS) such as Global Positioning System (GPS), Galileo, GLONASS, BeiDou, and Indian Regional Navigation Satellite System (IRNSS) have been used for providing position, velocity and time information in all weather conditions. The ionosphere, occupying an altitude of 50-1000 km, is one such dominant layer of atmosphere challenging the Communication, Navigation and Surveillance (CNS) applications. The interplanetary space conditions, such as solar activity, geomagnetic activity, meteorological influences and coupling of thermosphere and magnetosphere contribute to the complexity of the ionosphere. The physical and chemical parameters of the ionosphere such as temperature, composition, and number of ions and electrons change with respect to geographic location, time of the day, day of the season, 1

season of the year, and solar and geo-activity (Rees, 1989). Hence, the study of temporal and spatial variations in the ionosphere indicates the requirement of new investigations in understanding, modeling and forecasting the dynamic ionospheric variations over low-latitude regions. The International Reference Ionosphere (IRI) is one of the standard empirical models providing TEC data (Bilitza, 2001). IRI is an ISO (International Standardisation Organisation) project of the Committee on Space Research (COSPAR) and International Union of Radio Science (URSI). IRI model provides improved and updated monthly averages of critical ionospheric parameters as a function of geographical location, local time, height, and sunspot number (Bilitza, 200l, Bilitza et al., 2014). IRI model parameters are derived based on the availability of ground and in situ measurements. The IRI project inception since 1968 and the enhanced features of the model version, IRI-2012, over previous versions have been reported by Bilitza et al. (2014). The IRI model, IRI-2012, is accessible at irimodel.org. It gives the TEC by the integration of electron density from the lower boundary of 60 km to an upper boundary of 2,000 km (Bilitza, 2001). IRI provides three topside electron density profile options: NeQuick, IRI-2001, and IRI-01-Corr; available bottom-side thickness options are: Bil-2000, Gul-1987, and ABT-2009 to control TEC and the electron density profile (Coisson et al., 2008). The upper side electron density profile options are expressed by various numerical functions. For example, IRI-2001 contains piecewise constant gradients based on the approach of Skelton profile (Booker, 1977). The IRI-NeQuick is given by semi-Epstein layer function (Coisson et al., 2006). The topside electron density profile decreases exponentially with altitude with these topside options. For the topside options such as IRI-NeQuick and IRI-Corr, decrement in the electron density profile with respect to altitude is more rapid than in the case of IRI-2001 (Bilitza, 2001). The monthly, seasonal and annual diurnal variations in TEC during the low solar activity period of 2005-2007, 2007-2008 and 2006-2009 have been investigated over the Indian equatorial and low-latitude regions by several authors (Bagiya et al., 2009; Sanjay Kumar and Singh, 2009; Vishal Chauhan et al., 2011). The study of variability in ionospheric TEC using observed GPS-TEC near the Equatorial Ionisation Anomaly (EIA) crest in Chinese, equatorial Nigerian and Malaysian stations during low and moderate solar activity periods reveal the spatial and temporal variability of the ionosphere. These investigations indicate that the highest TEC values are observed during the equinoctial months while the lowest are encountered during the summer season. It is also demonstrated that TEC values differ based on the geographical location and show appreciable variability during different solar activity periods (Wengeng Huang et al., 2013; Adewalea et al., 2013; Radzi et al., 2013). The distribution and characteristics of TEC variations due to solar and geomagnetic activities at equatorial, lower, middle and high latitudes are investigated by several researchers (Lanyi and Roth, 1988; Coco, 1991; Goodwin et al., 1995; Ho et al., 1996; Mannucci et al., 1998; Brunini et al., 2003; Wu et al., 2004; Mukherjee et al., 2010; Bhuyan et al., 2007). The seasonal variations of TEC also depend on the solar zenith angle, thermospheric composition and the ratio of O/N2, as discussed in the literature (Rishbeth and Setty, 1961). In later studies, the diurnal and seasonal variations of TEC predicted by the IRI-2000 model are compared with the ionogram and GPS TEC observations. It is found that IRI is overestimating both ionogram and GPS TEC values (Mosert et al., 2007). The seasonal variations of TEC over low-latitude stations are compared, and the validation of the IRI-2007 model is conducted during the lowest phase of the solar activity period (Praveen et al., 2010). It is revealed that the estimations of IRI model have seasonal and longitudinal discrepancies in TEC. The TEC derived from GPS, and International GNSS Service (IGS) are compared with the IRI-2007 model-predicted TEC values over an equatorial region in Thailand (Kenpankho et al., 2011). It is found that IRI underestimates GPS with a maximum difference of 15 TECU during day times and a minimum variation of 5 TECU during night times. The studies of ionospheric variability and validation of different IRI models over equatorial and lowlatitude stations are carried out by numerous authors (Kouris and Fotiadis, 2002; Kouris et al., 2004; Oyekola and Fagundes, 2012; Sanjay Kumar et al., 2014; Saranya et al., 2015). Recently, several investigations have been conducted to characterize the ionospheric TEC patterns and discrepancies/consistencies of the IRI-2012 model during the ascending phase of the 24th solar cycle over different equatorial and low-latitude regions (Tariku, 2015a, 2015b; Sanjay Kumar et al., 2015; Rathore et al., 2015). It is reported that the IRI-2012 model has not responded during geomagnetic storm time, and the largest deviations (overestimated) are observed during the low solar activity phase compared to the high solar activity phase (Tariku, 2015b). Sanjay Kumar et al. (2015) compared the TEC estimation of IRI models (IRI-2012 and IRI-2007) over Indian equatorial (Bengaluru) and EIA (Lucknow) regions during 2

2012-2013. It is reported that the IRI model is unable to recognize the absence of winter anomaly and the performance of the IRI-2012 model is better than the IRI-2007 model over equatorial region compared to the EIA region. Statistical analysis is carried out on the IRI-2012 model performance during 2012-2013 over Varanasi (Geographic: 25°16′ N, 82°59′ E; Geomagnetic: 14°55′ N, 154° E), a low-latitude Indian station (Rathore et al., 2015). It is reported that their results obtained a good correlation coefficient of approximately 0.9 and found 25-70% of root mean square deviations (RMSD) for diurnal comparisons during both 2012 and 2013. The latest version of IRI, International Reference Ionosphere Extended to Plasmasphere (IRI-Plas) model covers the range up to a GPS orbital height of 20,000 km and, thus, is appropriate for comparison with GPS-TEC (Gulyaeva et al., 2011; Sezen et al., 2013). The performance of IRI-Plas model in estimating STEC is compared with the measured STEC value derived from GPS during the period of ionospheric disturbances due to geomagnetic storms and earthquakes (Arikan et al., 2016). IRI-Plas model is used over low-latitude and equatorial regions to exclude the contributions of Plasmaspheric Electron Content (PEC) from the GPS-observed TEC in order to compare measured TEC with TEC derived from IRI-2012 (Akala et al., 2015; Karia et al., 2015). Akala et al. (2015) have evaluated the accuracy of the IRI-2012 model during 2010-2013 ascending phase of solar activity over an African equatorial region, Ethiopia. It is observed that the seasonal percentage contribution of PEC to GPS-TEC is maximum during the December solstice and minimum during the June solstice. Their results referred that TEC values are proportionally varying with respect to solar activity, and the NeQuick topside electron density option performed well compared to the other two topside options (IRI-2001, and IRI-01-Corr). The performance of the IRI-2012 model is evaluated by Karia et al. (2015) over the crest of EIA region, Surat, India during 2009-2012. It is noticed that TEC estimation of the IRI-2012 model is well for the dusk (18:00 LT) and noon (12:00 LT) hours during 20102012, but during the year 2009 it shows discrepancies with the measured TEC. Significant fluctuations in TEC response have been observed by various investigations carried out during different geomagnetic storms over low-latitude and equatorial regions (Rama Rao et al., 2009; Sanjay Kumar et al., 2012; Chakraborty et al., 2015). In this paper, the seasonal, temporal and spatial variability of ionosphere TEC has been investigated during the high solar activity period of the 24th solar cycle (2013). The day to day, month to month and seasonal variations of ionospheric TEC over three low-latitude stations are presented and compared with IRI-2007 and IRI-2012 models. The geomagnetic storm effect on both the measured and modeled VTEC patterns has also been assessed. The data and method of analysis have been presented in Section 2. In Section 3, the results and discussion of TEC variability during quiet and disturbed days has been outlined. Lastly, the conclusion has been given in Section 4. 2. Analysis of TEC Data and Method of Processing The analysis of GPS-TEC data has been conducted for a period of one year, January-December 2013, which is the solar maximum peak of the 24th solar cycle (Rz = 58 - 76). The data for analysis is collected from three low-latitude GNSS stations enlisted in Table1 and shown in Figure 1. The ionospheric TEC data over KL University, Guntur station, has been obtained from a multi-frequency GNSS Ionospheric Scintillation and TEC Monitor (GISTM) receiver (Model: GPStation-6, Make: NovAtel). The GPS data of Bengaluru and Hyderabad stations are downloaded from Scripps Orbit and Permanent Array Center (SOPAC) website http://sopac.ucsd.edu/. The GPS data are recorded in the RINEX format, which is converted into VTEC by the planar fit ionospheric grid model (Sarma et al., 2009). To avoid the mapping function error, satellites with more than 500 elevation angle measurements are considered for converting slant to vertical TEC measurements (Rama Rao et al., 2006a, 2006b). In the present analysis, NeQuick option is chosen for the topside electron density profile for both the IRI-2012 and IRI-2007 models. The results of the three stations are compared with their corresponding IRI models, IRI - 2007 and IRI – 2012, to validate them.

3

S.No Station Name 1

Bengaluru

2

Guntur (KL University) Hyderabad

3

Geographical Latitude in degrees N 13.02

Table.1 Details of the three GNSS stations Geomagnetic Geographical Geomagnetic Latitude in Longitude in Longitude in degrees N degrees E degrees E 4.40 77.57 150.77

16.37

7.50

80.37

153.76

17.41

8.87

78.55

152.09

Operated by IGS GNSS station KL University IGS GNSS station

20oN

*Hyderabad *Guntur (KLU)

16o

Latitude(D egrees)

N

*Bengaluru 12oN

***** Geomagnetic Equator******************** ******************** ********** 8 oN ***** ***************

4 oN

72oE

78oE

75oE

81oE

84oE

Longitude (Degrees)

Fig. 1.The network of GNSS stations for the analysis of low-latitude ionosphere variability. The relative deviation in the ionospheric TEC about monthly-median values can be considered as a measure/indication of ionospheric variability. The relative TEC parameter is calculated to study day-to-day, monthly and seasonal variations of the ionosphere using Eq. (1) given by (Kouris and Fotiadis, 2002),

dX =

X − Xm Xm

(1)

where X denotes the hourly daily values of TEC, Xm represents the monthly-median value of TEC representing the quiet state of the ionosphere, and dX is the relative deviation of ionospheric TEC. The above equation is used to calculate the deviation quantity of ionospheric conditions from their quiet state to estimate their current state, i.e., ionospheric variability. The decile factors (lower quartiles and upper quartiles) at each hour of each month of the year at three low-latitude stations have been analysed to understand ionosphere variability and the corresponding predictions made by IRI models. The grand TEC variations are analysed using Eq. (2) and (3), respectively. 1 D nh TECgrand − mean = (2) ∑ ∑ TECday ,h nh D day =1 h =1

TECgrand −int ensity =

2⎤ 1 ⎡ D nh ⎢ ∑ ∑ (TECday ,h − TECav ) ⎥ nh D ⎣ day =1 h =1 ⎦

(3)

where D refers to day, nh denotes the number of TEC data per day, h refers to hour. The TECgrand − mean represents the monthly grand-mean, and TEC grand −int ensity represents the monthly grand-variation intensity. 4

The grand TEC variations, TECgrand − mean and TEC grand −int ensity , describe the overall properties of the seasonal variations in the ionospheric TEC (Wu et al., 2012). Later, based on the hourly averages of each season, the accuracy of IRI model is assessed from the percentage of deviation (%Dev). The percentage deviation between the GPS-VTEC values and IRI models (IRI-2012 and IRI-2007) can be calculated by (Akala et al., 2015), ⎛ GPSTEC − IRITEC ⎞ % Dev = ⎜ (4) ⎟ ×100 GPSTEC ⎝ ⎠ where GPSTEC refers to the GPS-TEC values, and IRITEC refers to the derived TEC from IRI model. Then, the root mean square error (RMSE) values have been measured between the GPS-TEC and TEC derived from IRI models using the Eq. (5). N 1 RMSE = ∑ (GPSTEC − IRITEC )2 (5) TEC =1 N where N denotes the number of observations. 3. Results and Discussion 3.1. Low-latitude Ionospheric TEC Variation The ionospheric VTEC data are considered to map TEC observations over three low-latitude stations for the year 2013. Figure 2 depict the contour diagrams of the diurnal ionospheric TEC variations over Bengaluru, Guntur, and Hyderabad stations. It is observed that variation of TEC diurnal pattern exhibited a steady rise from pre-sunrise period to a maximum peak in the TEC value during the afternoon, and then fell to a minimum value just before sunset, with the local times differing by ±1-2 hours (Figure 2). During the solar maximum period, the diurnal VTEC peak values are found to be between 10:00-14:00 LT and sometimes up to 16:00 LT; they reached a minimum at dusk, around 18:30 LT. The maximum ionospheric variability over the low-latitude stations is found between 10:00-13:00 LT over Bengaluru, 08:00-12:00 LT over Guntur, and 09:00-13:00 LT over Hyderabad, which represents the non-linear spread of TEC (Figure 2). Further, VTEC has been reported to reach its peak earlier (10:00 LT) during winter than during summer (11:00 LT) and Equinox (12:00 LT) months. VTEC exhibits a usual trend of the day-to-day variation of minimum in the early hours (06:00 LT) and maximum between 10:00 LT and 12:00 LT (Figure 2). The reason could be the earth’s self-rotation and its revolution around the sun in its elliptical orbit, which affect ionosphere variability. The axis of the earth is tilted 66.50 to the plane of the earth’s orbit, which causes changes in the length of day and night (Sampad et al., 2015). The position of the earth during its revolution around the sun determines the seasons and amount of solar energy received by the two hemispheres. The effect of sunrise and sunset causes the production (photo ionisation) and loss (recombination) of electrons in the ionosphere, which can be observed with respect to local time in the contour plots (Figure 2). During winter, the duration of day is shorter than summer days. Hence, the production rate of the electrons reaches its peak earlier in winter when compared to summer months. The annual ionospheric TEC pattern variations over Bengaluru, Guntur, and Hyderabad depict the slight increment of TEC distribution from Bengaluru to Hyderabad (Figure 2). It is also noticeable from Figure 2 that the TEC variations of the three stations are similar with fewer discrepancies during pre-sunrise and after sunset hours, but differ during midday in all the seasons. This may be attributed to the increase in solar radiation and electrodynamics related to ExB drifts; EIA at low latitudes cause the non-linear distribution of electrons from dip equator to low latitudes (Sampad et al., 2015). Thus, the increment in the electron density distribution over Hyderabad compared to Bengaluru and Guntur describes the uplifting of TEC due to ExB drifts and fountain effect. The maximum TEC variability has been found in March and September equinoxes as compared to the June and December solstices (Figure 2).

5

Fig. 2.The annual diurnal variations of VTEC over three stations during the year 2013.

Fig. 3.The annual diurnal variations of VTEC derived from the IRI-2007 and IRI-2012 models over the three stations during 2013. Figure 3 shows diurnal TEC variations predicted by the IRI-2012 and IRI-2007 models of the three stations enlisted in Table 1. It can be observed from Figures 2-3 that the IRI models are good enough to follow the spatial variations but have large discrepancies over three stations. The temporal variations of IRI models are following the trends of observed GPS-TEC variations with large discrepancies during dawn hours (00:01-06:00 LT) compared to dusk hours (18:00 LT) while the daytime TEC estimation of IRI is in good agreement (Figure 3). The maximum deviation of IRI model-predicted TEC has been found during the March equinox as compared to the September equinox for Guntur station and during September equinox for 6

Hyderabad station, but the range of IRI deviations over Bengaluru are 15-30 TECU for all seasons of the solar maximum period. 3.2. Monthly Spatial and Temporal Variations of Relative TEC This study is further extended to collate month-wise ionospheric relative TEC variations for the three stations to understand the local temporal TEC variations of low-latitude ionosphere during the solar maximum period. Temporal and spatial differences are observed in the variations of the relative deviations of TEC over the three regions, calculated using Eq. (1). Figure 4 shows the temporal variations of the relative deviations of TEC in contour diagrams for all the three low-latitude stations for the month of April 2013.

Fig. 4. Temporal and spatial relative deviations of VTEC during April, 2013. 7

The positive variability is higher during 08:00-16:00 LT with a peak value around 12:00 LT while negative variability can be observed during early morning hours and during 18:00-24:00 LT. The difference between positive and negative variability is around 2 TECU. The relative TEC variations over Hyderabad are the highest compared to Bengaluru and Guntur during April 2013, as shown in Figure 4. The increment in electron density distribution over EIA station, Hyderabad as noticed in Figure 2, is the reason for enhancements in the relative deviations over Hyderabad. It is, therefore, apparent that the relative TEC deviations are ascending from equatorial zone to EIA zone along the magnetic field lines. The relative deviations of IRI-predicted TEC values do not follow the actual observations of GPS-TEC over the three low-latitude GNSS stations. It can be observed from Figure 4 that the deviation measured by the IRI-2012 model is 0.5-1 TECU less than the observed relative deviations of TEC during April 2013. The estimation of relative ionospheric TEC by the IRI-2012 model is more accurate than the IRI-2007 model, as shown in Figure 4. 2 Bengaluru IRI-2007 IRI-2012

R ela tiv e D ev ia tio n s (d T E C )

1 0 -1 2

Guntur (KLU) IRI-2007 IRI-2012

1 0 -1 2

Hyderabad IRI-2007 IRI-2012

1 0 -1

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Months (Jan-Dec, 2013)

Fig. 5. The monthly upper and lower quartiles of the VTEC values during the solar maximum period of the year, 2013. The monthly relative deviations of VTEC for each station are compared with the VTEC derived from the IRI models, as shown in Figure 5. It illustrates the upper and lower quartiles for each hour of every month during the 24th solar maximum period, 2013. The maximum relative deviations are found during May and August months over Bengaluru, during January, June and December months over Guntur and during June and August over Hyderabad. It can be analysed from Figure 5 that the TEC variability (quartiles) lie in the range of -1 to1.2 TECU for the Bengaluru station, -1 to -1.4 TECU for the Guntur station and -1 to -1.8 TECU for the Hyderabad station for 25-75% of the time every month. The relative deviations of TEC show that the variability of the ionosphere is more predominant during the equinoctial month (August) than summer. The variability (quartiles) of IRI-derived TEC over the three low-latitude stations is smoother, indicating the necessity of improvement in the IRI model accuracy. The trend of IRI model relative deviations follows the temporal variations of ionosphere TEC as well as the spatial (latitudinal) variations (Figure 5). However, the relative deviations of modeled VTEC values show a discrepancy of 0.5-1 TECU over the three low-latitude GNSS stations. 3.3. Seasonal Variations of TEC The monthly grand-mean of VTEC and monthly grand variations of VTEC intensity are calculated using Eq. (2-3), to examine the seasonal equinox (March and September) and solstice (June and December)based variations of the ionosphere. It is observed from Figure 6 that the highest grand-mean of VTEC are observed in the equinoctial months (October) while the lowest VTEC is seen during June and December solstice over all the three stations. It is apparent from Figure 6a that the monthly grand-mean of VTEC for Guntur and Bengaluru are coinciding with each other. The spatial (latitudinal) grand-mean of VTEC during equinox periods is higher by 10 TECU while during solstice periods it is higher by 5 TECU for the 8

Hyderabad station when compared with the Bengaluru and Guntur stations. The maximum value of grandmean VTEC is registered during equinox (35-40 TECU) and minimum during June solstice (25 TECU) over the Hyderabad station. Figure 6b shows the grand variation of VTEC intensity for all the months of 2013. The highest grand-variation of VTEC intensity is found over the Hyderabad station, followed by Guntur and Bengaluru, during the December solstice (November) and September equinox (October). The measured grand-mean and intensity variations of VTEC values are in ascending phase during March and September equinoxes and descending phase during June and December solstices (Figure 6). Thus, these results represent the seasonal anomaly, which is due to the change in the direction of neutral winds and composition of atmospheric species. The reason for the lowest values of TEC during June solstice is the reduced recombination rate of electrons during winter due to asymmetry in the heating of hemispheres, which causes the transfer of neutral winds from summer to the winter hemisphere (Rishbeth and Setty, 1961). Thus, depletion of recombination in winter results in increased TEC in winter as compared to the summer (June) solstice. The propagation flow of longitudinal (meridional) component of neutral winds, which are against the plasma diffusion process from magnetic equator, and decrease in atmospheric species (O/N2 ratio) during summer solstice may also cause the diminished electron concentration in June solstice (Wu et al., 2004; Bhuyan et al., 2006). The reason for obtaining maximum VTEC grand-mean and intensity values during equinoctial months may be attributed to the meridional winds that flow towards poles from equator and cause high ionisation (Wu et al., 2004; Bhuyan et al., 2006). Monthly grand mean of TEC

G ra n d M ea n o f T E C (T E C U )

45

Guntur (KLU) Bengaluru Hyderabad KLU IRI-2007 KLU IRI-2012 Ben IRI-2007 Ben IRI-2012 Hyd IRI-2007 Hyd IRI-2012

40

35

30

25

20 Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Month of the Year,2013

(a) Monthly grand variation of TEC intensity

Grand intensity of TEC (TECU)

28

Guntur (KLU) Bengaluru Hyderabad KLU IRI-2007 KLU IRI-2012 Ben IRI-2007 Ben IRI-2012 Hyd IRI-2007 Hyd IRI-2012

26 24 22 20 18 16 14 12 10 Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Month of the Year,2013

(b) Fig. 6. The seasonal variations of ionosphere over low-latitude regions (a) monthly grand-mean of VTEC (b) monthly grand variation of VTEC intensity during the year 2013. 9

% Dev

% Dev

Both IRI models are overestimating the monthly grand-mean TEC values and underestimating the grand TEC intensity variations. IRI-2012 model is able to estimate the grand-mean TEC values for July, November and December months with relatively little discrepancy for Hyderabad. The values of the monthly grand-mean of TEC and variation of TEC intensity and corresponding values of IRI models reflect the electron density variations, as shown in Figures 2-3. Thus, it is observed from Figures 2-3 and Figure 6 that double peak structures occur during the equinoctial months at all the stations, which indicate the semiannual variation of TEC values over equatorial and low-latitude regions. The seasonal percentage deviation of VTEC derived by IRI models to the GPS-VTEC during the solar maximum period for Bengaluru, Guntur and Hyderabad stations correspondingly is shown in Figures 7-9. The positive and negative percentage deviations illustrate the underestimation and overestimation of observed TEC respectively. IRI models are overestimating the observed GPS-TEC significantly during the early-morning hours (01:00 -06:00 LT) and post sunset hours during all the seasons over all the three stations. Moreover, it is remarkable from the Figure 7 that at 01:00 LT, the overestimation of IRI models is extended up to 200-845% over Bengaluru, 100-200% over Guntur and 100-500% over Hyderabad. Ezquer et al. (1995) reported that the early-morning deviations could arise due to shape of electron density profile is not well predicted by the IRI model. IRI models predicted slight underestimations and reduced deviations from observed GPS-TEC during the daytime for all the seasons over three stations. Large percentage deviations are observed during equinox seasons followed by December solstice than June solstice for all the three stations. The similar kinds of observations have been reported by Akala et al. (2015) over an equatorial station, Addis Ababa, Ethiopia and Karia et al. (2015) over EIA station, Surat, India. The high percentage deviations of IRI models could be attributed to more plasmaspheric contribution in GPS TEC which changes with season, latitude and local time (Balan et al., 2002; Cherniak et al., 2012; Karia et al., 2015, Akala et al., 2015). Table 2 shows the seasonal variations of RMSE values of IRI models to measured GPS-TEC over three stations during the solar maximum period, 2013. IRI-2007 model has shown significant RMSE over Bengaluru than IRI-2012 model. However, IRI-2012 has more RMSE values than IRI-2007 over EIA regions, Guntur and Hyderabad during March and September equinox seasons. Bengaluru 100 100 Jun SOL Mar EQU 0 0 -100 -100 -200 -200 -300 -300 -400 -400 -500 -500 IRI-2012 -600 -600 IRI-2012 -700 IRI-2007 -700 IRI-2007 -800 -800 -900 -900 -1000 -1000 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 10 12 14 16 18 20 22 24 LT (Hrs) LT (Hrs) (a) (b)

10

100 Dec SOL 0 -100 -200 -300 -400 -500 -600 IRI-2012 -700 IRI-2007 -800 -900 -1000 0 2 4 6 8 10 12 14 16 18 20 22 24 LT (Hrs) (c) (A) Guntur (KLU) % Dev

% Dev

100 0 Sep EQU -100 -200 -300 -400 -500 -600 -700 -800 -900 -1000 0 2 4 6

100

IRI-2012 IRI-2007

8 10 12 14 16 18 20 22 24 LT (Hrs) (d)

100 Jun SOL % Dev

Mar EQU

% Dev

0

-100

0

-100

IRI-2012 IRI-2007

IRI-2012 IRI-2007 -200

0 2 4 6 8 10 12 14 16 18 20 22 24 LT (Hrs)

-200

0

2

4

6

(a)

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(C) Fig. 7. The percentage of deviation between the IRI model (IRI-2012 and 2007) predicted VTEC and observed GPS-VTEC over (A) Bengaluru (B) Guntur and (C) Hyderabad stations, for 2013 (a) during March equinox (b) during June solstice (c) during September equinox (d) during December solstice. Table. 2 Seasonal variations of RMSE values of the both IRI models (IRI-2012 and 2007) to observed GPSTEC S. No GPS Station IRI Model Mar EQU Jun SOL Sep EQU Dec SOL 1 Bengaluru IRI-2007 10.04 9.49 10.18 10.61 IRI-2012 8.91 7.91 9.02 9.45 2 Guntur (KL IRI-2007 8.50 9.18 9.09 8.76 University) IRI-2012 9.98 7.14 10.06 9.05 3 Hyderabad IRI-2007 10.61 7.76 10.58 11.20 IRI-2012 11.31 7.63 11.37 11.14 3.4. Effect of Geomagnetic Storm on TEC Variations Two geomagnetic storms occurred on March 17, 2013 and June 29, 2013 in the 24th solar maximum period. In the present section, the variations in the VTEC values obtained from equatorial region, Bengaluru and EIA region, Guntur GPS stations are compared with their corresponding VTEC values derived from the IRI models during these disturbed geomagnetic days. The storm option for IRI models (IRI-2012 and IRI2007) have been switched ‘on’ for analyzing their performance during geomagnetic storm (disturbed) days. 12

3.4.1. Storm 1: March 16-18, 2013 Figure 8 depicts analogy between the GPS VTEC values and the model-predicted (IRI-2007 and IRI-2012) VTEC response with respect to the Dst (Disturbance storm time) index during the storm period (March 16, 2013 to March 18, 2013). The Dst index values are obtained from http://omniweb.gsfc.nasa.gov/form/dx1.html. The VTEC fluctuations over Guntur and Bengaluru are plotted in Figure 8b-c. A Coronal Mass Ejection (CME) from the sun erupted with solar wind speed of 700 km/s on March 15, 2013, reaching the earth's magnetic field at 06:00 UTC (Coordinated Universal Time) (11:30 LT) on March 17, 2013. It is a minor S1 solar radiation storm caused a moderately strong geomagnetic storm. The sunspot number during March 2013 storm period is 58. During the pre-storm day, i.e., on March 16, 2013, over Guntur (KLU) station, VTEC started to increase from 4.66 TECU at 00:01 LT, and reached 60.52 TECU at 12:00 LT. The peak value of background TEC over Bengaluru is 50.4 TECU. The Dst index values are consistent during the initial phase of the storm (March 16, 2013) as shown in Figure 8a. During the storm day (main phase of the strom), i.e., on March 17, 2013, Dst index decreased from -12 nT to -132 nT, during early hours to midnight, representing a strong storm. The continuous decrement in the Dst index represents the strength and duration of the geomagnetic storm during the main phase, as shown in Figure 8a. The VTEC values at 12:00 LT reached 59.04 TECU and 67.12 TECU over Bengaluru and Guntur, respectively. During the storm day (March 17, 2013), it can be noticed that there is an enhancement in VTEC, which is more compared to the pre-storm day (March 16, 2013) at both the stations, Guntur (Figure 8b) and Bengaluru (Figure 8c). It is apparent from Figure 8b-c that there is an increase in peak VTEC value (9 TECU) over the Bengaluru station, followed by Guntur (7 TECU) during the main phase of March storm. The highest peak of Dst index reached -132 nT at 20:00 UT on March 17, 2013 (01:30 LT on the post-storm day, March 18, 2013). Slowly, the storm intensity, Dst index reduced to -106 nT at 05:30 LT and depleted further for quiet day values during storm recovery phase (March 18, 2013). The VTEC peak values over Bengaluru, and Guntur are found as 64 TECU and 64.36 TECU, respectively during the recovery phase of March storm, 2013.

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(c) Fig. 8. (a) Observations of Dst index on March 16, 2013, March 17, 2013, and March 18, 2013, variations of GPS VTEC, derived VTEC from IRI-2012 and IRI-2007 models, (b) at Guntur and (c) at Bengaluru during the March 2013 geomagnetic storm period. Further, it is illustrated from Figure 8b-c that the patterns of GPS-TEC have shown fluctuations due to the occurrence of geomagnetic storm, whereas the VTEC values derived from IRI (IRI-2012 and IRI2007) models have shown large deviations compared with GPS-TEC over both stations. Moreover, during the main phase of March storm, IRI models do not capture the positive storm effect on GPS-TEC over both Guntur and Bengaluru. IRI models are overestimating during dawn and dusk hours and underestimating during 12:00-14:00 LT hours on March 17, 2013 at both the EIA region, Guntur and equatorial region, Bengaluru. The patterns of deviations between the GPS-TEC and IRI modeled TEC values are clearly noticeable from the hourly TEC variations during the initial and recovery phases of the storm (Figure 8b-c). In addition, it is observed that the prediction of VTEC values by IRI models during disturbed conditions differs by approximately 8-12 TECU over the Bengaluru and Guntur stations (Figure 8b-c). 3.4.2. Storm 2: June 28-30, 2013 The earth’s geomagnetic field is disturbed by a high-speed stream of CME of the sun on June 29, 2013. Figure 9 represented the variation of GPS VTEC over Guntur and Bengaluru, and VTEC derived from IRI-2012 and IRI-2007 models with respect to the Dst index during the storm period (June 28, 2013 to June 30, 2013). The sunspot number during June 2013 storm period is 52.5. GPS - VTEC over the Guntur station measured 9 TECU at 00:01 LT during the pre-storm day, June 28, 2013 (Figure 9b). At 12:00 LT, VTEC attained the value of 47.74 TECU. At 22:00 LT, VTEC measured 8.3 TECU during the initial phase of the storm. During this initial phase, the peak values of VTEC values over Bengaluru is found as 40.96 TECU (Figure 9c). During the storm day (main phase), i.e., June 29, 2013, the minimum of Dst index values reached -98 nT at 12:30 LT. From Figure 9, the depletion of TEC (negative storm effect) can be observed during the main phase of the storm over EIA region Guntur, but TEC enhancement (positive storm effect) over Bengaluru during the storm day. The enhancement of peak TEC values over Guntur (53.8 TECU), and suppression over Bengaluru (44.33 TECU) may also be noticed during the recovery phase of the storm on June 30, 2013 respectively (Figure 9). Such case of mixed response of GPS-TEC over EIA region (negative storm effect) and equatorial region (positive storm effect) during storm period on April 24, 2012 has been analyzed by Chakraboorty et al. (2015). Pedatella et al. (2009) has reported that the occurrence and magnitude of the negative and positive storm effects is dependent upon the local time, latitude, and phase of the storm.

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(c) Fig. 9. (a) Observations of Dst index on June 28, 2013, June 29, 2013, and June 30, 2013, variations of GPS VTEC, derived VTEC from IRI-2012 and IRI-2007 models (b) at Guntur and (c) at Bengaluru during the June 2013 geomagnetic storm period. From Figure 9, it may be seen that during the quiet and intense space weather events such as geomagnetic storms, the accuracy of the IRI models differs depending on the geographic location. The IRI models are not able to predict the negative storm response of GPS-TEC over EIA region, Guntur and positive storm response of GPS-TEC over equatorial region, Bengaluru during the main phase (June 29, 2013) of June storm (Figure 9b-c). It is observed that the IRI models are overestimating the GPS-TEC at EIA region, Guntur and underestimating the GPS-TEC at equatorial region, Bengaluru during the main phase of storm day. Several authors have studied the validation of IRI model during the various geomagnetic storms over different equatorial and low latitude regions (Sanjay Kumar et al., 2014; Arunpold et al., 2014, Chowdhary et al., 2015; Panda et al., 2015; Tariku et al., 2015b). It has been reported that modeled VTEC derived from IRI (IRI-2012) model tends to remain smooth during the geomagnetic storm period. At the 15

Guntur station, hour-to-hour VTEC values derived from the IRI-2012 have been overestimated more than the IRI-2007 model from the observed VTEC for all the three phases of the storm during 00:01-11:00 LT. Further, the patterns of derived VTEC with the ‘storm on’ option for IRI-2012 and IRI-2007 models are found to be closer to each other and following the GPS-TEC values for remaining hours, as shown in Figure 9b. During the main phase of June storm, the IRI-2012 and IRI-2007 models are overestimating the observed VTEC at Bengaluru during dawn and dusk hours and underestimating during 12:00 LT (Figure 9c). The IRI models are overestimating the actual VTEC by approximately 5-10 TECU at the Guntur station and underestimating the measured VTEC by approximately 2-6 TECU at Bengaluru during the main phase of the June storm (June 29, 2013). It is reported that the GPS-TEC is underestimated by IRI model towards the equatorial stations (Panda et al., 2015). 4. Conclusions In this paper, the temporal (monthly as well as seasonal) and spatial variability of the ionosphere has been investigated using GPS-based TEC patterns obtained from GPS receivers at three low-latitude stations during the solar maximum period, 2013. Also, the GPS-based TEC observations have been compared with TEC data derived from IRI-2007 and IRI-2012 models during both geomagnetic quiet and disturbed days. Following are the key observations. i. ii.

iii.

iv. v.

vi. vii.

viii.

ix.

The results illustrate that the maximum peak values of TEC are found during 08:00-13:00 LT and minimum values during dawn and dusk hours over equatorial and low-latitude stations. The temporal and seasonal variations of TEC over low-latitude stations replicate the spatial differences in the distribution of electron density. The increment in the electron density distribution and TEC values over EIA stations, Hyderabad and Guntur compared to equatorial station, Bengaluru describes the uplifting of plasma along the magnetic - field lines due to ExB drifts, EIA and fountain effect. The temporal variations of the IRI models are following the trends of observed GPS-TEC patterns with large discrepancies during dawn hours (00:01-06:00 LT) compared to dusk hours (18:00 LT) while the daytime estimation of TEC is in good agreement. The relative deviations of ionospheric TEC show that the variability of the ionosphere is more predominant during the equinoctial month (August) than summer solstice. The highest grand-mean of VTEC is observed in the equinoctial months (October) while the lowest VTEC is seen during June and December solstice, whereas the grand variation of TEC intensity is maximum during November over the three stations. The measured grand-mean and intensity variations of VTEC values are in the ascending phase during March and September equinoxes and descending phase during June and December solstices. The double peak structures in VTEC patterns at all the stations indicate the semi-annual variations of low-latitude ionosphere during the 2013 solar maximum period. The IRI models have shown large discrepancies during early morning hours and post-sunset hours, while fewer deviations have observed during the daytime over Indian low latitude regions of considered. Both enhancements and depletions in measured TEC and discrepancy of IRI models’ performance are found during geomagnetic storms that occurred in 2013. The ‘storm on’ option of the IRI-2012 model overlapped with IRI-2007 (‘storm on’ option) over Guntur and Bengaluru during March geomagnetic storm, 2013 except during the peak hours while they differ during June storm, 2013. However, VTEC derived from IRI models do not respond to storm effects and remain smooth. The IRI-2012 model is in good agreement with the GPS-TEC of the respective stations compared to the IRI-2007 model during both geomagnetic quiet and disturbed days. Nonetheless, the IRI2012 model has shown poor performance than IRI-2007 model over EIA regions, Guntur and 16

Hyderabad during the March and September equinoxes. Hence, further upgrading in the IRI models is necessary, particularly in the Indian low-latitude and EIA regions. ACKNOWLEDGMENTS The present work has been carried out under the project titled “Development of Ionospheric Forecasting models for Satellite based Navigation Systems over low latitude stations” sponsored by the Department of Science and Technology, New Delhi, India, vide sanction letter No: SR/FTP/ETA- 0029/2012, dated: 08.05.12. Authors are thankful to Department of Science and Technology, New Delhi, India for funding this research through SR/FST/ESI-130/2013(C) FIST program. The authors would like to thank all the reviewers for giving precise critical comments and suggestions for improving the quality of this paper.

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