Excerpt
ii
DEDICATION
I dedicate this work to my beloved wife Ms. Apio Miriam and my beloved son Oketayot
Marvin Isaac.
iii
ACKNOWLEDGEMENTS
I give all the glory and majesty to the Almighty God who made ways where there seemed
to be no way. Thank you Jesus!
With great honor, delight, pleasure and respect, I thank and appreciate my supervisors: Dr.
N. Ssebiyonga and Dr. E. Jurua for their generous time, support, patience, advice and
diligent review of my research work. In the same mood, I also thank Dr. F.M. D'ujanga
for the encouragement and advice she gave me during my research.
I appreciate the Management of Busitema University for both financial and technical
supports that made my dream a reality. I thank both the teaching and non-teaching staff of
the Department of Physics, Busitema and Makerere Universities for the maximum
cooperation accorded to me during my study.
Finally, I whole heartedly congratulate my parents: Mr. Opwa Anthony and Ms. Aciro
Sabina for their support, without which I would not have attained this academic height. I
also thank my siblings: Okello Forever (RIP), Akullu Alice, Tabo Francis, Menya Ensio,
Amwony Stella and Oyella Vicky for every word of prayers, guidance and encouragement
they spoke to me. Thank you so much and may the Almighty bless you abundantly in your
endeavors. Thank you for your love.
.
iv
TABLE OF CONTENTS
Fehler! Textmarke nicht definiert.
DEDICATION ... ii
ACKNOWLEDGEMENTS ... iii
TABLE OF CONTENTS ... iv
LIST OF TABLES ... vi
LIST OF FIGURES ... vii
ACRONYMS AND ABBREVIATIONS ... viii
ABSTRACT ... x
CHAPTER ONE: INTRODUCTION ... 1
1.1
Background of the Study ... 1
1.2
Problem Statement ... 3
1.3
Objectives of the Study ... 3
1.3.1 Main Objective ... 3
1.3.2 Specific Objectives ... 3
1.4
Significance of the Study ... 4
1.5
Scope of the Study ... 4
CHAPTER TWO: LITERATURE REVIEW ... 5
2.1
Introduction ... 5
2.2
Ionosphere ... 6
2.2.1 Ionospheric Regions ... 7
2.3
Spatial and Temporal Variations of the Ionosphere ... 9
2.3.1 Diurnal Anomaly ... 9
2.3.2 Appleton Anomaly ... 10
2.3.3 Seasonal Anomaly ... 11
2.4
Geomagnetic Regions of the Ionosphere ... 11
2.4.1 The Low-Latitude (Equatorial) Ionosphere ... 11
2.4.2 Mid-Latitude Region ... 12
2.4.3 Polar (high latitude) Region ... 13
2.5
Ionospheric Perturbations ... 13
2.5.1 Ionospheric Storms ... 13
2.5.2 Geomagnetic Storms ... 14
2.6
Solar Terrestrial Activity ... 17
2.7
The Global Positioning System ... 18
v
2.7.1 GPS Segments ... 18
2.7.2 GPS Signal Structure ... 19
2.8
Ionospheric Effects on GPS Signal Propagation ... 20
2.8.1 Refractive Index of the Ionosphere ... 21
2.8.2 Group Path Delay and Phase Advance ... 22
2.8.3 Doppler Shift ... 23
2.8.4 Ionospheric Scintillation ... 23
2.9
Total Electron Content ... 24
2.9.1 TEC Extraction from Dual Frequency GPS Signals ... 24
2.9.2 Obtaining Absolute TEC from Dual-Frequency GPS Measurement ... 25
2.9.3 Vertical Total Electron Content ... 25
CHAPTER THREE: METHODOLOGY ... 27
3.1
Introduction ... 27
3.2
Study Area ... 27
3.3
Data Used ... 28
3.4
Data Processing ... 28
3.4.1 Annual TEC Variations ... 29
3.4.2 Seasonal TEC Variability... 30
3.4.3 Diurnal TEC Variability ... 31
3.4.4 Variability of Crest-to-Trough TEC Ratio ... 31
3.4.5 Storm Time Variations in GPS-TEC ... 31
CHAPTER FOUR: RESULTS AND DISCUSSIONS ... 33
4.1
Introduction ... 33
4.2
Annual TEC Variability ... 33
4.3
Seasonal TEC Variations ... 36
4.4
Diurnal TEC Variations ... 38
4.5
Coefficient of VTEC Variability ... 41
4.6
Variability in Crest-to-Trough TEC Ratio ... 42
4.7
Effects of Geomagnetic Storms on TEC ... 48
CHAPTER FIVE: CONCLUSION & RECOMMENDATIONS ... 52
5.1
Introduction ... 52
5.2
Conclusions ... 52
5.3
Recommendations ... 53
REFERENCES ... 54
vi
LIST OF TABLES
Table 3.1: Geographic and geomagnetic coordinates of the GPS receiver stations ... 27
Table 4.1: Monthly-averaged F10.7 for each month of the year 2012 ... 35
vii
LIST OF FIGURES
Figure 2.1: Layers of the Earth's atmosphere in ascending order . ... 5
Figure 2.2: Ionization of neutral particles by solar radiation.. ... 6
Figure 2.3: Regions (D, E, F and Topside) and layers (F1 and F2) of the ionosphereller ... 7
Figure 2.4: Formation of the equatorial ionization anomaly in the ionosphere.. ... 10
Figure 2.5: The earth's geomagnetic regions ... 12
Figure 2.6: Phases of a typical geomagnetic storm ... 14
Figure 2.7: Magnetic field lines reconnection ... 17
Figure 2.8: GPS segments.. ... 19
Figure 2.9: Influence of the earth's ionosphere on ground-based radio communication ... 21
Figure 2.10: Geometry of a single-layer ionospheric shell model at altitude h
m
... 26
Figure 3.1: Map of Africa showing locations of GPS receiver stations used. ... 28
Figure 4.1: Annual ionospheric distribution of TEC during the year of 2012. ... 34
Figure 4.2: Seasonal variations in TEC over ADIS, MAL2, KAMP and ZAMB stations . 37
Figure 4.3: Diurnal variations in TEC at ADIS, MAL2, KAMP and ZAMB stations ... 39
Figure 4.4: Percentage coefficient of VTEC variability... 41
Figure 4.5: Contour plot showing variation of the crest-to-trough TEC ratios of Equatorial
Ionization Anomaly for the year 2012. ... 43
Figure 4.6: Diurnal variation of the TEC-CTR of Equatorial Ionization Anomaly for the 12
months of the year 2012 ... 44
Figure 4.7: Crest-to-Trough TEC Ratio versus F10.7 solar flux index for the 01:0004:00
UT time bin ... 46
Figure 4.8: Crest-to-Trough TEC Ratio versus F10.7 solar flux index for the 16:0020:00
UT time bin ... 46
Figure 4.9: Diurnal seasonal variation of the TEC-CTR of Equatorial Ionization Anomaly
for the year 2012. ... 47
Figure 4.10: Variations of VTEC during a geomagnetic storm ... 50
viii
ACRONYMS AND ABBREVIATIONS
A/S -
Anti-Spoofing
ASCII -
American Standard Code for Information Interchange
C/A -
Coarse Acquisition
CDMA -
Code Division Multiple Access
CI
-
Covington Index
CME -
Coronal Mass Ejection
CV
-
Coefficient of TEC Variability
DCB -
Differential Code Bias
DoD -
Department of Defense
Dst
-
Disturbance Storm Time
EIA -
Equatorial Ionization Anomaly
EPB -
Equatorial Plasma Bubble
ESF -
Equatorial Spread F
EUV -
Extreme Ultraviolet
GAGAN -
GPS Aided Geo Augmented Navigation
GLONASS - GLObal'naya NAvigatsionnaya Sputnikovaya Sistema
GNSS -
Global Navigation Satellite System
GPS -
Global Positioning System
HF
-
High Frequency
HMF -
Heliospheric Magnetic Field
HSSWS -
High Speed Solar Wind Stream
IGS
-
International GNSS Services
IMF -
Interplanetary Magnetic Field
IPP -
Ionospheric Pierce Point
Kp
-
Planetarische Kennziffer
L1 and L2 - GPS L-band Carrier Frequencies
LQ
-
Lower Quartile
LT
-
Local Time
MSAS -
Multi-functional Satellite Augmentation System
NCO -
Numerically Controlled Oscillator
P(Y)-Code - The Encrypted Precision Code (the Y-Code)
ix
P-Code -
Precision Code
PRN -
Pseudo-Random Noise
QZSS -
Quasi Zenith Satellite System
RINEX -
Receiver Independent Exchange Format
S/A
-
Selective Availability
SBAS -
Space Based Augmentation Systems
SCINDA -
Scintillation Decision Aid Network
SI
-
Sudden Impulse
SIDC -
Solar Influences Data Analysis Centre
SOPAC -
Scripps Orbit and Permanent Array Center
SSC -
Sudden Storm Commencement
TAI -
International Atomic Time
TEC -
Total Electron Content
UQ -
Upper Quartile
US
-
United States
UT
-
Universal Time
UV -
Ultra Violet
WAAS -
Wide Area Augmentation System
x
ABSTRACT
The presence of charged particles in the earth's ionosphere affect radio signals that
traverse the ionosphere, causing signal delay or loss of lock when in severe conditions,
and this hampers GPS-based communication systems. Studies have proved that the
magnitude of these ionospheric effects on GPS signals is directly proportional to the total
electron content (TEC).
In this study, TEC variations as well as variations of Crest-to-Trough TEC Ratio (TEC-
CTR), and the effects of geomagnetic storms on ionospheric TEC were investigated using
dual-frequency GPS derived TEC data obtained from four stations within the Eastern
African equatorial region for the high solar activity year 2012.
Annual variations showed that TEC had two peaks in the equinoctial months while
minima values were observed in the summer and winter solstices. The diurnal pattern
showed a pre-dawn minimum, a steady increase from about sunrise to an afternoon
maximum and then a gradual fall after sunset to attain a minimum just before sunrise.
Nighttime enhancements of TEC were observed mostly in the equinoctial months.
Analysis of the diurnal and seasonal variability of TEC showed two peaks, one peak
occurred during pre-midnight hours and the second (highest) peak occurred during the
post-midnight (early morning) hours. There was comparably higher percentage variability
during nighttime than daytime and highest during equinoxes, moderate in winter and least
during summer solstice. It was observed that generally TEC values were higher at the dip
equator than near the crest of the equatorial ionization anomaly.
TEC-CTR was seen to have two peak values, one occurred in the pre-sunrise hours around
02:00-03:00 UT and the second (highest) occurred in the post-sunset hours around 18:00-
20:00 UT. TEC exhibited good correlation with geomagnetic storm indices.
1
CHAPTER ONE:
INTRODUCTION
1.1
Background of the Study
The Earth's atmosphere contains free charged particles within an altitude range of about
60-1,000 km above the Earth's surface, and this region of partially ionized particles is
called the ionosphere (Goodman, 2005). These free charged particles are generated by the
process of photoionization, during which short wavelength solar radiations which include
X-rays and ultra-violet radiations interact with and knock-off electrons from the shells of
neutral particles in the earth's atmosphere, leaving behind a cloud of charged particles
(Memarzadeh, 2009).
The existence of these charged particles in the Earth's ionosphere affect radio signals
travelling through the medium, causing effects such as range errors, scintillations, Faraday
rotation, absorption, ionospheric Doppler shift, refraction and waveform distortion of
signals (Doherty, 2010). The magnitude of these ionospheric effects on satellite
communication, satellite tracking and navigational control application are directly
proportional to the Total Electron Content (TEC) (Bagiya et al., 2009). TEC is the most
dominant ionospheric component that affects GPS signal propagations (Seemala, 2010).
TEC is defined as a measure of the total number of electrons in a unit area along the line
of sight of GPS signal from space satellite to ground receiver (Bhuyan and Borah, 2007).
Ionospheric TEC values exhibit significant variations with solar cycle, season, local time,
altitude, latitude, longitude, geomagnetic activity, and shows significant day-to-day
variability which results from changes in the solar extreme ultraviolet (EUV) and X-ray
radiations (Sardar et al., 2012).
The Earth's ionosphere along the equatorial (low latitude) region is quite unique and
different from that at the mid and high latitudes (Chakraborty and Hajra, 2009). This is
because the low latitude ionospheric F-region is dominated by a phenomenon called
equatorial ionization anomaly (EIA), which is characterized by an electron density trough
region around the magnetic equator, and a dual band of enhanced electron density (crest
regions) at about 15
0
north and south of the trough (Schunk and Nagy, 2000). The EIA is
formed as a result of the diurnal variation of the zonal electric field, which primarily
points eastward during the day and reverses at night. In conjunction with the horizontal
2
northward geomagnetic field at equatorial latitudes, the ionospheric plasma is lifted
upward by vertical E x B drift (Stolle et al., 2008).
Once the plasma is transported to higher altitudes, it diffuses downward along the
geomagnetic field lines into both hemispheres due to gravitational and pressure gradient
forces (Goodman, 2005). This combination of electromagnetic drift and diffusion
produces a fountain like pattern of plasma motion called the equatorial fountain effect,
leaving region around the magnetic equator with little electron density concentration and
higher electron density concentrations at the crests or equatorial anomaly regions (Schunk
and Nagy, 2000). This implies that ionospheric densities are higher around the equatorial
crests than at the trough region or magnetic equator. However, the latitudes of the anomaly
crests and strength of the anomaly vary with condition of the day, season of the year and
solar activity (Chakraborty and Hajra, 2009).
Variations in TEC along magnetic equator and equatorial anomaly regions have been more
extensively studied in Asia (e.g. DasGupta et al., 2007; Liu and Chen, 2009; Walker et al.,
1994; Tsai et al., 2001; Zhang et al., 2009; and Bagiya et al., 2009 etc) and South America
(e.g. Natali and Meza, 2011; Walker et al., 1994; de Abreu et al., 2014; Sahai et al., 2007)
than in Africa. These studies indicate that equatorial anomaly regions manifest remarkable
diurnal and seasonal TEC variations, with TEC on both northern and southern equatorial
anomaly crests yielding maxima values during the equinoctial months. In Africa, limited
studies (e.g. Fayose et al., 2012; Adewale et al., 2011; Ouattara and Fleury, 2011;
Okonkwo and Ugwuanyi, 2012; Zoundi et al., 2012; D'ujanga et al., 2012; Oron et al.,
2013 etc) were carried out to understand its ionospheric phenomena and irregularities
showed a significant diurnal and seasonal TEC variations. The highest day-to-day TEC
values were observed around 18:00 UT and highest seasonal values exhibited during
equinoctial months, moderate in the summer solstice and least in the winter solstice. Much
as these studies were conducted, there is still need for further studies to investigate the
diurnal and seasonal variations of TEC as well as the effects of varying geomagnetic
activities on TEC within the region.
More so, the Crest-to-Trough TEC Ratio (TEC-CTR) along Equatorial Ionization
Anomaly (EIA) seems not to have been studied. TEC-CTR is a measure of the strength of
the fountain effect which produces equatorial ionization anomaly. The degree of
3
development of EIA is of key importance in the generation and development of the
Equatorial Spread F (ESF) irregularities that have important impacts on
telecommunication systems (Alex et al., 1989; Jayachandran et al., 1997). A well-
developed EIA is one of the conditions conducive for the generation of ESF and
scintillation that is most disruptive to the trans-ionospheric radio wave propagation and it
occurs when an Equatorial Plasma Bubble (EPB) intersects the maximum electron density
of the equatorial anomaly (Whalen, 2004).
Variations of TEC-CTR are closely related to the generation and development of the
equatorial spread F irregularities, equatorial plasma bubbles and ionospheric scintillations
(Valladares et al., 2001, 2004; Henderson et al., 2005). This suggests that TEC-CTR of
EIA is an important parameter that can be used to study the dynamics of the equatorial
ionosphere. Therefore, it is of significance to study the variability of crest-to-trough ratio
of the equatorial ionization anomaly both for scientific implication and for practical
application.
Based on the above background, this research investigated the variations of TEC, TEC-
CTR and the effects of solar and geomagnetic activities on TEC along the Eastern African
magnetic equatorial and equatorial anomaly regions using GPS data for the year 2012.
1.2
Problem Statement
The equatorial region in Africa has not been extensively studied to understand its
dynamics. Therefore, there was need to investigate TEC variations along the magnetic
equatorial and equatorial anomaly regions of the Eastern African sector.
1.3
Objectives of the Study
1.3.1
Main Objective
To investigate the variations and variability of TEC over magnetic equatorial and
equatorial ionospheric anomaly regions of the Eastern African sector
1.3.2
Specific Objectives
1.
To determine the annual, seasonal and diurnal variations of TEC over magnetic
equatorial and equatorial anomaly regions of the Eastern African sector.
2.
To determine the variability of Crest-to-Trough TEC Ratio (TEC-CTR) for the
southern crest of the Eastern African equatorial region.
4
3.
Determine the effects of a geomagnetic storm on GPS-TEC.
1.4
Significance of the Study
The results of this study will be useful for GPS users such as the Aviation Authorities,
Military, Navigation and Marines, Communication Companies, Survey and Mapping
Authorities, motorists, and farmers within the equatorial region of Eastern Africa.
1.5
Scope of the Study
The study was limited to investigating the variations of TEC as well as the effects of a
geomagnetic storm on GPS-TEC over equatorial region in the Eastern African sector using
data for the year 2012 only. TEC-CTR was also investigated for the southern crest region
only.
5
CHAPTER TWO:
LITERATURE REVIEW
2.1
Introduction
The Earth's atmosphere is divided into several concentric spherical layers based on
vertical atmospheric temperature variation as troposphere, stratosphere, mesosphere and
the thermosphere as shown in Figure 2.1. However with respect to ionization and signal
propagation, the Earth's atmosphere is divided into only two distinct layers: the
troposphere and ionosphere (Memarzadeh, 2009; Moldwin, 2008). The ionosphere was the
main interest in this study because it affects both the space-based and ground-based
communication systems due to its dispersive nature.
Figure 2.1: Layers of the Earth's atmosphere (troposphere, stratosphere, mesosphere,
thermosphere and exosphere) in ascending order with their corresponding altitudes in km,
(Dugassa, 2010).
6
2.2
Ionosphere
The ionosphere is a partially ionized region in the Earth's upper atmosphere that lies
between altitude ranges of 60 1,000 km (Goodman, 2005; Moeketsi, 2007; Kelley,
1989). The free electrons and ions in the Earth's atmosphere are produced mainly as a
result of ionization of neutral particles by solar radiation, a process called photoionization
(Moldwin, 2008). During photoionization, solar electromagnetic radiations associated with
low wavelength ultra-violet (UV), extreme ultra-violet (EUV) and X-rays collide and
interact with neutral particles in the earth's upper atmosphere, resulting into absorption of
energy by the particles (Moldwin, 2008). The absorbed energy can be large enough to
knock-off electrons from the shells of neutral particles, leaving behind a cloud of
positively charged particles as shown in Figure 2.2 (a). Photoionization therefore causes
the upper atmosphere to transform into a partially ionized region called the ionosphere
(Memarzadeh, 2009; Moeketsi, 2007).
Figure 2.2: Ionization of neutral particles by solar radiation. In (a), uncharged atom
interacts and absorbs energy from the incoming solar radiation. In (b), the charged atom
undergoes recombination process to form a neutral atom (Dugassa, 2010).
Each ion and electron produced in the ionosphere has a finite lifetime. The ions are either
absorbed by ionic chemical reactions or they recombine with the electrons to form neutral
particles (McNamara, 1991; Davies, 1990). The rate of recombination is dependent on the
background density of charged particles within a region. Variations in ionospheric
7
components and charged particle concentrations result in different regions/layers of the
ionosphere which include D, E, and F regions as discussed in the following sub-section.
2.2.1
Ionospheric Regions
Due to the altitude variations in the atmospheric neutral composition and the ions
production rate, the ionosphere has vertical layer structures which are arranged according
to plasma density variations as shown in Figure 2.3.
Figure 2.3: Regions (D, E, F and Topside) and layers (F1 and F2) of the ionosphere, their
predominant ions and corresponding altitude and electron density (Anderson and Fuller-
Rowell, 1999).
(a)
The D-Region
This is the lowest region of the earth's ionosphere which extends from approximately 50-
90 km above earth's surface (Moldwin, 2008). This region is controlled by chemical
processes and the dominant species are molecular ions and neutral particles. The D-region
is composed of both the negative and positive ions (Schunk and Nagy, 2009). The major
8
sources of ionization in this region are X-rays and UV radiations from the sun. However,
nitric oxide in the D-region can easily be ionized by a third source of ionization called the
Lyman- radiation (Olusegun, 2013; Moeketsi, 2007).
The ionization rate and therefore the electron density in this region are very low. As a
result high frequency radio waves are not reflected by this region, which is mainly
responsible for absorption of high-frequency radio waves (Olusegun, 2013). When a radio
wave enters the ionosphere, the free electrons are set into motion by the alternating electric
field on the wave. The energy that is transferred from the wave to the free electrons is lost
when the electrons collide with molecules. Due to relatively high density of neutral
particles in this region, recombination rate is very high and therefore D-region is
essentially only present during the day (Haddad, 2011; Kelley, 1989).
(b)
The E-Region
The E-region extends between heights from about 90-170 km and it is dominated by
2
O
and NO
+
ions. The
2
O
is mainly produced by photoionization of neutral diatomic oxygen
and NO
+
produced by a rapid charge exchange process between primary ions O
+
,
2
N
and
.
O
2
The electron peak density in the E-region is much greater than in the D-region
because ionization level is higher in the E-region than in the D-region, though the E-region
decays away at night when the source of ionization disappears (Memarzadeh, 2009).
(c)
The F-Region
The F-region is located from about 170 km to about 600 km. This region is formed by
solar EUV radiation ionizing atomic oxygen. The F-region is subdivided into two layers:
(i)
F1-Layer
The F1-layer occupies an altitude range from about 170 km to 200 km and is dominated
by atomic oxygen ion which disappears during night times. This layer facilitates high
radio frequency signaling to long distances, especially during the daytime.
(ii)
F2-Layer
This layer lies from about 200 km to 600 km above the Earth's surface. The F2-layer is on
top of the F1-layer, making it situated closer to the sun. As a result of being closer to the
sun, it comes into contact with more of the ultra-violet and X-ray energy, making it more
9
ionized than the F1-layer (Memarzadeh, 2009). Also, the F2-layer is the most important
region for long distance communication on the earth's surface because its high electron
density helps to reflect radio signals around the globe. However, in space-based
communications, the F2-layer is of main concern for GPS users due to the absolute
ranging errors caused by the larger electron densities in this region (Lotfy, 2003).
(d)
The Topside Region and the Protonosphere
The topside region is above the F2-region and extends from about 600 km to 1,000 km. In
this region, the density of neutral particles as well as ionization and recombination
processes decreases exponentially (Goodman, 2005). This means that electron density in
the topside region decreases exponentially and diffusive equilibrium is dominant. Above
the topside region, there is a region dominated by lighter hydrogen and helium ions called
the protonosphere. The region is fully ionized and is often considered as part of the
ionosphere for radio and navigation applications (Memarzadeh, 2009).
The peak of the electron density in the ionosphere highly depends on time of the day,
season of the year, location and year of the solar cycle. This makes the ionosphere very
dynamic and irregular in nature as discussed in the following section.
2.3
Spatial and Temporal Variations of the Ionosphere
The ionospheric F2-layer is the most significant region for many radio wave systems. But
unfortunately, this
layer exhibits the greatest degree of unpredictable variability in electron
density due to influences of ionospheric winds, diffusion and dynamical forces. The major
forms of anomalous behavior in the F2 layer include: diurnal, Appleton and winter
anomalies (Goodman, 2005). These anomalies are discussed in the following sub-sections.
2.3.1
Diurnal Anomaly
The ion production rate in the ionosphere depends on the intensity of solar radiation,
density of atmospheric gases and solar zenith angle (Goodman, 2005). Therefore
ionization is expected to reach its peak values at around noon Local Time (LT). This is
when the solar zenith angle and solar radiations are maxima. However, the actual
maximum value of ionization in the F2-layer occurs at the temporal neighbourhood of
13:00 LT to 15:00 LT, and this departure from expected behavior is termed diurnal
anomaly (Memarzadeh, 2009).
10
2.3.2
Appleton Anomaly
This is a unique symmetric feature which occurs at the equatorial ionospheric regions. It is
also called geographic anomaly, geomagnetic anomaly or equatorial ionospheric anomaly
(Goodman, 2005). This anomaly is associated with latitudinal distribution of the maximum
electron density around 15 degrees on either side of the magnetic equator as shown in
Figure 2.4.
In the early morning hours, a single ionization peak is observed over the magnetic equator.
However, after a few hours the equatorial F-region is characterized by two distinct crests
of ionization that increase in electron density as they migrate pole ward. This phenomenon
is known as an equatorial fountain and it is initiated by an
B
E
plasma drift, where E
is
the equatorial electrojet electric field and B
is the geomagnetic field vector. This drift is
upward during the day since the equatorial electric field E
is eastward at that time
(Memarzadeh, 2009). There are significant day-to-day, seasonal and solar controlled
variations in the on-set, magnitude and position of the anomaly (Chakraborty and Hajra,
2009).
Figure 2.4: Formation of the equatorial ionization anomaly within the earth's ionosphere.
The +15
0
Mag and -15
0
Mag represent the equatorial anomaly regions where most of the
electrons are deposited by the geomagnetic field lines (Doherty, 2010).
11
2.3.3
Seasonal Anomaly
This is more evident in the middle latitudes than in the low and high latitudes. In seasonal
anomaly, the summer months at the hemispheres have quite lower ionization densities than
their corresponding winter months (Goodman, 2005). This situation is a bit awkward since
it is expected that ionization be higher during summer than the winter periods. This is
because summer periods receive longer daytime solar radiation compared to their
corresponding winter periods. The main reason for seasonal anomaly is the ratio between
the atomic and molecular components at the altitudes of the F2-region. This ratio is
changed and it results in changes in the rates of ion production and electron
recombination. This mechanism leads to increased loss rate of the electrons in the summer
hemisphere (Memarzadeh, 2009).
Besides the vertical layered profiles of the Earth's ionosphere which include the D, E and
F-regions, the ionosphere is also divided into three distinct regions depending on their
geomagnetic locations as discussed in the following section.
2.4
Geomagnetic Regions of the Ionosphere
Latitudinal variations of the Earth's ionosphere show distinct behaviors due to geometry
of the Earth's magnetic field lines (Olusegun, 2013). Hence the ionosphere can be
classified by three latitudinal regions, each of which is controlled by different physical
processes. These latitudinal regions include: the low latitude (equatorial) region, middle
latitude, and high (aurora) latitude regions as shown in Figure 2.5. This study was mainly
focussed on the low latitude (equatorial) region. However, the middle and high latitude
regions were also briefly discussed. These regions are discussed below.
2.4.1
The Low-Latitude (Equatorial) Ionosphere
This region spans about 20 degrees on either side of the magnetic equator (Moeketsi,
2007). The morphology of equatorial ionosphere is quite unique and different from that of
mid and high latitudes because the magnetic field is nearly horizontal to the earth's surface
(Memarzadeh, 2009).
During the daytime, solar heating of the thermosphere drifts ionospheric plasma upward
under the influences of an eastward-directed electrojet electric field and the northward
horizontal geomagnetic field as shown in Figure 2.4. Due to gravity and pressure-gradient
forces, the uplifted plasma then moves downward along the magnetic field lines on both
12
sides of the magnetic equator (Shim, 2009). This phenomenon forms two ionization
maxima at about 15 degrees on either side of the magnetic equator. This anomaly
generates dense plasma, large enough to disturb satellite signals as they traverse this
region. During the nighttime, the equatorial electric field is westward and the plasma drifts
downward in a diurnal pattern (Li et al., 2008).
Asymmetry exists between the northern and southern anomalies as a result of inter
hemispheric wind (meridional neutral wind) blowing from the summer to the winter
hemisphere. In the summer hemisphere, plasma moves upward along the geomagnetic
field lines while in the winter hemisphere, plasma moves downward. Therefore, the
transport of the lifted plasma toward the winter hemisphere is enhanced and the plasma
transport toward the summer hemisphere is decreased. As a result, the equatorial anomaly
in the winter hemisphere is generally larger than in the summer hemisphere (Schunk and
Nagy, 2000).
Figure 2.5: The earth's geomagnetic regions with their corresponding latitudes and
longitudes. The equatorial region is in the center with mid and Polar Regions on either
side (Dugassa, 2010)
2.4.2
Mid-Latitude Region
The mid latitude region of the ionosphere includes geomagnetic latitudes from about 30
0
to about 60
0
on either sides. The mid latitude ionosphere is the best understood of all
regions and is out of the direct influence from phenomena associated with the plasma
13
fountain of the equatorial region. In the mid-latitude region, only solar photon radiation is
responsible for the ionization process and the electron density is generally not affected by
the particle radiation (Basu et al., 2005).
2.4.3
Polar (high latitude) Region
The polar region is sub divided into the auroral zone (approximately 60
0
-70
0
geomagnetic
latitudes) and the polar cap (pole ward of the auroral zone). At high latitudes the
geomagnetic field runs nearly vertical and this leads to the existence of an ionosphere that
is considerably more complex than that in the middle and low latitudes. This is because
the geomagnetic field lines connect the high latitudes to the outer part of the
magnetosphere which is driven by the solar wind (Memarzadeh, 2009).
2.5
Ionospheric Perturbations
Disturbances within the ionosphere are mainly triggered by solar flares and Coronal Mass
Ejections (CME), which impinge on the terrestrial magnetosphere-ionosphere system
(Basu et al., 2007). These events affect the outermost geomagnetic field lines and
compress the geomagnetic field causing geomagnetic disturbances. Ionospheric
perturbations can be categorized into ionospheric storms and geomagnetic storms (Otto,
2005). These perturbations are discussed in the following sub-sections.
2.5.1
Ionospheric Storms
Ionospheric storms are caused by clouds of ionized gases ejected from the Sun during
solar flares. However, electromagnetic radiation such as X-rays produced during the flare
can penetrate as far as the D-region causing a phenomenon known as short-wave fadeout.
The energetic particles also produced during the flares can hit the Earth's magnetosphere,
causing ionospheric storms. This can manifest itself as sudden, unpredictable changes in
ionospheric parameters, such as foF2, and electron concentrations. Whether these
parameters are increased or decreased will depend on the time of the day, the season, and
geographical location when the plasma cloud hit the Earth, as well as the magnitude of the
storm (Memarzadeh, 2009).
Ionospheric storms can also be caused by a High Speed Solar Wind Stream (HSSWS)
which emanates from coronal holes. The Sun's magnetic field lines stretch into the
interplanetary medium forming what is known as a Heliospheric Magnetic Field (HMF).
The HMF makes it possible for ionized materials such as solar wind particles to travel
14
along the field lines by a diffusion process and eventually reach the Earth. The effect of
HSSWS on the ionosphere is usually not as devastating as those of large solar flares. This
happens because the HSSWS does not overtake the Earth as fast as the ionized cloud from
solar flares (Shetti, 2006). Sudden disappearing filaments on the solar surface can also
cause ionospheric storms. They are a large, relatively cool structure on the solar surface
potentially blowing out magnetized plasma into interplanetary space, affecting the Earth's
geomagnetic field (McNamara, 1991).
2.5.2
Geomagnetic Storms
Geomagnetic storms result from a temporal disturbance of the Earth's magnetosphere
caused by a disturbance in the interplanetary medium (Schunk and Nagy, 2000). A
geomagnetic storm is a major component of space weather and provides the input for
many other components of space weather (Moldwin, 2008). A geomagnetic storm is
caused by a solar wind shock wave and cloud of magnetic field which interacts with the
Earth's magnetic field. An increase in the solar wind pressure initially compresses the
magnetosphere and the solar wind's magnetic field interacts with the Earth's magnetic
field and transfers an increased amount of energy into the magnetosphere. Both
interactions cause an increase in the movement of plasma through the magnetosphere
(driven by increased electric fields inside the magnetosphere) and an increase in electric
current in the magnetosphere and ionosphere (Memarzadeh, 2009).
Figure 2.6: Phases of a typical geomagnetic storm (Schunk and Nagy, 2000).
A geomagnetic storm generally has three phases: initial, main and recovery phases (see
Figure 2.6). The initial phase results from a compression of the magnetosphere due to the
arrival of a solar wind shock at the Earth (McNamara, 1991; Forster and Jakowski, 2000).
15
Frequently, storms begin abruptly and this is called a Sudden Storm Commencement
(SSC), but storms can also begin gradually without an SSC. Sometimes an impulsive
change in the magnetic field occurs but a storm does not develop, and this is called a
Sudden Impulse (SI) (D'ujanga et al., 2012).
The initial phase of a storm lasts for a few hours, during which Disturbed storm time (Dst)
index is increased, owing to the compression of the magnetosphere. During the main phase
of a geomagnetic storm, Dst is decreased. This decrease occurs because magnetic storms
are generally associated with a southward interplanetary magnetic field, which allows for
an efficient energy coupling of the solar wind and magnetosphere (Memarzadeh, 2009).
The net result is an intensification of the ring current which is the westward current that
encircles the Earth at equatorial latitudes (Schunk and Nagy, 2000). The enhanced
westward current induces a horizontal magnetic field that is southward (opposite to the
Earth's dipole field), and this accounts for the negative Dst during the main phase of a
geomagnetic storm. The recovery phase, which can last more than a day, is a time
dependent when Dst gradually increases to its pre-storm value. This occurs because the
source of the enhanced ring current subsides and the excess particles are lost via several
different mechanisms (Schunk and Nagy, 2000).
Geomagnetic storm activities are usually monitored using geomagnetic storm indices,
which include: the Dst index, Kp index and the Z-component of the Interplanetary
Magnetic Field (IMF), commonly known as IMF Bz index. These indices are usually
parameters that can be monitored continuously with ground-based equipments or derived
from continuously monitored parameters (Moeketsi, 2007). These indices are briefly
described as follows:
(a)
Disturbed Storm Time Index
Dst index is a geomagnetic index which indicates the severity of a geomagnetic storm and
the development of the ring current. It is constructed by averaging the horizontal
components of the geomagnetic field from mid-latitude and equatorial magnetograms
from the worldwide network of magnetometers (Moeketsi, 2007). Negative Dst values
indicate a magnetic storm in progress. The negative reflections in the Dst are caused by
the storm time ring current, which flows around the Earth from east to west in the
equatorial plane (Kumar and Singh, 2008).
16
The ring current results from differential gradient and curvature drift of electrons and
protons in the near Earth region, and its strength is coupled to the solar wind conditions
(Moeketsi, 2007). This happens when there is an electric field, due to magnetospheric
convections resulting from the interconnection between the southward interplanetary
magnetic field and the geomagnetic field. Through understanding the solar wind
conditions and the form of coupling functions between the solar wind and ring current, an
estimate of the Dst index can be made (Lotfy, 2003).
(b)
Kp Index
Kp index reflects the mid-latitude global magnetic activity. Kp indices are derived at a
given station by computing the maximum range between the lowest and highest observed
magnetic field values during a three hour period, with one day representing eight values of
Kp (Moeketsi, 2007). This range is then converted into an integer value ranging from 0 to
9, with 0 representing the lowest level of ionospheric activity (Lotfy, 2003). Classification
between calm days and disturbed can be determined according to the sum of these eight
values. If the daily sum of Kp exceeds the 24, the day is classified as disturbed, otherwise
the day is classified as calm.
(c)
Interplanetary Magnetic Field Bz Index
The northsouth component of the IMF Bz controls the coupling of the solar wind to the
magnetosphere. When a CME hits the Earth, the magnetosphere is compressed further and
solar particles can penetrate the Earth's atmosphere, mainly in the magnetic polar areas
(Estefania, 2007). The orientation of the Z component of the IMF has an important
influence on the magnetosphere and high-latitude ionosphere as it controls the fraction of
the energy in the solar wind flow that can penetrate in the magnetosphere (Dungey, 1961).
When Bz is strongly negative, magnetic reconnection between the IMF and the
geomagnetic field produces open field lines which allows energetic particles to be
transferred from the solar wind to the Earth's magnetosphere (see Figure 2.7). These
particles increase the density of the ring current which creates a magnetic field in the
direction opposite to that of the Earth's magnetic field and thus weakens the total magnetic
field (Prölss, 2004).
17
2.6
Solar Terrestrial Activity
The ionosphere is primarily affected due to solar radiations. The sun emits a wide
spectrum of high energy radiations and particles which interact with neutral particles in the
earth's atmosphere to cause photoionization (Memarzadeh, 2009). In general, these solar
radiations are measured in terms of three solar indices which include: Extreme Ultraviolet
(EUV) flux, 10.7 cm Solar Radio flux (F10.7) and Sunspot numbers (SSN) (Chauhan et
al., 2011).
Sunspots are temporary phenomena on the photosphere of the sun that appear visibly as
dark spots compared to surrounding regions (Prölss, 2004). They are caused by intense
magnetic activity which inhibits convection by an effect comparable to the eddy current
brake, forming areas of reduced surface temperature (Kivelson and Russel, 1995). They
usually appear as pairs, with each sunspot having the opposite magnetic pole than the
other. During a solar maximum, the number of sunspots increases (Phillips, 1992;
Moldwin, 2008). These dark temporary regions on the surface of the sun are thought to be
caused by interplay between the sun's plasma and its magnetic field. Sunspots are the
source of the solar flares and ejections that can send charge particles hurtling toward
Earth, which can damage satellites, surge power grids, cause radio blackouts and, more
benignly, produce dazzling auroras above the planet.
Figure 2.7: Magnetic field lines reconnection (Source: Estefania, 2007)
18
Apart from the sunspot numbers, solar activity can be described using the solar radiation
flux index, F10.7. The solar flux on the radio wavelength of 10.7 cm (2800 MHz) is well
correlated with X-ray, EUV, and UV fluxes (Kivelson and Russel, 1995). As a result it
gives a very good indication of conditions for long-distance communication. The 10.7 cm
radio flux is known as F10.7 index or Covington Index (CI) and varies from a minimum
near 65 (corresponding to sunspot number zero at solar minimum) to a maximum of about
200 corresponding to a sunspot number of about 150 to 160. Because of correlation with
X-ray, EUV and UV fluxes the F10.7 is one of the most commonly used indicator for solar
activity. The F10.7 index displays similar variations as the sunspot number (Leitinger et
al., 2005).
2.7
The Global Positioning System
The Global Positioning System (GPS) is a satellite-based navigation system developed by
the US Department of Defence (DoD) in the early 1970s in order to avail the US military
with Positioning Navigation and Timing (PNT) services (Morrison, 2010). However the
world-wide civil society picked interest and became attracted to the usefulness of GPS and
to date, it is widely employed in both military and civilian applications (Rabbany, 2002).
For civil use, the GPS provides Standard Positioning Service (SPS) whereas for authorized
users by the DoD, GPS provides Precise Positioning Service (PPS) (Haddad, 2011).
Besides the GPS, there are other Global Navigation Satellite Systems (GNSS) such as
Russia's GLObal'naya NAvigatsionnaya Sputnikovaya Sistema (GLONASS), Galileo
System of Europe, Quasi Zenith Satellite System (QZSS) of Japan and Compass System
of China (Memarzadeh, 2009).
The accuracy and integrity of GNSS can be greatly enhanced by the use of augmentation
information derived from various sources such as: Space Based Augmentation Systems
(SBAS) in Europe and Asia, Wide Area Augmentation System (WAAS) in USA, Multi-
functional Satellite Augmentation System (MSAS) in Japan and the GPS Aided Geo
Augmented Navigation (GAGAN) system in India.
2.7.1
GPS Segments
GPS consists of three segments: the space segment, the control segment and the user
segment as shown in Figure 2.8. The space and control segments are controlled by the US
DoD while the user segment is controlled by market forces. The space segment is the GPS
19
satellite constellation which currently consists of 32 satellites (PRN: 1-32) with usually
2428 operational satellites at any given time (Saadi and Abdullah, 2009). This guarantees
all users at any time and position to have at least 4 satellites in view. The satellites orbit
over six orbital planes with 55
0
inclinations, orbital radius of about 20,200 km and a 12
hour period (Garner et al., 2008).
Figure 2.8: GPS segments. Space segment is the satellite constellation, the control
consists of worldwide network of tracking stations and the master control center, and the
user segment includes all the military and civilian applications (Rabbany, 2002).
The control segment of the GPS system consists of a worldwide network of tracking and
monitoring stations around the globe which periodically send the corrections of ephemeris
and clock errors. The monitoring stations are equipped with communication facilities to
transmit data to the master station via terrestrial transmission (S-band) link to be accessed
by the users
(Frederic and Snider, 2012).
The user segment consists of receivers used by
both military and civilians. The receiver is made up of hardware and software for
positioning, navigation, and timing applications (Haddad, 2011). The receivers may be
fixed at one position or portable (handheld).
2.7.2
GPS Signal Structure
The GPS has undergone technological revolution right from the time it was established by
the US DoD in the early 1970s up to date. The early GPS satellites generate and transmit
20
their signals on a single frequency, L1
MHz)
1575.42
(
1
f
at the L-band but these
satellites were later outcompeted and replaced by more efficient and accurate dual-
frequency GPS satellites which generate and transmit L1 and L2 carrier frequencies.
However, currently there are GPS satellites that generate and transmit their signals on
multiple carrier frequencies as L1
MHz)
1575.42
(
1
L
f
L2
MHz)
1227.60
(
2
L
f
and
L5
MHz)
1176.45
(
5
L
f
(Haddad, 2011). In this study, the data used were obtained from a
dual-frequency GPS-receiver.
The code modulation of all dual-frequency GPS satellites is different for each satellite and
this significantly helps in minimizing the signal interference (Olusegun, 2013, Rabbany,
2002). Information generated from space-based satellites is encoded in the form of binary
bits on the carrier signals by a process known as phase modulation and each satellite is
identified with a technique called Code Division Multiple Access (CDMA) using Pseudo-
Random Noise (PRN) codes (Fayose et al., 2012). The carrier signals contain three types
of codes; the C/A code, the P-code and the Navigation Message (Olusegun, 2013).
The C/A code is a pseudo-random code that appears to be random and generated by an in-
built system algorithm. Each satellite has a different C/A code, so that they can be
uniquely identified. On the other hand, the P-code is identical on both the L1 and L2
carrier frequencies and it is better for more precise positioning. The P code repeats every
267 days. The navigation message is found on the L1 carrier frequency, being transmitted
at a very slow rate of 50 bps. It is a 1500-bit sequence, and therefore takes 30 seconds to
transmit. The Navigation Message includes information on the broadcast ephemeris
(satellite orbital parameters), satellite clock corrections, almanac data (a crude ephemeris
for all satellites), ionosphere information, and satellite health status (Olusegun, 2013).
2.8
Ionospheric Effects on GPS Signal Propagation
When a GPS signal (electromagnetic wave in nature) propagates through the ionosphere,
its propagation direction, amplitude and velocity are interrupted by the dispersive nature of
the ionospheric plasma (Shim, 2009; Lotfy, 2003). The interaction between an
electromagnetic wave and the ionosphere sets the charged particles in the ionosphere into
oscillation, with angular frequency given by;
21
2
1
2
m
ne
o
(2.1)
where, n is the charged particle density, e the charge, m the mass of the charged particle
and
o
the permittivity of free space.
When the frequency of a radio wave is less than plasma frequency, the ionosphere behaves
as a metallic mirror and reflects the wave. This is significant in aiding groundbased
communications (see Figure 2.9).
Figure 2.9: Influence of the earth's ionosphere on ground-based radio communication
1
If the frequency of radio wave is greater than the plasma frequency, the wave penetrates
the ionosphere without being reflected but it is refracted and retarded by the dispersive
nature of the ionosphere (Memarzadeh, 2009). The amount of GPS signal disturbance in
the ionosphere depends on the refractive index of the ionosphere and this fact calls for the
importance of u
nderstanding the index of refraction of the ionosphere
(Lotfy, 2003). This is
discussed in the following sub-section.
2.8.1
Refractive Index of the Ionosphere
The electron density within the ionosphere is not the same for different locations and this
makes the ionosphere an inhomogeneous medium. As a result, the ionospheric refractive
index varies significantly along the propagation path of GPS signals. This leads to bending
of the signal path, causing signal range delay (Memarzadeh, 2009). The phase index of
1
(//www.srh.noaa.gov/jetstream/atmos/ionosphere_max.htm. Date: 05/09/2013)
22
refraction at a given location in the ionosphere, n
p
can be expressed as (Lotfy, 2003; Shim,
2009; Haddad, 2011).
2
3
40
1
f
N
.
n
p
(2.2)
Therefore, the phase index of refraction mainly depends on the electron density N, and the
radio-wave frequency f. The group index of refraction can be expressed as:
2
3
.
40
1
f
N
n
g
(2.3)
It is seen that the phase refractive index is always smaller than 1, while the group
refractive index is larger than 1. This implies that in the ionosphere the phase of the wave
is advanced, while at the same time its group is delayed (Petrie et al., 2010; Memarzadeh,
2009).
The ionospheric effects on satellite communication, satellite tracking and navigational
control application are directly proportional to the TEC (Bagiya et al., 2009). These
ionospheric effects include group delay of signal modulation, carrier phase advance,
scintillation (amplitude and phase), Faraday rotation, absorption, ionospheric Doppler
shift, refraction, waveform distortion, and angular refraction (Klobuchar, 1983; Doherty,
2010). Some of these effects are briefly explained below.
2.8.2
Group Path Delay and Phase Advance
Due to inhomogeneity of the ionosphere, the ionospheric index of refraction is not a unit
value. Also, the assumption that GPS signals propagate at the speed of light as assumed in
deriving GPS pseudo-range and carrier phase observations is not correct. Using the
relation
,
c
n
k
the phase and group velocities can be expressed as (Klobuchar, 1983;
Haddad, 2011)
(m/s)
3
.
40
1
3
.
40
1
2
2
v
c
f
N
c
f
N
c
n
c
k
v
p
p
(2.4)
(m/s)
3
.
40
1
3
.
40
1
)
(
2
2
v
c
f
N
c
f
N
c
n
c
f
f
n
c
k
v
g
g
g
(2.5)
23
It can be seen from Equations (2.4) and (2.5) respectively that the apparent phase velocity
is larger than the speed of light in a vacuum, causing the phase advance. On the other
hand, group velocity is seen to be less than the speed of light, causing the group delay
(Lotfy, 2003; Shim, 2009).
Using Equations (2.4) and (2.5), the phase advance and group ionospheric range delays
produce range errors which can be expressed in units of meters as (Lotfy, 2003).
The range delay,
(metres)
3
.
40
3
.
40
2
2
TEC
f
Ndl
f
R
path
(2.6)
The magnitude of the range errors is equal for both carrier phase and pseudo-range
measurements but with opposite sign. The quantity
path
Ndl
can be evaluated by integrating
the electron density along the signal path, l. This quantity represents the total electron
content (TEC). Thus, the magnitude of the range errors is a function of the TEC along the
signal path (Lotfy, 2003).
2.8.3
Doppler Shift
The relative motion between the satellite and the GPS receiver makes the frequency of the
received signal to deviate from the original frequency (MacGougan et al., 2002). This
difference between the true and the received frequency is called geometric Doppler shift.
However, the ionosphere also induces an additional change in frequency of a GPS signal
due to varying TEC, called ionospheric Doppler shift. This additional frequency shift is
generally small compared to the normal geometric Doppler shift (Klobuchar, 1983;
Ghafoori, 2012). The Doppler shifts caused by TEC variations can be up to 1 Hz per
second which causes some narrow-band receivers to lose lock on the signals.
2.8.4
Ionospheric Scintillation
Ionospheric scintillation refers to random fluctuations in the phase and amplitude of GPS
signals caused by electron density irregularities encountered along the signal path through
the ionosphere (Li et al., 2007). The severity of scintillation effects is proportional to the
electron density and the size of patterns of irregularities in the electron density, which are
determined by the level of solar activity (Lotfy, 2003). In extreme cases, scintillation
results in loss of lock and this makes positioning to become impossible (Zernov et al.,
2009).
24
The amount of scintillation activity in the atmosphere is estimated using scintillation
indices which measure the stochastic fluctuating components of an electromagnetic
radiation. For the amplitude scintillation, S
4
index is used for estimating the standard
deviation of signal intensity normalized to the average received intensity and is given by
(De Paula et al., 2004; Forte, 2007)
2
2
2
4
I
I
I
s
(2.7)
The phase scintillation index
is usually defined as the standard deviation of the
received phase and is given by (Forte, 2007)
2
2
(2.8)
The occurrence morphology of ionospheric scintillation depends on geographic location,
local time, season, solar cycle, magnetic activity, and exhibits a high degree of night-to-
night variability (Carrano et al., 2012). Scintillation effects are strongest in the equatorial
(±20° geomagnetic latitude) than in the auroral (65-75° geomagnetic latitude) and polar
cap (> 75° geomagnetic latitude) regions (Skone et al., 2008).
2.9
Total Electron Content
Total Electron Content (TEC) is a main ionospheric parameter that describes and produces
the major impacts of ionization in the atmosphere on propagation of radio signals and
hence on precise positioning using GPS (Norsuzila et al., 2010). TEC values are measured
in TEC Units (TECU) and one TECU is equal to 10
16
electrons per square meter (Tiwari et
al., 2009; Janssen et al., 2012).
There are several methods to obtain TEC over a reference
station
(Norsuzila et al., 2010). In this work, TEC was obtained from the dual-frequency
receivers discussed below.
2.9.1
TEC Extraction from Dual Frequency GPS Signals
Each operational GPS satellites in orbit broadcast information on two frequency carrier
signals, and the ground receivers provide two distances (known as pseudo-ranges) and two
phase measurements corresponding to the two GPS satellite signals (Lotfy, 2003).
Due to dispersive nature of the earth's ionosphere, the two radio signals are delayed by
different amounts, and their phases are advanced when they propagate from satellite to a
25
receiver on the ground or on another space vehicle (Lotfy, 2003). Therefore, the electron
content along the GPS signal path between the receiver and satellite (known as slant TEC)
can be obtained from the difference between the pseudo-ranges (P
1
and P
2
), and the
difference between the phases (L
1
and L
2
) of the two signals (Haddad, 2011). The Slant
TEC is the number of electrons in a volume of one square meter cross section along the
receiver - satellite line of sight (Fayose et al., 2012).
2.9.2
Obtaining Absolute TEC from Dual-Frequency GPS Measurement
The STEC extracted from the differential pseudo-range GPS signals is strongly affected
by multipath effects, especially at low elevation angles. Multipath is one of the most
significant and difficult error sources to model. It is caused by reflection and diffraction of
the satellite signal by nearby objects. An electromagnetic signal may reach an antenna by a
single direct path or indirectly through one or more reflected paths (Abdullah et al., 2008).
The presence of additional signals arriving at the antenna due to reflected or diffracted
paths is called multipath. Because of the extra path length travelled, multipath signals
usually arrive at the antenna with a delay relative to the direct signal, introducing strong
fluctuations that may exceed the expected TEC values. Thus, the TEC estimations based
on pseudo-range difference can have large errors and so be rather uncertain (Hansen et al.,
2000).
2.9.3
Vertical Total Electron Content
All artificial satellites use radio waves to communicate with ground stations. Their radio
signals have to penetrate part of the ionosphere. As already explained, the effects of the
ionosphere are to first order approximation proportional to the slant electron content along
the line of sight ray path. By using a mapping function,
)
(
M
, the slant TEC can be
converted to vertical total electron content (VTEC) which is a more useful parameter for
describing the overall ionization of the ionosphere (Horvath and Essex, 2000).
In determining this mapping function, the ionosphere is assumed to be equivalent to a thin
shell encircling the Earth with its centre the same as that of the Earth. Thus it is assumed
that there are no horizontal gradients along the slant line of sight path from the satellite to
the ground station (Schaer et al., 1996). The geometry of the GPS satellite, receiver and
the ionosphere is shown in Figure 2.10. The intersection of the slant path from the satellite
(S) to the receiver (R) at the ionospheric median height (h
m
) is referred to as an ionospheric
26
pierce point (IPP). The IPP is commonly assumed to be 350 km above the Earth's surface
(Ma and Maruyama, 2003). Its projection vertically downwards to the surface of the Earth
(G) is known as the sub-ionospheric point, and the angle between the vertical and the slant
path at the piercing point is called the zenith angle,
(Jakowski, 1996; Jakowski et al.,
1997; Ma and Maruyama, 2003). Thus, the zenith angle
is expressed as;
,
cos
arcsin
m
E
E
h
R
R
(2.9)
Using the mapping function
sec
)
(
M
, the VTEC is then mathematically given as:
,
)
(
STEC
M
VTEC
(2.10)
Where,
)
(e
M
2
cos
1
m
E
E
h
R
R
,
2
cos
1
m
E
E
h
R
R
STEC
VTEC
(2.11)
Where
E
R
is the radius of the Earth,
the elevation angle of the satellite, and h
m
is the
median height of the ionospheric layer.
Figure 2.10: Geometry of a single-layer ionospheric shell model at altitude h
m
. R
E
is the
radius of the Earth
is the elevation angle of the satellite,
is the zenith angle between
STEC and VTEC at the ionospheric pierce point (IPP). Sub-ionospheric point (G) is a
point on the earth's surface directly below the IPP (Source: Norsuzila et al., 2008).
27
CHAPTER THREE: METHODOLOGY
3.1
Introduction
This study is aimed at investigating the variations of TEC over magnetic equatorial and
equatorial anomaly regions of the Eastern African sector. This chapter therefore describes
detailed information about the study area, types of data used, data processing techniques
and the methods used in order to achieve the study objectives. These are discussed in the
following sub-sections.
3.2
Study Area
The area of interest in this study was the equatorial region of the Eastern African sector.
Data was obtained from four stations within the region, and these stations include: Addis
Ababa (Ethiopia), Malindi (Kenya), Kampala (Uganda) and Lusaka (Zambia). The codes
ADIS, MAL2, KAMP and ZAMB have been used to respectively represent the station
names. The geographic and geomagnetic locations of the stations are shown in Table 3.1.
In order to convert the coordinate system of the stations from geographic to geomagnetic
coordinate system, the website http://www.ukssdc.ac.uk/cgi-bin/wdcc1/coordcnv.pl was
used. The geographic locations of these GPS stations have also been indicated as shown in
Figure 3.1.
Table 3.1: Geographic and geomagnetic coordinates of the GPS receiver stations
Station/ Country
Station
Code
Geographic
Geomagnetic
GNSS
receiver
used
Lat
Long
Lat
Long
Lusaka, Zambia
ZAMB
-15.4
o
S
28.3
o
E
-26.2
o
S
98.4
o
E
IGS
Malindi, Kenya
MAL2
-2.99
o
S
40.19
o
E
-12.4
o
S
111.9
o
E
IGS
Kampala, Uganda
KAMP
0.3
o
N
32.5
o
E
-9.3
o
S
104.3
o
E SCINDA
Addis Ababa, Ethiopia
ADIS
9.03
o
N
38.77
o
E
0.16
o
N
110.5
o
E
IGS
28
Figure 3.1: Map of Africa showing locations of GPS receiver stations used in the study.
3.3
Data Used
The GPS data used in this study was obtained from selected operational Scintillation
Network Decision Aid (SCINDA) and International GNSS Services (IGS) receiver
stations located within the stipulated study region. IGS data were obtained using Scripps
Orbit and Permanent Array Center (SOPAC) website (http://www.sopac.ucsd.edu) while
SCINDA data was obtained from a dual frequency NovAtel GPS receiver installed in
Kampala by the US Air Force Research Laboratory (AFRL) at the Department of Physics,
Makerere University. Solar F10.7 flux data was obtained from the Earth Orientation
Parameters and Space Weather (website: http://celestrak.com/spacedata/). While Dst and
Kp indices were obtained from the website http://swdcwww.kugi.kyoto-u.ac.jp.
3.4
Data Processing
GPS data obtained from the stations are available in a zipped
Receiver INdependent
EXchange Format (RINEX) files which are not understandable. A RINEX file consists of
the observation data file, navigation message file, meteorological file, GLONASS
29
navigation message file, GPS signal payload data files and satellite and receiver clock data
files (Hofmann-Wellenhof et al., 1997).
The RINEX observation files were processed by the Gopi GPSTEC analysis application
software, version 2.2 (Gopi, 2010). The program has the features and ability to batch
process the input files (RINEX) for all files of the month, year, all stations and all files in a
directory. It also gets ephemeris from IGS navigation files and has the ability to download
the navigation files automatically if connected to internet unless it finds the files in the
same directory as data. It calculates TEC from the observation data of GPS RINEX and
reads, calculates and removes satellite and receiver biases from Differential Code Bias
(DCB) IGS code files and calculates the inter-channel biases for different satellites in the
receiver. The software calculates vertical TEC from the observation data using a suitable
mapping function given by;
,
)
cos(
1
cos
1
)
(
5
.
0
2
s
E
E
h
R
E
R
z
E
S
(3.1)
where
)
(E
S
is the mapping function, Z is the zenith angle of the satellite as seen from the
observing station,
E
R
is the Earth's radius, E is the elevation angle in radians, and
s
h
is the
altitude of the thin layer above the surface of the Earth (taken as 350 km)
To reduce errors on TEC due to multipath effect, the Gopi GPSTEC analysis application
software eliminated data for which elevation angles of the satellite was less than 20
degrees. In this study, multipath effects were further reduced by eliminating TEC values
for which elevation angles of the satellite were less than 30
o
.
In order to achieve the objectives of this study, a number of methods were used as
discussed in the following sub-sections.
3.4.1
Annual TEC Variations
The overall day-to-day variations in TEC over the selected stations were observed by
using daily averages of vertical TEC values. These daily averages were obtained by
getting mean of the vertical TEC values at a sampling rate of 24 hours. This was done in
order to show how averaged TEC values change from one day to the other. These daily
30
values were then plotted against days of the year. This was done for all the stations
considered in the study.
3.4.2
Seasonal TEC Variability
The seasons considered in this study included: Equinoxes (March, April and September,
October), Summer Solstice (May, June, July and August) and Winter Solstice (November,
December, January and February). In order to investigate seasonal variations of TEC over
the selected stations, TEC values for 20 days of each month of available data were used.
The 20-day TEC values were considered for convenience in order to cater for days with
missing data. Seasonal values were obtained by averaging the 20-day TEC values for the
months of each season. These seasonal values were then plotted against universal time.
In order to further investigate TEC variability, scientific methods have been developed to
statistically analyze these variations. For instance, Aggarwal (2011); Somoye and Akala
(2010) reported that the use of median, Lower Quartile (LQ) and Upper Quartile (UQ)
could be a good method since it is less affected by large deviations that occur during
magnetic storms and the advantage of these parameters is that they are easily interpreted in
terms of probability. D'ujanga et al., (2012) used the monthly TEC average values and the
standard deviation deduced from the daily values and plotted on the same axes to give a
summary measure of the daily variability of TEC. However, Aravindan and Iyer (1990);
Bilitza et al., (2004); Araujo-Pradere et al., (2004); Bhuyan and Borah (2007) and
Adewale et al., (2012) reported that the use of standard deviation approach provides a
better method of describing average deviation from the mean value.
Therefore, in this study TEC variability was described by using the ratio of standard
deviation of the daily values to the mean values in percentage. This parameter was termed
as Coefficient of Variability (CV). The coefficient of variability is a statistical tool that
describes the extent of spread or deviation of each data point from the calculated mean for
the entire data set. The coefficient of VTEC variability was evaluated using the monthly
mean
)
(
of the VTEC values and their corresponding standard deviations
)
(
and it is
statistically defined as:
100
(%)
CV
(3.2)
The
(%)
CV
values for each of the selected stations were plotted against universal time.
31
3.4.3
Diurnal TEC Variability
In order to determine diurnal variability of TEC over the selected stations, TEC values
were obtained for each day of the year at 6 minutes interval. This interval was chosen
because it is small enough to observe changes in TEC values within a day. These TEC
values were averaged for all the days of available dataset for each month of the year. This
was done in order to get a single 24-hour running dataset representative of all the days of a
month, and these mean values were plotted against universal time.
3.4.4
Variability of Crest-to-Trough TEC Ratio
The vertical TEC data derived from GPS measurements obtained at two ground GPS
receiving stations around 110
o
E longitude were used to study the crest-to-trough TEC
ratios of EIA in this region. MAL2 station (located at -12.4
o
S geomagnetic latitude and
111.9
o
E geomagnetic longitude) was considered for the crest region since it is close to the
geomagnetic southern crest region, whereas ADIS station (located at 0.2
o
N geomagnetic
latitude and 110.5
o
E geomagnetic longitude) was considered for the crest region since it is
located at the magnetic equator. Unfortunately due to lack of available data sources in the
northern crest region in the year 2012, crest-to-trough ratios of TEC for the North crest
was not included in this work.
In order to compute the CTR-TEC values, vertical TEC data with half hour time resolution
for each day of available dataset at both stations were obtained. Each value of CTR-TEC
at crest station (MAL2) was then divided by its corresponding value at the trough station
(ADIS). This computation was done for all the 12 months of the year 2012 and mass plots
of monthly mean and seasonal mean CTR-TEC values against universal time obtained.
3.4.5
Storm Time Variations in GPS-TEC
The Earth's ionosphere is primarily affected by solar radiations. The sun emits a wide
spectrum of high energy radiations and particles from its upper chromospheres which
results in a CME. When the CME hits the Earth's atmosphere, it compresses the
magnetosphere, and solar particles can penetrate into the Earth's atmosphere causing
geomagnetic storms.
To investigate the effects of geomagnetic activity on GPS-TEC, Dst and Kp indices for the
year 2012 were used. Daily maximum values of vertical TEC were presented on the same
plot with Dst and Kp indices. In order to further investigate the effects of a geomagnetic
32
storm on TEC, one most intense storm observed in the year 2012, which occurred on 9
th
March was chosen. To see the short-term effects of this storm on TEC, four days were
considered (8
th
11
th
March). The Dst index, Kp index, Observed TEC and Background
TEC for these days were plotted against universal time. The Observed TEC is the TEC
recorded during each of the stormy days, whereas Background TEC is the average TEC
for 10 days before the commencement of the storm.
33
CHAPTER FOUR: RESULTS AND DISCUSSIONS
4.1
Introduction
The major aim of this study was to investigate the variations and variability of TEC over
magnetic equatorial and equatorial anomaly regions of the Eastern African sector. In
particular, we investigated the annual, diurnal and seasonal variations of TEC as well as
variations in TEC-CTR. The effects of solar and geomagnetic activities on TEC were also
investigated in this study. This chapter therefore presents the findings of this study as
disccused in the sub-sections that follow.
4.2
Annual TEC Variability
Day-to-day variations in TEC were obtained by using the mean vertical TEC values.
These values were plotted against days of the year as presented in Figure 4.1. Generally, it
can be seen from this figure that ADIS and MAL2 stations recorded the highest TEC
values. Both ADIS and MAL2 stations recorded TEC value as high as about 43 TECU in
the March equinox whereas in the September equinox, ADIS station recorded a maximum
TEC value of about 45 TECU and MAL2 station recorded the highest TEC value of about
47 TECU. The high TEC values recorded over ADIS and MAL2 stations may be
attributed to the equatorial ionization anomaly.
Figure 4.1 suggests that ZAMB station recorded the least TEC values, with a maximum of
about 37 TECU. As seen from Figure 3.1, ZAMB station (geographic latitude: -15.4
o
S
and geomagnetic latitude: -26.2
o
S) is located far from the geomagnetic equator. It is also
located far beyond the southern equatorial anomaly region (geomagnetic latitude: -15
o
S).
Therefore, the latitudinal location of ZAMB station with respect to both magnetic equator
and equatorial anomaly region may account for its low recorded TEC values. This is
because TEC is known to be higher within regions close to the equatorial anomaly regions
as a result of the fountain effect formation (Moeketsi, 2007).
KAMP station recorded a maximum TEC value of about 40 TECU in the September
equinox. This station showed only one peak because there was no data recorded for the
months of January-June. Oron et al., 2013 investigated day-to-day variability in TEC over
Kampala station using GPS data for the years 2010 and 2011. Their study revealed that the
year 2011 recorded a higher TEC value (35 TECU) than the year 2010, which recorded a
34
maximum TEC value of about 23 TECU. They attributed the difference in TEC values to
the fact that the year 2011 was in the ascending phase of solar activity (cycle 24). This
study however suggests that the year 2012 even registered much higher TEC values than
the year 2011. This may also be attributed to the fact that the year 2012 is in the ascending
phase of solar cycle 24.
0
60
120
180
240
300
360
0
10
20
30
40
50
(b) mal2
0
10
20
30
40
50
(a) ADIS
DAYS OF THE YEAR
D
A
IL
Y
A
V
E
R
A
G
E
D
V
T
E
C
(T
E
C
U
)
0
60
120
180
240
300
360
(d) ZAMB
(c) KAMP
(b) MAL2
Figure 4.1: Annual ionospheric distribution of TEC during the year of 2012. These values
are daily averages of TEC.
Generally, it can also be observed from Figure 4.1 that equinoctial months recorded higher
TEC values than the solstices. This behavior is called semi-annual anomaly. It is normally
observed in the ionospheric F-region (Torr and Torr, 1973). The low TEC values
registered during the solstice months is attributed to the fact that formation of equatorial
ionization anomaly is weaker during these months (Olusegun, 2013). Table 4.1 shows the
monthly-averaged
F10.7 for each month of the year 2012.
As seen from this table, solar F10.7
35
flux is higher at the equinoxes than at the solstices. These differences in F10.7 could have
made a contribution to the differences in the electron density at the equinoxes and
solstices. This is because during the equinoxes, the Earth's ionosphere along the equatorial
region receives a huge amount of electromagnetic radiations from the sun (Li et al., 2008).
These solar radiations (particularly the low wavelength UV and X-ray radiations) collide
and interact with neutral particles in the Earth's upper atmosphere, resulting into
photoionization (Moldwin, 2008).
Table 4.1: Monthly-averaged F10.7 for each month of the year 2012
Month
Average F10.7
January
103
February
107
March
115
April
113
May
112
June
101
July
106
August
116
September
123
October
123
November
121
December
108
It can also be seen from Figure 4.1 that September Equinox recorded higher TEC values
than March Equinox. This reveals an existence of equinoctial assymetry, where by TEC is
higher at one equinox than at the other. Previous studies (e.g Titheridge and Buonsanto,
1983; Feichter and Leitinger, 1997; Bailey et al., 2000; Zhao et al., 2009; Chkraborty and
Hajra, 2007) observed the existance of equinoctial asymmetry in ionospheric TEC values.
Feichter and Leitinger (1997) revealed that the behavior of equinoctial asymmetry depends
on location and solar activity.
Kherani et al., 2013 attributed the existence of equinoctial asymmetry between the March
and September equinoxes to neutral atmospheric temperature and composition of O/N
2
36
ratio. Their study pointed that O/N
2
ratio and neutral temperature are larger in one equinox
than the other. According to Bailey et al., (2000), equinoctial asymmetry is caused by the
south-north imbalances of the thermosphere and ionosphere at the equinoxes due to the
slow response of the thermosphere to the effects of thermospheric circulation. This may
also explain the existence of equinoctial asymmetry observed in this study.
However, the annual and day-to-day TEC variation described above does not provide
classified detailed observations of ionospheric TEC variation. Therefore, further analysis
of TEC was carried out by studying its seasonal variations as described in the section that
follows.
4.3
Seasonal TEC Variations
The seasons considered in this study included the equinoxes, summer and the winter
Solstices. In order to investigate seasonal TEC variations, mean TEC values for each
season were obtained and plotted as a function of universal time. This is presented in
Figure 4.2.
Generally, it is clearly seen from Figure 4.2 that the highest values of TEC were observed
in the equinoctial months, moderate in the summer solstice and then least in the winter
solstice, exhibiting the semiannual variation. D'ujanga et al., (2012); Oron et al., (2012)
both studied the variation of TEC using GPS-SCINDA data obtained from an equatorial
anomaly station in Uganda. They reported that equinoctial months recorded the highest
TEC values, moderate in summer and least during the winter solstices. Bhattacharya et al.,
(2009) studied the diurnal variation of the ionospheric time delay at an Indian equatorial
anomaly region and reported that the diurnal variation reached maximum during the
equinoctial months and least in winter solstices. Since ionospheric time delay is directly
proportional to TEC along the path of signal propagation, the above results agree with the
findings of this study.
High TEC values recorded in the equinoctial months can be attributed to changes in the
sun's position (Adewale et al., 2012). During equinoctial months, the sun is overhead the
equator and temperature at the equator are hotter than at the pole. This makes
thermospheric meridional wind to blow towards the poles from the equator. This
meridional wind changes the neutral composition and O/N
2
ratio
increases at equatorial
and low latitude regions (due to stronger effect of wind transport during high solar
37
activity) (Kherani et al., 2013). Increase in O/N
2
ratio results in higher electron density
and therefore during equinoxes, equatorial ionization anomaly is expected to be more
developed than during the solstices. This mechanism works perfectly for solar maximum
periods because of high wind effectiveness due to high rate of photoionization. The
semiannual variation of the EIA could also be due to the combined effect of the solar
zenith angle and geomagnetic field effects (Torr and Torr, 1973; Wu et al., 2004).
0
20
40
60
ADIS
MAL2
0
6
12
18
24
0
20
40
60
KAMP
Universal Time (Hours)
A
V
E
R
A
G
E
V
T
E
C
(
T
E
C
U
)
0
6
12
18
24
ZAMB
Equinoxes
Summer Solstice
Winter Solstice
F10.7=128.6
F10.7=121.8
F10.7=117.5
ADIS
MAL2
Figure 4.2: Seasonal variations in TEC over ADIS, MAL2, KAMP and ZAMB stations
The low values of TEC over all stations during the winter solstice is expected because in
winter solstice, the rate of photoionization at the equator decreases because the sun-
overhead moves to summer hemisphere and fountain effect is expected to be weak
(Olusegun, 2013). However, at ADIS and KAMP stations, winter anomaly was observed
especially in the post-noon hours, where TEC during winter solstices were higher than
during summer solstices. Bhuyan and Borah (2007); Balan et al., (2000) explained the
winter anomaly in terms of winter-to-summer thermospheric composition (O/N
2
ratio)
38
changes. In the winter hemisphere, thermospheric winds are downward and this results in
an increase of the O/N
2
ratio within the atmosphere. As a result, recombination is weaker
in the winter hemisphere and this leads to higher electron concentration in the winter
solstice than that in the summer solstice.
For all the seasons considered, TEC has higher values during day-time compared with
nighttime values over all the stations. Aggarwal (2011) explained this in terms of
recombination of ionized particles in the ionosphere. During daytime as the temperature
increases, loss rate of ionized particles also increases and when loss rate overcomes the
production rate, it results into gradual decrease in TEC. In the evening since the primary
source of production is no longer present, TEC values maintain the minimum values. At
ADIS station (located at magnetic equator), maximum TEC during the equinoxes, summer
and winter seasons were approximately 68 TECU, 58 TECU and 47 TECU respectively.
At MAL2, a station located close to the southern equatorial anomaly region, maximum
TEC during the equinoxes, summer and winter seasons were approximately 62 TECU, 49
TECU and 40 TECU respectively.
TEC values measured at the equatorial crest regions are usually expected to be higher than
the values measured at equatorial trough region (Bhuyan and Borah, 2007). This is
because of the existence of equatorial fountain effect which lifts and deposits plasma at F-
region altitudes around
15
o
geomagnetic latitudes. However, as can be seen from Figure
4.2, ADIS station which is located at the trough region recorded higher TEC values than
MAL2 and KAMP stations which are closer to the southern crest region. This abnormally
high TEC values observed over ADIS station could have been due to changes in the solar
activity. At KAMP, equinoctial months recorded 58 TECU, summer solstice recorded
48 TECU, and the winter solstice recorded
40 TECU. ZAMB station generally
registered the low TEC values since it is far beyond the southern equatorial anomaly crest
region. It had 47 TECU in equinoxes, 40 TECU in summer and 23 TECU during
winter solstices.
4.4
Diurnal TEC Variations
Diurnal variations of vertical TEC were studied by using TEC values obtained for each
day of the year at a 6 minute interval. These TEC values were then averaged for all the
days of available dataset for each month of the year and plotted against universal time as
39
shown in Figure 4.3. It is clearly seen from the figure that for all the months, minimum
TEC values were obtained in the post-midnight hours around 01:00-03:00 UT while
maximum TEC vales occurred in the post-sunrise hours around 10:00-14:00 UT.
0
20
40
60
80
JANUARY
FEBRUARY
MARCH
0
20
40
60
80
APRIL
MAY
JUNE
0
20
40
60
80
JULY
V
T
E
C
(
T
E
C
U
)
AUGUST
SEPTEMBER
0
8
16
24
0
20
40
60
80
OCTOBER
0
8
16
24
NOVEMBER
Universal Time (Hours)
0
8
16
24
DECEMBER
ADIS
MAL2
KAMP
ZAMB
Figure 4.3: Diurnal variations in TEC at ADIS, MAL2, KAMP and ZAMB stations
In general, the diurnal pattern of VTEC shows a pre-dawn minimum, a steady increase
from about sunrise to an afternoon maximum and then a gradual fall after sunset to attain a
minimum just before sunrise. These diurnal variations in VTEC show characteristics
typical of low latitude ionosphere. Chauhan et al., (2011) suggested that diurnal TEC
behaviors are caused by changes in the atmospheric magnetic field tube. As the total
magnetic field tube is very small at equatorial and low latitudes, the electron contents in
the field tubes collapse rapidly after sunset in response to the low temperature in the
thermosphere in the nighttime. Following the sunrise, the magnetic field tubes again get
filled up rapidly because of their low volume resulting into steep increase in ionization.
This may explain the diurnal TEC behaviors observed in this study.
40
However, diurnal TEC behaviors may also be caused by changes in the production and
loss rates of electrons in the ionosphere (Aggarwal, 2011). As the sun rises, the intensive
ionization increases the electron concentration near the F2-peak at a rate which primarily
depends upon the production rate. Since TEC is directly related to the maximum electron
density of the ionospheric plasma, it starts increasing with a maximum around 12:00 UT.
During daytime as the temperature increases, production rate also increases and
overcomes the loss rate resulting in gradual increase in TEC from a morning minimum
value to an afternoon maximum value. In late afternoon hours as temperatures decreases,
loss rate increases and overcomes the production rate leading to a gradual decrease in TEC
values. In the evening since the primary source of ionization is no longer present, TEC
values remain minimal.
Nighttime enhancements of TEC were observed over ADIS, MAL2 and KAMP stations,
with the equinoctial months showing the highest enhancements in TEC during post sunset
hours as compared to the solstice months. There was no enhancement in TEC over ZAMB
station because it is beyond the equatorial anomaly region. Nighttime enhancements in
TEC had been reported in previous studies (e.g Mukherjee et al., 2010; Adewale et al.,
2012; D'ujanga et al., 2012; Oron et al., 2012; Aggarwal, 2011; Unnikrishnan et al.,
2002). This enhancement in TEC could be due to enhancement of eastward electric field
which causes the equatorial ionization anomaly. Equatorial ionization anomaly occurs in
regions close to the equatorial anomaly (Mukherjee et al., 2010). This may therefore
explain why enhancement in TEC was higher over MAL2 and KAMP stations which are
close to the southern equatorial anomaly region than over ADIS station which is located at
the magnetic equator.
Generally, it was observed that for all the months, ADIS station recorded the highest TEC
values whereas ZAMB had the least. These low TEC values recorded over ZAMB station
could be due to the fact that the station is located far outside the equatorial anomaly region
(southward of the southern anomaly region). However, when the sun moves towards the
southern hemisphere (October, November, December and January), ZAMB is observed to
have relatively higher TEC, particularly in the post-sunset hours than even ADIS station
(Mendillo et al., 1980). Meanwhile when the sun moves towards the northern hemisphere
(February, March, April and May), there are large discrepancies between the maximum
TEC recorded at ADIS and ZAMB stations (Fayose et al., 2012). This seems to confirm
41
that electron concentrations in the ionosphere strongly depend on the changes in solar
activity which is associated with changes in the intensity of the incoming radiations, and
the zenith angle at which these radiations are incident on the earth's atmosphere (Rama
Rao et al., 2006).
4.5
Coefficient of VTEC Variability
In order to statistically investigate the diurnal and seasonal variability of TEC, percentage
coefficient of VTEC variability as evaluated from Equation (3.1) were plotted against
universal time as shown in Figures 4.4. Percentage coefficient of TEC variability is a
parameter that helps to show the changes in TEC from one value to the other.
0
2
4
6
8
10 12 14 16 18 20 22 24
0
5
10
15
20
25
30
(a) ADIS
0
2
4
6
8 10 12 14 16 18 20 22 24
0
5
10
15
20
25
30
(b) MAL2
0
2
4
6
8
10 12 14 16 18 20 22 24
0
5
10
15
20
25
30
(c) KAMP
Universal Time (Hours)
C
o
e
ffi
c
ie
n
t
o
f
V
T
E
C
V
a
ri
a
b
ili
ty
(
%
)
0
2
4
6
8 10 12 14 16 18 20 22 24
0
5
10
15
20
25
30
(d) ZAMB
Equinoxes
Summer Solstice
Winter Solstice
Figure 4.4: Percentage coefficient of VTEC variability
As seen from Figure 4.4, there are 2 peaks for ADIS station, 3 peaks for MAL2 and
KAMP stations and only 1 peak for ZAMB station. For ADIS station, one peak is noted to
occur during pre-midnight hours and the second peak (highest) during post-midnight
42
hours. For MAL2 and KAMP stations, 2 peaks were noted to occur during pre-midnight
hours and the third peak (highest) during post-midnight hours. ZAMB station recorded
only one peak; that was during the post-midnight hours.
These peaks of variability can be attributed to steep electron density gradients that are
caused by the onset and turn-off of solar ionization and superimposition of ionospheric F-
region irregularities (spread F) on the background electron density (Bilitza, 2004; Chuo
and Lee, 2008; Dabas et al., 1984; Rastogi and Alex, 1987; Sabaka et al., 2004). For
MAL2 and KAMP stations which are close to the southern equatorial anomaly region, the
additional CV peak observed between 20:00 and 23:00 UT could have been caused by
enhancements in TEC observed over these stations, mostly in the equinoctial months (see
Figure 4.3). Whereas for ZAMB station, its latitudinal location could have contributed to
the single CV peak observed over the station.
Generally, all the stations have the same diurnal features with comparatively higher
percentage variability during nighttime than during the day. CV attained lowest values that
range from values less than 5% during day time, and increased to about 1525% during
night-time. Minimum CV values were recorded during 10:0014:00 UT in all seasons and
at all stations. Maximum CV was observed to occur between 04:00 and 06:00 UT for all
the stations and seasons with an enhancement at around 16:00 UT. Similar observations
were made by Bhuyan and Borah (2007), D'ujanga et al., (2012) and Bolaji et al., (2013).
It is also observed that the distribution of CV had no seasonal biases since the
discrepancies between the seasonal CV values were not clearly defined (Adewale et al.,
2012; Soicher et al., 1982).
4.6
Variability in Crest-to-Trough TEC Ratio
In order to investigate the variations of TEC-CTR, values of TEC-CTR were obtained by
dividing daily maximum TEC at the crest station (MAL2) by their corresponding values at
the trough station (ADIS). The values obtained are then presented in Figure 4.5. This study
only focussed on the Southern crest because there was no data available from the Northern
crest during this study period. To clearly illustrate the TEC-CTR variations for a given
month, these ratios for the different months are presented in Figure 4.6.
43
Figure 4.5: Contour plot showing variation of the crest-to-trough TEC ratios of Equatorial
Ionization Anomaly for the year 2012.
To investigate TEC-CTR variations for each month, the monthly diurnal TEC-CTR values
were obtained by dividing vertical TEC data with half hour time resolution for each day of
available dataset at the crest station (MAL2) by their corresponding values at the trough
station (ADIS). The values obtained are presented in Figure 4.6.
From Figure 4.6, it can be seen that the most remarkable features for the diurnal variation
of TEC-CTR are the two peak values, one occurring in the pre-sunrise hours around
02:00-03:00 UT and the other occurring in the post sunset hours around 18:0020:00 UT.
It was observed that for all the months, post-sunset peaks had higher TEC-CTR values
than the pre-sunrise peaks. This nighttime enhancement in TEC-CTR could be due to
enhancement of eastward electric fields that causes the EIA at the crest regions
44
(Mukherjee et al., 2010). This leads to formation of huge clouds of electrons at the crest
region ionosphere.
Figure 4.6: Diurnal variation of the TEC-CTR of Equatorial Ionization Anomaly for the
12 months of the year 2012
Analysis of diurnal variations of TEC values at the equatorial crest and trough regions
(Figure 4.3) revealed that TEC at EIA's crest (MAL2 station) during the post-sunset hours
was slightly enhanced. However, TEC at EIA's trough (ADIS station) was much more
reduced during this time. Mukherjee et al., 2010 suggested that night time enhancement in
TEC could be due to enhancement of eastward electric fields that causes the EIA. They
also reported that EIA occurs in regions close to the equatorial anomaly regions. Since
45
TEC-CTR values are ratios of TEC at MAL2 station to TEC at ADIS station, the large
discrepancies seen between crest region and trough region TEC values could have led to
the large enhancement of TEC-CTR during the post-sunset hours. This seems to suggest
that the post-sunset enhancement of TEC-CTR is due to the regeneration/enhancement of
the fountain effect after sunset. Regeneration of the EIA strength or the fountain strength
after sunset is particularly strong for the equinoctial months during the high solar activity
years (Farley et al., 1986; Chkraborty and Hajra, 2007).
In order to further investigate whether the difference in TEC-CTR values between the pre-
sunrise and post-sunset peaks had any dependency on solar activity, mean TEC-CTR
values for the two time bins i.e. pre-sunrise hours (01:0004:00 UT) and post-sunset hours
(16:0020:00 UT) were used. These values were separately plotted against the mean F10.7
solar fluxes as shown in Figure 4.7 and Figure 4.8 respectively. The two time bins used
correspond to the time within which TEC-CTR values are enhanced.
It can be seen from Figure 4.7 and Figure 4.8 that the dependence of TEC-CTR values on
solar activity is different for the two time bins. For the 01:0004:00 UT time bin (Figure
4.7), TEC-CTR does not vary much with F10.7 solar flux. The correlation coefficient for
this relation is 0.35. While for the 16:0020:00 UT time bin (Figure 4.8), there seems to be
a good correlation with F10.7 solar flux, with correlation coefficient of 0.76. The good
relation seen in Figure 4.8 suggests that the evening pre-reversal which causes
enhancement of the F2 region's plasma
B
E
drift near the equatorial anomaly region is
dependent on solar activity (Zhang et al., 2009). As a result, TEC values at the crest
regions are more enhanced in the evening hours than in the early morning hours.
Since TEC-CTR is a measure of the equatorial anomaly's strength, it should be closely
related to the strength of the fountain effect that depends on the equatorial plasma's
vertical drifts induced by the electric fields. The daytime average upward equatorial F-
region vertical drift caused by electric field do not vary much with solar activity, but the
evening upward drifts increase from solar minimum to solar maximum (Fejer and
Scherliess, 2001). Fejer and Scherliess, 2001 therefore suggested that this behavior of the
dependence of the equatorial F-region vertical drifts on the solar activity causes a similar
solar activity dependency of TEC-CTR in the equatorial anomaly region.
46
Figure 4.7: Crest-to-Trough TEC Ratio versus F10.7 solar flux index for the 01:0004:00
UT time bin
Figure 4.8: Crest-to-Trough TEC Ratio versus F10.7 solar flux index for the 16:0020:00
UT time bin
47
Seasonal TEC-CTR variations were obtained by using values for the equinoxes, summer
and winter solstices. These values were then separately presented on the same graph as
shown in Figure 4.9. It can be observed from Figure 4.9 that TEC-CTR showed two peaks.
One peak occurred in the pre-sunrise hours and the second (highest) peak in the post-
sunset hours for all the seasons. This could be due to the enhancement of equatorial
fountain strength. The post-sunset peak reaches maximum value in the equinoctial months
while the pre-sunrise peak reaches maximum value during the winter solstices. TEC-CTR
had larger values in the winter solstice than in the summer solstice, a condition known as
winter anomaly effect. Winter anomaly of TEC itself is largely a neutral composition
effect resulting from the global thermospheric circulation and it confirms the existence of
hemispheric difference (Pavlov and Pavlova, 2005a; Rishbeth et al., 2000).
Figure 4.9: Diurnal seasonal variation of the TEC-CTR of Equatorial Ionization Anomaly
for the year 2012.
48
The findings of this study on TEC-CTR agree with that of Zhang et al., (2009) who
studied the variability of TEC-CTR of equatorial ionization anomaly using GPS data
obtained from Chinese network stations, South-East Asian stations and Australian stations
for the years 1998-2004. Their study was conducted for both the southern and northern
equatorial anomaly crest regions. They observed that TEC-CTR is a measure of the
equatorial anomaly strength, which is more closely related to the strength of the fountain
effect. They also reported that on average, the post-sunset equatorial upward drift induced
by electric field is higher in northern winter than in northern summer. This shows that
winter anomaly effect in TEC-CTR exists simultaneously in both hemispheres as a result
of the common driver electric fields.
4.7
Effects of Geomagnetic Storms on TEC
A geomagnetic storm is a temporary disturbance of the Earth's magnetosphere caused by a
solar wind shock wave and/or cloud of magnetic field which interacts with the
magnetosphere through the southern component of the interplanetary magnetic field
(IMF). This compresses the magnetosphere, with transfer of energy and energetic charged
particles (predominantly electrons and protons) into the magnetosphere (Gonzalez et al.,
1999; Basu et al., 2007). The energetic particles of solar wind can go into the
magnetosphere along magnetic field lines, yielding an injection of plasma in the night-side
of the magnetosphere, or they become trapped on closed geomagnetic field lines, forming
regions called radiation belts within the terrestrial environment (Rama Rao et al., 2009;
Bartels et al., 1939).
The trapped particles show drifts due to magnetic field gradient and curvature as well as to
gyration orbit effects. As drifts depend on the sign of charge, ions travel to west and
electrons to east, giving rise to a ring current (Tsurutani et al., 2003). The ring current
induces a surface magnetic field which is opposite to the Earth's magnetic, and whose
strength is inversely proportional to the energy content of the ring current, which increases
during geomagnetic storms (Bartels et al., 1939). When the electric field is intense enough
as to enhance the ring current above a value, a geomagnetic storm is produced. The Dst
index is considered to be an indicator of the ring current. Dst index of -50 nT is considered
as a geomagnetic storm and if it passes -100 nT the storm is considered as intense. Major
geomagnetic storms can reach more than -300 nT. The negative Dst values mean that
49
Earth's magnetic field is weakened by the shock wave, and this is particularly the case
during solar storms (Gonzalez et al., 1999).
In order to investigate the effects of geomagnetic storm on TEC, ionospheric TEC data
obtained from ADIS station was used in this study. One most intense storm observed in
the year 2012, which occurred on 9th March was chosen. To see the short-term effects of
this storm on TEC, four days were considered, including the storm-intense day (i.e. 8
th
11
th
March). The Dst (disturbance storm time) index, Kp index, Observed TEC and
Background TEC for these days were plotted against universal time as shown in Figure
4.10. Observed TEC is the TEC recorded during each of the stormy days, whereas
Background TEC is the average TEC for 10 days before the commencement of the storm.
Figure 4.10 shows that the initial commencement started at around 11:00 UT on 8
th
March
2012. This was followed by a slight decrease in the geomagnetic Dst index and an increase
in the geomagnetic Kp index. The sudden sharp jump in the Earth's field at the onset of
the initial phase is caused by the abrupt increase in the solar wind pressure at
interplanetary shock (Araki and Nagano, 1988; Araki, 1994). However, the Background
TEC remained relatively higher than the Observed TEC during the initial phase of the
storm. This could be because not all initial phases of geomagnetic storms can cause
significant effects on the magnetosphere since the magnitudes of the effects caused depend
on the intensity of the shock waves (Araki and Nagano, 1988; Araki, 1994; Forster and
Jakowski, 2000). When the shock wave hits the magnetosphere, a compressional wave
travels at the magnetosonic wave speed from multiple points of the outer magnetosphere.
Thus, if the intensity of the shock wave is not strong enough, it causes no influence on the
ionospheric parameters (Araki et al., 1985).
The main phase of the storm started at about 02:00 UT on 9
th
March 2012, when Dst
dropped from about -10 to about -131 nT at around 09:00 UT, and the geomagnetic Kp
index increased to 8 as shown in Figure 4.10. A Dst value of -131 nT indicates an intense
storm. In this phase, the interplanetary electric field penetrates to the low-latitude
ionosphere for many hours without decay and energy is transferred from solar wind to the
magnetosphere. This produces loading of the interplanetary particles into the
magnetosphere-ionosphere region, and enhances the ring current within the terrestrial
environment (Kumar and Singh, 2008). This produces a strong decrease of Dst index
50
during the storm's main phase, followed by enhancements in ionospheric TEC values as
observed in Figure 4.10.
Figure 4.10; Variations of VTEC, Dst-index and Kp-index with Universal Time during
Storm of March 8-11, 2012
The deposition of solar wind energy in the magnetospheric polar cap region causes a
disturbance in geomagnetic field. As a result of this disturbance, the energy inputs from
the magnetosphere to the upper atmosphere can cause a dramatic change in electron
density of the F-region of the ionosphere. Geomagnetic storms produce large and rapid
changes in magnetospheric convection currents (Gonzalez et al., 1999). As a result, direct
prompt penetration of dawn-dusk electric field to the equatorial and low-latitude
ionosphere modulates the currents and fields of that region. The perturbation in field
affects the distribution of ionospheric plasma. During day time, prompt penetration
51
electric field is eastward and enhances the dynamo electric field. This dynamo electric
field enhances vertical E x B plasma drift with lifting the plasma to higher altitudes
(Rastogi and Alex, 1987). At these altitudes, the production to loss ratio is greater which
results into enhanced electron density in the dayside sector. Thus prompt penetration
electric field is associated with huge enhancement in total electron content (TEC) in the
dayside sector and depletion in TEC in night side sector as seen in Figure 4.10. The
observed increases and decreases in the ionospheric F-region electron densities and TEC
are respectively referred as positive and negative storm effects (Abdu et al., 2007).
The recovery phase of the storm started on 9
th
March 2012 at about 16:00 and continued
up to 11
th
March 2012 at about 12:00 UT (Dst ~ -15 nT). This phase is associated with the
loss of ring-current particles from the magnetosphere. During this phase, the magnetic
field on the Earth's surface goes back to the value of quiet time because of a decay of the
ring current. This decay is due basically to loss processes such as; exchange of charge,
Coulomb interaction, and particle wave interaction (Tsurutani et al., 2008).
52
CHAPTER FIVE: CONCLUSION & RECOMMENDATIONS
5.1
Introduction
In this study, GPS-TEC data obtained from ADIS, KAMP, MAL2 and ZAMB stations
were analyzed for annual, diurnal, and seasonal variations. Crest-to-trough TEC ratio was
investigated for the southern equatorial anomaly region by considering the ratio of TEC
data for the crest and the trough regions. The effects of geomagnetic storms on TEC were
also investigated in this study. The following section summarizes the results obtained from
this study.
5.2
Conclusions
It was observed that TEC showed two maxima peaks in the equinoctial months and two
minima peaks in the solstices. ADIS and MAL2 stations recorded the highest TEC values
during the year 2012, followed by KAMP and ZAMB. For all the stations, equinoctial
asymmetry was observed with higher TEC values recorded in the September equinox than
the March equinox. Diurnal variations in TEC revealed that generally TEC attained
maximum values around 10:0014:00 UT and minimum values at around 02:0004:00
UT. The diurnal pattern showed a pre-dawn minimum, a steady increase from about
sunrise to an afternoon maximum and then a gradual fall after sunset to attain a minimum
just before sunrise.
Nighttime enhancements of TEC were observed mostly in the equinoctial months at
MAL2, ADIS and KAMP stations. Seasonal variations in TEC showed that highest values
of TEC were observed in the equinoctial months, moderate in summer and least in the
winter solstice. The percentage coefficient of VTEC variability showed two peaks. One
peak occurred during pre-midnight hours and the second (highest) peak occurred during
the post-midnight (early morning) hours. There was comparably higher percentage
variability during nighttime than daytime. The coefficient of VTEC variability recorded
minimum values at around 10:0014:00 UT in all seasons and at all stations, while
maximum percentage variability was registered at around 03:0006:00 UT. During
equinoctial months, percentage variability was highest, moderate in winter and least in
summer solstice. TEC exhibited good correlation with geomagnetic storm indices.
53
The diurnal variation pattern of TEC-CTR is characterized by two remarkable peak values,
one occurring in the post-midnight hours around 02: 00-03: 00 UT (05: 00-06: 00 LT) and
the second (highest) peak occurred in the post-sunset hours around 18: 00-20: 00 UT (21:
00-23: 00 LT). This means that EIA is regenerated (enhanced) to reach its largest strength
in the post-sunset hours before midnight. Seasonal TEC-CTR variations showed a semi-
annual variation pattern, with maximum peak values occurring in the equinoctial months.
TEC-CTR also revealed an existence of winter anomaly in this region, with higher values
of TEC-CTR in the winter solstice than summer solstice. TEC-CTR in the daytime post-
noon hours; between 01: 00-04: 00 UT (04: 00-07: 00 LT) does not vary much with the
solar activity; however, TEC-CTR in the post-sunset hours; between 16: 00-20: 00 UT
(19: 00-23: 00 LT) shows a clear dependence on the solar activity, with its values
increasing with solar activity. This is due to the similar dependence of the equatorial F-
region vertical drifts on the solar activity.
5.3
Recommendations
This study investigated the annual, diurnal, seasonal variations of the ionospheric TEC
over four selected ground-based receiver stations in Eastern Africa during the high solar
activity year 2012. Variations TEC-CTR as well as the effects of geomagnetic storms on
TEC was also investigated in this study. However, further studies to investigate the
annual, diurnal, seasonal and latitudinal variations of TEC over these four stations during a
low solar activity period could still be done in the future. It is further recommended that
TEC-CTR could also be investigated by using data obtained at both the southern and
northern equatorial anomaly crest regions. Lastly, in order to use the outcome of this kind
of study for predicting future ionospheric phenomena, a study can be carried using data for
more than five years, preferably 10 years.
54
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