MODELING THE F REGION IONOSPHERIC PEAK HEIGHT …umpir.ump.edu.my/13178/1/FKEE - ZETI AKMA RHAZALI - CD 9649.pdf · MODELING THE F REGION IONOSPHERIC PEAK HEIGHT VARIATIONS OVER MALAYSIA

MODELING THE F REGION IONOSPHERIC PEAK HEIGHT VARIATIONS OVER

MALAYSIA BY ANTENNA PATTERN SYNTHESIS TECHNIQUE

ZETI AKMA BINTI RHAZALI

Thesis submitted in fulfilment of the requirements

for the award of the degree of

Doctor of Philosophy in Electrical Engineering

Faculty of Electrical and Electronic Engineering

UNIVERSITI MALAYSIA PAHANG

SEPTEMBER 2014

vi

ABSTRACT

The ionospheric F region over Malaysia is still an issue to many radio communication

enthusiasts. The actual height of this layer is not well defined. Models available are

mostly reliable for temperate zones. This thesis describes the determination of the actual

F layer height and proposed a unique model to represent the height variations. The

ionospheric F region is observed via ionograms, produced by the ionosonde operated at

Parit Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. The ionogram gives the

virtual height representation of the ionosphere. POLAN ionogram inversion program is

used to determine the real height of the ionospheric layer. The observations are held

during period of moderate to low solar activity of solar cycle 23 (2005 to 2010).

However, in this work, only hourly data of March, June, September, and December,

2006 and 2007, are examined. The data are statistically analysed to summarize their

main characteristics. The actual height of the F layer is determined from the median

values and the coefficient of variability quantifies the height deviations. To derive the

mathematical representation of the variations, the least-squares regression technique is

used to fit functions to the median data. The best fit function is the descriptive model

that describes the variations. A new model of ionospheric height variations is also

proposed on the same basis. The ionospheric height time variation which is a cyclic

event is re-represented in polar coordinate form. The cyclic representation which

approximates an antenna radiation pattern allows the development of antenna equivalent

model of peak height variations. The association of ionospheric height variations to the

radiation pattern of antenna array is the novelty idea of this study. The observation

results indicate that the median height of peak electron density, hmax, varies from 420

km in June to 550 km in other months during noon time. The night-time average heights

rest around 300 km for all months. The daytime peak is found highest in December

solstice season and lowest in June season while post sunset peaks are not seen during

this period. The descriptive mathematical model of diurnal variations shows that the

variations fit well into a four-term Fourier series model. The two-element arrays with

array spacing in the x-direction of /8, and phase of /3, and with element spacing in

the y-direction of /4, and phase of zero, is the optimal array configuration which

signifies the variations. The results show that an array of two-element arrays antenna is

suitable to represent the ionosphere peak height variations over Malaysia during

moderate to low solar activity period.

vii

ABSTRAK

Rantau F ionosfera merentasi Malaysia masih menjadi isu kepada kebanyakan

pengguna komunikasi radio. Ketinggian sebenar lapisan ini belum dapat dipastikan.

Model-model yang ada pula cenderung untuk kegunaan di zon bersuhu. Tesis in

menjelaskan penentuan ketinggian sebenar lapisan F dan mensyorkan sebuah model

unik sebagai paparan kepelbagaian ketinggian. Rantau F ionosfera diperhatikan melalui

ionogram, hasil cerapan yang diperolehi daripada ‘ionosonde’ yang beroperasi di Parit

Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. Ionogram mempaparkan

ketinggian maya lapisan ionosfera. Perisian POLAN digunakan untuk menukar kepada

ketinggian sebenar lapisan ini. Pencerapan telah dilakukan dalam tempoh aktiviti solar

sederhana hingga rendah, pada kitaran solar 23 (2005-2010). Bagaimanapun, untuk

kajian ini, hanya ionogram dalam sela masa jam bagi bulan Mac, Jun, September, dan

Disember, 2006 dan 2007, diteliti. Analisa statistik digunakan untuk menentukan ciri

penting data tersebut. Ketinggian lapisan ionosfera diperolehi daripada nilai median

manakala pekali variasi menentukan corak kepelbagaian. Pembangunan model

matematik menggunakan teknik ‘least-squares regression’. Sesuatu fungsi matematik

akan disesuaikan kepada nilai median tersebut. Model matematik diperolehi apabila

fungsi matematik tersebut memberikan penghampiran terbaik. Atas dasar yang sama,

pembangunan model bagi menggambarkan kepelbagaian ketinggian ionosfera juga

dilaksanakan. Kepelbagaian ketinggian lapisan ionosfera terhadap masa adalah suatu

keadaan yang silih berulang. Ia boleh dipaparkan dalam koordinat polar. Paparan

sebegini menghampiri paparan corak radiasi antenna tatasusun justeru pembangunan

model kepelbagaian ketinggian lapisan ionosfera adalah perlu. Kesinambungan di antara

kepelbagaian ketinggian lapisan ionosfera dan corak radiasi antena tatasusun merupakan

idea terbaru yang terhasil dari kajian ini. Keputusan pemerhatian menunjukkan

ketinggian ionosfera, hmax berubah dari 420 km pada bulan Jun kepada 550 km pada

bulan-bulan yang lain semasa waktu tengahari. Purata ketinggian pada waktu malam

pula berada pada paras 300 km. Puncak tertinggi dicapai pada bulan Disember dan

terendah dalam bulan Jun. Model matematik untuk kepelbagaian harian menunjukkan

bahawa model jujukan Fourier 4-terma sangat bersesuaian dengan kepelbagaian ini.

Antena tatasusun dua-elemen dengan jarak susunan /8 dalam arah-x dan fasa /3, dan

jarak elemen /4 dalam arah-y dengan fasa sifar, adalah konfigurasi tatasusun yang

paling optimum untuk menggambarkan kepelbagaian ketinggian ionosfera. Keputusan

kajian menyatakan tatasusun dua-elemen tatasusun adalah paparan yang paling sesuai

untuk kepelbagaian ketinggian ionosfera untuk tempoh aktiviti solar sederhana hingga

rendah.

viii

TABLE OF CONTENTS

Page

SUPERVISOR’S DECLARATION ii

STUDENT’S DECLARATION iii

DEDICATION iv

ACKNOWLEDGEMENTS v

ABSTRACT vi

ABSTRAK vii

TABLE OF CONTENTS viii

LIST OF TABLES xii

LIST OF FIGURES xiii

LIST OF SYMBOLS xvii

LIST OF ABBREVIATIONS xix

CHAPTER 1 INTRODUCTION

1.1 Background 1

1.2 Problem Statement 3

1.3 Objectives 5

1.4 Scope of Work 7

1.4.1 Ionospheric Observation

1.4.2 Data Analysis and Trending

1.4.3 Modeling

7

8

8

1.5 Thesis Outline 8

1.6 Summary 10

CHAPTER 2 LITERATURE REVIEW

2.1 Early Discovery 11

2.2 Ionospheric Research 12

2.2.1 Research in Equatorial Region

2.2.2 Research in Malaysia

16

21

ix

2.3 Ionospheric Electron-Density Profile 22

2.3.1 Peak Electron Density, Nmax

2.3.2 Height of Peak Electron Density, hmax

23

28

2.4 Associating Ionospheric Height Variation to Antenna 30

2.4.1 Array Pattern Synthesis Techniques

2.4.2 Parameterising Ionospheric Height Variations by Array

Design Techniques

32

33

2.5 Summary 34

CHAPTER 3 CHARACTERISING THE IONOSPHERIC F REGION

3.1 Introduction 36

3.2 From Observation to Modeling 37

3.3 Data Collection 38

3.3.1 Radio Sounding Technique

3.3.2 Experimental Setup

3.3.3 The Ionogram

38

40

41

3.4 Data Management and Pre-processing 43

3.4.2 Ionogram Inversion using POLAN Program

3.4.2 Technique used to Manage Empty Data Bins

3.4.3 Data Assimilation

3.4.4 Data Mining

43

49

52

55

3.5 Exploratory Analysis of Data 57

3.6 Modeling the Ionospheric Peak Height Variations 59

3.6.1 The Descriptive Model

3.6.2 Ionospheric Peak Height Variations Model

59

60

3.7 Summary 61

CHAPTER 4 OBSERVATIONAL RESULTS OF THE IONOSPHERE

OVER MALAYSIA

4.1 Introduction 64

4.2 Ionospheric Electron Density Studies 64

4.2.1 Electron-Density Profile

4.2.2 Peak Electron Density, Nmax

4.2.3 Height of Peak Electron Density, hmax 4.2.4 Temporal Variations of Nmax

and hmax

64

68

71

76

x

4.3 Ionospheric Features and Characteristics over Parit Raja 78

4.3.1 F3 layer Features of the Noon time Ionosphere

4.3.2 Spread F and Sporadic E Events

78

83

4.4 Influence of Solar Activity 85

4.4.1 Midday vs. Midnight Profiles 86

4.5 Influence of Geomagnetic Activity 88

4.5.1 Geomagnetic Storms Impact on Plasma Distribution 89

4.6 Ionospheric Variability 92

4.7 International Reference Ionosphere (IRI) Model Verification 94

4.8 Summary 97

CHAPTER 5 ANTENNA PATTERN EQUIVALENCE OF PEAK

HEIGHT VARIATIONS

5.1 Introduction 104

5.2 Characterisation of the Height of Peak Electron Density Variations 105

5.2.1 Introduction

5.2.2 Fourier Components as Approximation to Median Height of

Peak Electron Density Variations

5.2.3 Mathematical Representation

5.2.4 Cyclic Diagram

105

105

112

114

5.3 Antenna Pattern Equivalence of Peak Height Variations 115

5.3.1 Development of the Model

5.3.2 Array of an Array

5.3.3 Closeness of Fit

115

126

133

5.4 Summary 139

CHAPTER 6 CONCLUSIONS

6.1 Introduction 143

6.1.1 Ionospheric Height Variations

6.1.2 Cyclic Diagram

6.1.3 Parameterisation of Ionospheric Height Variations

143

144

144

6.2 Summary 145

6.3 Future Work 147

xi

REFERENCES 149

APPENDICES

A Solar Cycle 23/24 158

B Sample Ionograms 159

C Curve Fitting using Fourier Series Approximation 164

D Catalogue of Array Patterns 188

E List of Publications 193

xii

LIST OF TABLES

Table No. Title Page

2.1 Ionosonde stations in equatorial region 17

3.1 Standard modes of analysis incorporated in POLAN 45

3.2 Solar activity indicator 53

3.3 Geomagnetic activity condition 55

4.1 The daytime and night-time Nmax and hmax values for five

consecutive days of January 2005

88

4.2 Optimal value of median Nmax, and hmax and their corresponding

standard deviations

97

5.1 RMSE values for all representative months 108

5.2 Performance comparison for the four representative months

under different geometrical configuration

125

5.3 Performance comparison for the four representative months

under different geometrical configuration

134

5.4 Standard deviations 135

5.5 Numerical results of the antenna equivalence of hmax variations

(2006) giving the magnitude, G dB, and difference, dB

141

5.6 Numerical results of the antenna equivalence of hmax variations

(2007) giving the magnitude, G dB, and difference, dB

142

5.7 Results showing the coefficients of Fourier series

approximation to March median hmax variations

164


approximation to June median hmax variations

170


approximation to September median hmax variations

176


approximation to December median hmax variations

182

5.11 Array factor of N = 2, 3, and 4 for different element spacing, d 188

5.12 Array factor of N = 2 for different element spacing, d, and

progressive phase shift,

190

xiii

LIST OF FIGURES

Figure No. Title Page

2.1 (a) An illustration of the equatorial plasma fountain effect

(Bilitza, undated) (b) Latitudinal variation of electron density at

fixed height

19

2.2 Equatorial atmosphere ionosphere coupling processes 20

2.3 Sample electron-density profile 23

2.4 (a) The buildup of the ITS-78 model (b) The Bradley and

Dudeney (1973) model

25

2.5 The normalized electron density N(h)/No according to Chapman’s

theory

26

2.6 The buildup of the IRI model 28

3.1 Sequence of procedures to final model development 37

3.2 Radio sounding principle 38

3.3 Experimental setup 40

3.4 Sample (a) daytime and (b) night-time ionograms of Parit Raja

(THO)

42

3.5 POLAN Output 46

3.6 Sample scaled ionogram and real-height profile of Parit Raja

obtained using POLAN with (a) START = -1 (b) START = 0 (c)

START = 3 d) START = 90

48

3.7 Real-height profiles of Parit Raja using different AMODE values 49

3.8 Linear fit overestimates the missing data of Parit Raja 50

3.9 Interpolation shows better approximation in substituting missing

data of Parit Raja

51

3.10 Comparison of pre-processing techniques to data of Parit Raja 52

3.11 Geomagnetic activity conditions 56

3.12 Solar activity conditions 57

3.13 The parameterisation process 61

4.1 Electron density profiles showing progressive development of F

layers

66

xiv

4.2 The peak electron density, Nmax, diurnal variations of (a) March

Equinox (b) June Solstice (c) September Equinox and (d)

December Solstice during moderate solar activity (2006).

Discontinuities in June plots are due to null data resulting from

high irregularities that blankets any ground observation

69

4.3 Seasonal patterns of median Nmax during moderate solar activity 70

4.4 The height of maximum electron density, hmax diurnal variations

of (a) March Equinox (b) June Solstice (c) September Equinox

and (d) December Solstice during moderate solar activity (2006).

Discontinuities in June plots are due to null data resulting from

high irregularities that blankets any ground observation

72

4.5 Seasonal patterns of median hmax during moderate solar activity 73

4.6 Median hmax for four different seasons in (a) 2006 and (b) 2007

during moderate solar activity period

74

4.7 Variability of hmax for four different seasons during low solar

activity period (a) 2006 (b) 2007. The solid line show the median

valued for the year

75

4.8 Temporal variations of Nmax and hmax 77

4.9 The monthly occurrence rate of ionospheric F3 layer over Parit

Raja

79

4.10 The onset and peak occurrences of F3 layer over Parit Raja for

2006-2007

79

4.11 Seasonal variations of ionospheric F3 layer occurrences 80

4.12 Median hmax for four different seasons in (a) 2006 and (b) 2007

during moderate solar activity period

82

4.13 Spread F and sporadic E occurrences 84

4.14 Seasonal patterns of median hmax during moderate solar activity 85

4.15 Sample (a) midday (1200 LT) and (b) midnight (0000 LT)

electron density profiles of five consecutive days of January 2005

87

4.16 Respective maxN and maxh day-to-day variations for December

2006. The dotted lines are the respective monthly medians

90

4.17 Median values of (a) Nmax and (b) hmax under different

ionospheric conditions

91

4.18 Variability of hmax for four different seasons during low solar

activity period (a) 2006 (b) 2007. The solid line show the median

valued for the year

93

xv

4.19 IRI comparison (a) peak electron density (b) height of peak

electron density

95

4.20 Ion composition of the neutral atmosphere 101

4.21 Equatorial Ionosphere Thermosphere System 102

4.22 Sample vertical ion drift pattern for December 2006 103

4.23 Ionograms of 14 January 2005 159





5.1 Sample of numerical fit for March 06 106

5.2 Samples showing the confidence bounds for the fitted coefficients 109

5.3 Curve fitting using Fourier Series approximation and the

residuals

111

5.4 hmax variations (a) 2006 (b) 2007 113

5.5 (a) Polar representation of hmax variations (b) Antenna

equivalence hmax variations radiation pattern

114

5.6 Far-field geometry of N-element array of isotropic sources

positioned along the z-axis

116

5.7 Array patterns for array antenna with N = 2, 3, and 4 elements

separated by d = /8, /4, /3, /2, and

122

5.8 Two-element array pattern with element separation, d = /8, /4,

and d = /3 for = 0, /6, /3, and = /2

123

5.9 Array factor of two-element array with d = /8 and = /3

(solid line)

126

5.10 The planar array geometry 128

5.11 Pattern multiplication of two identical arrays (a) linear

configuration (b) multidimensional configuration. Both arrays

have uniform element spacing, d = /8, and progressive phase

shifts, = /3. The total pattern is compared to June 2006

antenna equivalence of peak height variations radiation pattern

130

xvi

5.12 Pattern multiplication of two different arrays (a) linear

configuration (b) multidimensional configuration. Array 1 is a

two-element array with d = /8 and = /3 while Array 2 is

another two-element array with d = /4 and 0 . The total

pattern is compared to June 2006 antenna equivalence of peak

height variations radiation pattern

132

5.13 Antenna equivalence of peak height variations radiation patterns

(solid line). The dotted line shows respective months variations

136

5.14 Difference from the fits for (a) 2006 and (b) 2007 138

5.15 Geometrical configuration of planar array 140

5.16 Samples showing the confidence bounds for the fitted coefficients

(March 2006)

166

5.17 Data fits and residuals (March 2006) 167


(March 2007)

168

5.19 Data fits and residuals (March 2007) 169


(June 2006)

172

5.21 Data fits and residuals (June 2006) 173


(June 2007)

174

5.23 Data fits and residuals (June 2007) 175


(September 2006)

178

5.25 Data fits and residuals (September 2006) 179


(September 2007)

180

5.27 Data fits and residuals (September 2007) 181


(December 2006)

184

5.29 Data fits and residuals (December 2006) 185


(December 2007)

186

5.31 Data fits and residuals (December 2007) 187

xvii

LIST OF SYMBOLS

foE Critical frequency of the E layer

foF1 Critical frequency of the F1 layer

foF2 Critical frequency of the F2 layer / Ordinary wave

fxF2 Extraordinary wave

fN Plasma frequency

fc Critical frequency

fo Critical frequency of ordinary wave

fx Critical frequency of extraordinary wave

f Frequency

h Real height

h’ Virtual height

ho Base of the ionosphere

hr Reflection height

maxh Height of peak electron density

hmF2 F2 layer height of peak electron density

H Scale height

N, Ne Number of electron (per meter3)

maxN Peak electron density

NmF2 F2 peak electron density

B0 Thickness of the F2 region

B1 Shape of the F2 region

2)3000( FM Propagation factor

Rz12 12 month running-mean sunspot number

IG12 ionosphere-effective solar index

Ap Daily magnetic index

Kp 3-hour Planetary

c Speed of light

t Time

T Time of flight

Solar zenith angle

xviii

Refractive index

' Group refractive index

a0, an, bn Fourier coefficients

n Number of term (harmonics)

E Electric field

N Number of element

d Element spacing

dx Array spacing

dy Element spacing

Progressive phase shift

Elevation angle

k wave number

r Far field distance

Array phase

Wavelength

O Oxygen

N2 Nitrogen

NO Nitrogen Oxide

xix

LIST OF ABBREVIATIONS

ACE Advanced Composition Explorer

ARTIST Automatic Real Time Ionogram Scaler with True Height

CADI Canadian Advanced Digital Ionosonde

CCIR International Radio Consultative Committee

COSPAR Committee on Space Research

CTIP Coupled Thermosphere-Ionosphere-Plasmasphere

EEJ Equatorial Electrojet

EIA Equatorial Ionization Anomaly

EITS Equatorial Ionosphere-Thermosphere System

ESF Equatorial Spread F

EUV Extreme Ultra-violet

FAIM Fully Analytical Ionospheric Model

GIRO Global Ionospheric Radio Observatory

GPS Global Positioning System

HF High Frequency

HWM Horizontal Wind Model

ICED Ionospheric Conductivity and Electron Density

IONCAP Ionospheric Communication Analysis and Prediction

IRI International Reference Ionosphere

ISR Incoherent Scatter Radars

LT Local Time

MSIS Mass Spectrometer and Incoherent Scatter

MUF Maximum Usable Frequency

NASA National Aeronautics and Space Administration

NHPC N(h) on PC

NOAA National Oceanic and Atmospheric Administration

PARIM Parameterized Regional Ionosphere Model

PIM Parameterized Ionospheric Model

POLAN Polynomial Analysis

RCS Radar Cross Section

xx

RMSE Root Mean Squared Error

SID Sudden Ionospheric Disturbance

SLIM Semi-Empirical Low-Latitude Ionospheric Model

SOHO Solar and Heliospheric Observatory

SPIDR Space Physics Interactive Data Resource

SSE Sum of Squares due to Eerror

SSN Sunspot Number

SUPIM Sheffield University Plasmasphere-Ionosphere Model

TEC Total Electron Concentration

THO Tun Hussein Onn

UHF Ultra High Frequency

URSI International Union of Radio Science

UTC Universal Time

VHF Very High Frequency

VIS Vertical Incidence Sounding

CHAPTER 1

INTRODUCTION

1.1 BACKGROUND

The knowledge on the state of the upper atmosphere, in particular its ionospheric

part, is very important in several applications affected by space weather. The radio

frequency communications and the satellite positioning and navigation systems are the

most affected ones by ionospheric disturbances. In particular, ionospheric disturbances

can cause drastic changes of large-scale to the usable range of high frequency (HF) or

below high frequency bands affecting the standard ground-to-ground and submarine

communication systems. The effects are recognized as loss of communications, change

in area of coverage, low signal power, fading, and error rate change. Fading and error

rate change are also the effect of very high frequency (VHF) or ultra high frequency

(UHF) band, causing disturbances in ground-to-satellite communication systems.

Ionospheric scintillation and dispersion could lead to loss of phase lock and position

errors, which strongly affects the advanced navigation systems. Therefore, to keep

different technical systems functioning in spite of all these effects, specification and

prediction of the state of the upper atmosphere is of significant important and valuable.

The most important property in the ionosphere is the electron density. This

parameter varies considerably with time (sunspot cycle, seasonally, and diurnally),

geographical location (polar cap, auroral zones, equatorial regions), and with certain

solar disturbances (Davies, 1990). Over the last 60 years, continuous and automatic

monitoring of the state of the ionosphere has been carried out extensively with the

worldwide network of ionosonde stations. The ionospheric electron-density profiles are

modeled and their characteristic parameters are presented through global maps. These

2

models are widely used for effective ionospheric study and forecasting. However, in

some regions the discrepancies are highlighted. The models had under or overestimated

densities that may lead to wrong interpretation of the state of the ionosphere. The

accuracy of the data-based model is highly dependent on the availability of reliable data

for the specific region and time (Bilitza et al., 1993). Inadequate comparisons are

obviously seen in particular at low- and equatorial latitudes regions due to scarce

distribution of ionosonde stations. This scenario had raised interest for researchers and

scientists to extend studies over these regions. More ionosonde stations are installed in

equatorial region and their results are valuable inputs to the improvement of these

models. Readers are referred to Chapter 2.2 for further deliberations on this issue.

The ionosphere over this region was described by Rishbeth (2000) as unique as

it exhibits the well-known equatorial ionization anomaly (EIA). This is characterized by

an ionization trough at the magnetic equator and crests on either side at latitudes around

±16o (Appleton, 1946). The cause of the anomaly is by the equatorial plasma fountain

that transfers ionization from around the equator to higher latitudes (Appleton, 1946).

Peculiar features over this region such as the appearance of an additional ionization

layer above the F2 peak, namely the F3 layer during morning-noon period and the post-

sunset peak are results of the above mentioned mechanism (Bailey and Balan, 1996;

Jenkins et al., 1997; Balan et al., 1998). Located in between the geographical equator at

the south and geomagnetic equator in the north, the location of Malaysia is found to be

very strategic to explore such interesting phenomena. The operational of Parit Raja

ionosonde station is a substantial beginning of this exploration. The station was in

operation in December 2004. It is the only ionosonde station in Malaysia that provides

ionosonde data for region close to magnetic equator.

The ionosonde data is a viable resource to describe the vertical profile of the

ionosphere. The data is analysed to determine the actual F layer height and produce

better description of its variations. The height of peak electron density, hmax, is the

height where maximum electron density occurs. Along with the peak electron density,

Nmax, these parameters made up the electron-density profiles. Thus, ionospheric

observation is a vital step in understanding of the ionospheric behavior. This will be

3

further elaborated in the subsequent chapters. A model that characterised the F region

peak density height variations is the outcome of the study.

1.2 PROBLEM STATEMENT

The ionosphere F region, being the most important region of the ionosphere

exist in the upper atmosphere at an altitude range of 200 km to about 1000 km (Davies,

1990). This region is primarily responsible for most skywave propagation of radio

waves, facilitating high frequency, or shortwave radio communications over long

distances as it has the densest electron density and most important exists at all time

(Davies, 1990; Rishbeth and Garriot, 1969). This layer may also cause signal

attenuation to most space related applications, deteriorating the performance of satellite

radio systems. The equatorial F region is also known to be highly variable corresponds

to the processes which control its production, loss, and transport of electrons, especially

at the altitude range above 250 km (Rishbeth and Garriot, 1969; Rishbeth, 2000). The

greatest electron density, Nmax, occurred at higher altitude and the corresponding height

is referred as the height of maximum electron density, hmax (Rishbeth and Garriot,

1969).

Studies on the F layer height of peak electron density, hmax, received less

attention compared to other ionospheric parameters. Unlike critical frequencies, the

actual height determination process is more complex as the electrons are easily drifted.

This thesis reports on three main problems associated with the actual height of

maximum electron density, hmax, which had inspired research on this parameter, as

below:

i) To enhance the actual height analysis studies in Malaysia.

All ionospheric sounding processes provide only virtual height information.

When Zain et al. (2008) observed the appearance of F3 layer over Parit Raja, the

demand for a precise value of actual height of peak electron density becomes

apparent. The F region peak electron density is assumed to occur at 300 km, as

observed in mid-latitude regions, whereas, in equatorial latitude regions, the

4

height of peak electron density has been reported high, between 350 and 500 km

(Bilitza, undated). The assumptions need further justification considering that

Malaysia is located in the vicinity of equatorial ionization anomaly. The actual

height of peak electron density over Malaysia is still unknown. Varying height is

expected in the diurnal pattern of hmax.

The assertion on varying height of the ionosphere over Malaysia requires

research on the height deviation of hmax. The F region hmax variability study is

important to determine the extent of the height deviation from the mean value

under different ionospheric conditions. The dependence of electron density on

solar radiation is known as the main cause of the hmax variability. The effects are

greater under severe solar activities and geomagnetic storms. Any occurrence of

ionospheric disturbances may change the physical properties of the ionosphere.

The F layer may become unstable, fragmented, or even disappear completely.

The electron-density profile is very significant to illustrate the variation of

electron densities with heights. Different shapes of day and night profiles are

observed to gauge better understanding of the physical mechanisms that control

the processes and behavior of the equatorial ionosphere.

Furthermore, the International Reference Ionosphere (IRI) model verification for

Malaysia has not been extensively reported. The IRI model is the most widely

used empirical model for effective ionospheric study and forecasting globally.

The model becomes the first adopted standard specification of ionospheric

parameters by the Committee on Space Research (COSPAR) and the

International Union of Radio Science (URSI) in 1990. The accuracy of IRI

model in presenting equatorial region densities have been reported elsewhere

(Jesus et al., 2011; Yadav et al., 2010; Wichaipanich et al., 2010), however for

Malaysia, there is no activities conducted related to IRI model verification.

5

ii) The classical way of representing hmax temporal variation in the Cartesian

coordinate system is too conventional

In this study, trend analyses are used to illustrate the characteristic variation

patterns. Appropriate mathematical functions are then used to represent the

temporal variations; for a repetitive function, the Fourier series approximation is

suitable to describe the variations. This is a classical way of representing

temporal variations which is usually represented in a rectangular coordinate

system. An alternative representation is introduced where the diurnal height

variation, which is cyclic in nature, can be represented using polar

representation. By using appropriate formulation, the time variation model is

transformed into polar representation.

iii) Lack of a model to signify the ionospheric height variations

A suitable model representing the characteristic parameter is anticipated at the

end of this study. Equivalence antenna pattern model of ionospheric height of

peak density variations based on antenna radiation characteristics is possible

considering the underlying principle of polar representation. This is a novel

approach introduced in this study by parameterization of the ionospheric height

variation using the attributes of array antenna.

In general, further specifications on the actual height of F layer over equatorial

region require thorough studies in this domain. The Parit Raja ionosonde data may

provide good insight into this anonymous scenario. The experimental data sets are

analysed to obtain concrete justifications to the above statements. In addition,

characterisation of this parameter helps to describe the scenario in a more appropriate

manner.

1.3 OBJECTIVES

The quest for actual F region height of peak electron density over Malaysia

instigates studies in this domain. Important attributes of the F region height of peak

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electron density are used to explain the dependency in the actual behavior of this

parameter to the variations in solar activity, and other geographical constraints. The

objectives of this work in addressing the problem statements described in section 1.2

are:

i) To determine the actual ionospheric F region height of peak electron density,

hmax, overhead, describes its variability (diurnal, seasonal, annual) corresponding

to different ionospheric conditions, and investigate the adequacy of IRI model in

explaining the observed densities in equatorial regions.

The actual heights of ionospheric F region during moderate to low solar activity

period are deduced from hourly ionograms of March, June, September, and

December, 2006 and 2007. The representations are based on median data. The

typical behavior of the F region ionosphere is explained and statistical analyses

are used to quantify the expected deviations from that typical behavior. The

variability of ionospheric characteristics with local time, season, and solar

indices, as a result of known changes in ionising sources and atmospheric

composition are clarified. The results of IRI prediction model will be compared

with observational data to establish an empirical correction to the current model,

if exists.

ii) To develop a descriptive model that represents the diurnal characteristics of the

ionospheric F region height of peak electron density over Malaysia and further

enhanced the classical representation.

A simple, numerical model that can be used to calculate approximate profiles

under any required conditions are derived based on experimental evidence using

data sources from the ionosonde. The descriptive model should give fully

smooth and physically realistic variations at all times. The cyclic nature of the

variations would enable new representation in polar form. Enhancement in the

classical way of representing hmax temporal variation is feasible by using

appropriate transformation of the time domain.

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iii) To model an antenna equivalences of peak height variation.

A signature of ionospheric height of peak density variations in this manner may

represent appropriately the ionospheric F region height variations over Malaysia.

The variations can be described by antenna array design parameters such as

number of elements, element separation, and current and phase in each element.

1.4 SCOPE OF WORK

The scope of work is divided into three main categories according to the

research approach. The description for each of the stages is as follows:

1.4.1 Ionospheric Observation

Ionospheric observation is the most fundamental step in preliminary

understanding of the ionosphere. The ionosonde used to probe the ionosphere is located

at Parit Raja (2oN, 103oW, dip 14.3o), Batu Pahat, Malaysia. Radio soundings are

carried out daily at 5 minutes interval to monitor the state of the ionosphere. The

recorded tracings of reflected high frequency radio pulses are observed regularly to

examine the present ionospheric condition. These ionograms, generated by the

ionosonde, shows the virtual height, h’, of the ionospheric layers as a function of plasma

frequency. Proper inversion method is required to obtain the real height, h. Several

programs arise to facilitate this inversion, among which the polynomial analysis

(POLAN) program and NHPC are widely used at present (Liu et al., 1992). Depending

on the instrument type, the POLAN program developed by Titheridge (1985) is used

extensively in this study. The inversion process is manually performed on individual

ionogram. The tediousness of the inversion process is highly vulnerable to error

especially when there are occurrences of ionospheric disturbances (e.g. spread F and

sporadic E). These disturbances may mislead the ionogram interpretation. Knowledge in

physics and chemistry of ionosphere are necessary to facilitate this process. The output

of POLAN is in text file where in this context, it is still considered as raw data.

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1.4.2 Data Analysis and Trending

The peak electron density, Nmax, and height of peak electron density, hmax, are

two important parameters derived from the ionograms using POLAN. Together with the

solar and geomagnetic data, these data are arranged to form a solid database. The data

assimilation process also involves some pre-processing procedures which categorised

the data according to event types and subsequently extract any geomagnetic dependency

data in the final output. The idea is to produce a database which will produce an ideal

approximation of the ionosphere behavior. The ‘processed data’ are also used to draw

the median Nmax and hmax trends. Different conditions could be considered; diurnal

variations (sunrise, noon time, sunset, midnight), seasonal variations (spring, summer,

autumn, winter), and solar activity (high, low) variations. These are various type of

variability that can weigh up any investigation on the ionospheric behavior. This stage

requires high computational skills and MATLAB program is utilized for this purpose.

1.4.3 Modeling

A numerical model of the diurnal trends of median height of peak electron

density variations is needed to calculate approximate variations at all times. In this case,

appropriate mathematical function is used to represent the characteristic variation

patterns. As for a periodic function, Fourier series approximation is the most suitable fit.

The empirical models are then remodeled into suitable representation before a final

model which constitutes to ionosphere height of peak electron density variations can be

established. The configuration of this new model is the novelty of this study.

1.5 THESIS OUTLINE

This thesis is divided into six main chapters. Chapter 1 introduces the main idea

of the research project. The introduction describes the importance of ionospheric studies

in communication aspects which involves either terrestrial or satellite communication

systems. The idea of having comprehensive global ionospheric profiles is also addressed

which then highlights the equatorial ionosphere as one of the challenging region to

Documents

MODELING THE F REGION IONOSPHERIC PEAK HEIGHT …umpir.ump.edu.my/13178/1/FKEE - ZETI AKMA RHAZALI - CD 9649.pdf · MODELING THE F REGION IONOSPHERIC PEAK HEIGHT VARIATIONS OVER MALAYSIA