The ionosphere is of practical importance for satellite-based communication and navigation systems due to its variable refractive nature which affects the propagation of trans-ionospheric radio signals. This thesis reports on the first attempt to investigate the mechanisms responsible for the generation of positive ionospheric storm effects over mid-latitude South Africa. The storm response on 15 May 2005 was associated with equatorward neutral winds and the passage of travelling ionospheric disturbances (TIDs). The two TIDs reported in this thesis propagated with average velocities of ∼438 m/s and ∼515 m/s respectively. The velocity of the first TID (i.e. 438 m/s) is consistent with the velocities calculated in other studies for the same storm event. In a second case study, the positive storm enhancement on both 25 and 27 July 2004 lasted for more than 7 hours, and were classified as long-duration positive ionospheric storm effects. It has been suggested that the long-duration positive storm effects could have been caused by large-scale thermospheric wind circulation and enhanced equatorward neutral winds. These processes were in turn most likely to have been driven by enhanced and sustained energy input in the high-latitude ionosphere due to Joule heating and particle energy injection. This is evident by the prolonged high-level geomagnetic activity on both 25 and 27 July. This thesis also reports on the phase scintillation investigation at the South African Antarctic polar research station during solar minimum conditions. The multi-instrument approach that was used shows that the scintillation events were associated with auroral electron precipitation and that substorms play an essential role in the production of scintillation in the high latitudes. Furthermore, the investigation reveals that external energy injection into the ionosphere is necessary for the development of high-latitude irregularities which produce scintillation. Finally, this thesis highlights inadequate data resources as one of the major shortcomings to be addressed in order to fully understand and distinguish between the various ionospheric storm drivers over the Southern Africa mid-latitude region. The results presented in this thesis on the ionospheric response during geomagnetic storms provide essential information to direct further investigation aimed at developing this emerging field of study in South Africa.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (p. 108-119).

The occurrence of mid-latitude spread F (SF) over South Africa has not been extensively studied since the installation of the DPS-4 digisondes at Madimbo (30.88◦E, 22.38◦S), Grahamstown (33.32◦S, 26.50◦E) and Louisvale (28.51◦S, 21.24◦E). This study is intended to quantify the probability of the occurrence of F region disturbances associated with ionospheric spread F (SF) and L-band scintillation over South Africa. This study used available ionosonde data for 8 years (2000-2008) from the three South African stations. The SF events were identified manually on ionograms and grouped for further statistical analysis into frequency SF (FSF), range SF (RSF) and mixed SF (MSF). The results show that the diurnal pattern of SF occurrence peaks strongly between 23:00 and 00:00 UT. This pattern is true for all seasons and types of SF at Madimbo and Grahamstown during 2001 and 2005, except for RSF which had peaks during autumn and spring during 2001 at Madimbo. The probability of both MSF and FSF tends to increase with decreasing sunspot number (SSN), with a peak in 2005 (a moderate solar activity period). The seasonal peaks of MSF and FSF are more frequent during winter months at both Madimbo and Grahamstown. In this study SF was evident in ∼ 0.03% and ∼ 0.06% of the available ionograms at Madimbo and Grahamstown respectively during the eight year period. The presence of ionospheric irregularities associated with SF and scintillation was investigated using data from selected Global Positioning System (GPS) receiver stations distributed across South Africa. The results, based on GPS total electron content (TEC) and ionosonde measurements, show that SF over this region can most likely be attributed to travelling ionospheric disturbances (TIDs), caused by gravity waves (GWs) and neutral wind composition changes. The GWs were mostly associated with geomagnetic storms and sub-storms that occurred during periods of high and moderate solar activity (2001-2005). SF occurrence during the low solar activity period (2006-2008)can probably be attributed to neutral wind composition changes.

It has been shown in ionospheric research that modelling total electron content (TEC) during storm conditions is a big challenge. In this study, mathematical equations were developed to estimate TEC over Sutherland (32.38⁰S, 20.81⁰E), during storm conditions, using the Empirical Orthogonal Function (EOF) analysis, combined with regression analysis. TEC was derived from GPS observations and a geomagnetic storm was defined for Dst ≤ -50 nT. The inputs for the model were chosen based on the factors that influence TEC variation, such as diurnal, seasonal, solar and geomagnetic activity variation, and these were represented by hour of the day, day number of the year, F10.7 and A index respectively. The EOF model was developed using GPS TEC data from 1999 to 2013 and tested on different storms. For the model validation (interpolation), three storms were chosen in 2000 (solar maximum period) and three others in 2006 (solar minimum period), while for extrapolation six storms including three in 2014 and three in 2015 were chosen. Before building the model, TEC values for the selected 2000 and 2006 storms were removed from the dataset used to construct the model in order to make the model validation independent on data. A comparison of the observed and modelled TEC showed that the EOF model works well for storms with non-significant ionospheric TEC response and storms that occurred during periods of low solar activity. High correlation coefficients between the observed and modelled TEC were obtained showing that the model covers most of the information contained in the observed TEC. Furthermore, it has been shown that the EOF model developed for a specific station may be used to estimate TEC over other locations within a latitudinal and longitudinal coverage of 8.7⁰ and 10.6⁰ respectively. This is an important result as it reduces the data dimensionality problem for computational purposes. It may therefore not be necessary for regional storm-time TEC modelling to compute TEC data for all the closest GPS receiver stations since most of the needed information can be extracted from measurements at one location.

Ionospheric storms are an extreme form of space weather phenomena which affect space- and ground-based technological systems. Extreme solar activity may give rise to Coronal Mass Ejections (CME) and solar flares that may result in ionospheric storms. This thesis reports on a statistical analysis of the ionospheric response over the ionosonde stations Grahamstown (33.3◦S, 26.5◦E) and Madimbo (22.4◦S,30.9◦E), South Africa, during geomagnetic storm conditions which occurred during the period 1996 - 2011. Total Electron Content (TEC) derived from Global Positioning System (GPS) data by a dual Frequency receiver and an ionosonde at Grahamstown, was analysed for the storms that occurred during the period 2006 - 2011. A comprehensive analysis of the critical frequency of the F2 layer (foF2) and TEC was done. To identify the geomagnetically disturbed conditions the Disturbance storm time (Dst) index with a storm criteria of Dst ≤ −50 nT was used. The ionospheric disturbances were categorized into three responses, namely single disturbance, double disturbance and not significant (NS) ionospheric storms. Single disturbance ionospheric storms refer to positive (P) and negative (N) ionospheric storms observed separately, while double disturbance storms refer to negative and positive ionospheric storms observed during the same storm period. The statistics show the impact of geomagnetic storms on the ionosphere and indicate that negative ionospheric effects follow the solar cycle. In general, only a few ionospheric storms (0.11%) were observed during solar minimum. Positive ionospheric storms occurred most frequently (47.54%) during the declining phase of solar cycle 23. Seasonally, negative ionospheric storms occurred mostly during the summer (63.24%), while positive ionospheric storms occurred frequently during the winter (53.62%). An important finding is that only negative ionospheric storms were observed during great geomagnetic storm activity (Dst ≤ −350 nT). For periods when both ionosonde and GPS was available, the two data sets indicated similar ionospheric responses. Hence, GPS data can be used to effectively identify the ionospheric response in the absence of ionosonde data.

Solar transient eruptions are the main cause of interplanetary-magnetospheric disturbances leading to the phenomena known as geomagnetic storms. Eruptive solar events such as coronal mass ejections (CMEs) are currently considered the main cause of geomagnetic storms (GMS). GMS are strong perturbations of the Earth’s magnetic field that can affect space-borne and ground-based technological systems. The solar-terrestrial impact on modern technological systems is commonly known as Space Weather. Part of the research study described in this thesis was to investigate and establish a relationship between GMS (periods with Dst ≤ −50 nT) and their associated solar and interplanetary (IP) properties during solar cycle (SC) 23. Solar and IP geoeffective properties associated with or without CMEs were investigated and used to qualitatively characterise both intense and moderate storms. The results of this analysis specifically provide an estimate of the main sources of GMS during an average 11-year solar activity period. This study indicates that during SC 23, the majority of intense GMS (83%) were associated with CMEs, while the non-associated CME storms were dominant among moderate storms. GMS phenomena are the result of a complex and non-linear chaotic system involving the Sun, the IP medium, the magnetosphere and ionosphere, which make the prediction of these phenomena challenging. This thesis also explored the predictability of both the occurrence and strength of GMS. Due to their nonlinear driving mechanisms, the prediction of GMS was attempted by the use of neural network (NN) techniques, known for their non-linear modelling capabilities. To predict the occurrence of storms, a combination of solar and IP parameters were used as inputs in the NN model that proved to predict the occurrence of GMS with a probability of 87%. Using the solar wind (SW) and IP magnetic field (IMF) parameters, a separate NN-based model was developed to predict the storm-time strength as measured by the global Dst and ap geomagnetic indices, as well as by the locally measured K-index. The performance of the models was tested on data sets which were not part of the NN training process. The results obtained indicate that NN models provide a reliable alternative method for empirically predicting the occurrence and strength of GMS on the basis of solar and IP parameters. The demonstrated ability to predict the geoeffectiveness of solar and IP transient events is a key step in the goal towards improving space weather modelling and prediction.