A contribution to TEC modelling over Southern Africa using GPS data

Modelling ionospheric total electron content (TEC) is an important area of interest for radio wave propagation, geodesy, surveying, the understanding of space weather dynamics and error correction in relation to Global Navigation Satellite Systems (GNNS) applications. With the utilisation of improved ionosonde technology coupled with the use of GNSS, the response of technological systems due to changes in the ionosphere during both quiet and disturbed conditions can be historically inferred. TEC values are usually derived from GNSS measurements using mathematically intensive algorithms. However, the techniques used to estimate these TEC values depend heavily on the availability of near-real time GNSS data, and therefore, are sometimes unable to generate complete datasets. This thesis investigated possibilities for the modelling of TEC values derived from the South African Global Positioning System (GPS)receiver network using linear regression methods and artificial neural networks (NNs). GPS TEC values were derived using the Adjusted Spherical Harmonic Analysis (ASHA) algorithm. Considering TEC and the factors that influence its variability as “dependent and independent variables” respectively, the capabilities of linear regression methods and NNs for TEC modelling were first investigated using a small dataset from two GPS receiver stations. NN and regression models were separately developed and used to reproduce TEC fluctuations at different stations not included in the models’ development. For this purpose, TEC was modelled as a function of diurnal variation, seasonal variation, solar and magnetic activities. Comparative analysis showed that NN models provide predictions of GPS TEC that were an improvement on those predicted by the regression models developed. A separate study to empirically investigate the effects of solar wind on GPS TEC was carried out. Quantitative results indicated that solar wind does not have a significant influence on TEC variability. The final TEC simulation model developed makes use of the NN technique to find the relationship between historical TEC data variations and factors that are known to influence TEC variability (such as solar and magnetic activities, diurnal and seasonal variations and the geographical locations of the respective GPS stations) for the purposes of regional TEC modelling and mapping. The NN technique in conjunction with interpolation and extrapolation methods makes it possible to construct ionospheric TEC maps and to analyse the spatial and temporal TEC behaviour over Southern Africa. For independent validation, modelled TEC values were compared to ionosonde TEC and the International Reference Ionosphere (IRI) generated TEC values during both quiet and disturbed conditions. This thesis provides a comprehensive guide on the development of TEC models for predicting ionospheric variability over the South African region, and forms a significant contribution to ionospheric modelling efforts in Africa

Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks

In this paper, first results from a national Global Positioning System (GPS) based total electron content (TEC) prediction model over South Africa are presented. Data for 10 GPS receiver stations distributed through out the country were used to train a feed forward neural network (NN) over an interval of at most five years. In the NN training, validating and testing processes, five factors which are well known to influence TEC variability namely diurnal variation, seasonal variation, magnetic activity, solar activity and the geographic position of the GPS receivers were included in the NN model. The database consisted of 1-min data and therefore the NN model developed can be used to forecast TEC values 1 min in advance. Results from the NN national model (NM) were compared with hourly TEC values generated by the earlier developed NN single station models (SSMs) at Sutherland (32.38°S, 20.81°E) and Springbok (29.67°S, 17.88°E), to predict TEC variations over the Cape Town (33.95°S, 18.47°E) and Upington (28.41°S, 21.26°E) stations, respectively, during equinoxes and solstices. This revealed that, on average, the NM led to an improvement in TEC prediction accuracy compared to the SSMs for the considered testing periods

A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results

This paper attempts to describe the search for the parameter(s) to represent solar wind effects in Global Positioning System total electron content (GPS TEC) modelling using the technique of neural networks (NNs). A study is carried out by including solar wind velocity (Vsw), proton number density (Np) and the Bz component of the interplanetary magnetic field (IMF Bz) obtained from the Advanced Composition Explorer (ACE) satellite as separate inputs to the NN each along with day number of the year (DN), hour (HR), a 4-month running mean of the daily sunspot number (R4) and the running mean of the previous eight 3-hourly magnetic A index values (A8). Hourly GPS TEC values derived from a dual frequency receiver located at Sutherland (32.38° S, 20.81° E), South Africa for 8 years (2000–2007) have been used to train the Elman neural network (ENN) and the result has been used to predict TEC variations for a GPS station located at Cape Town (33.95° S, 18.47° E). Quantitative results indicate that each of the parameters considered may have some degree of influence on GPS TEC at certain periods although a decrease in prediction accuracy is also observed for some parameters for different days and seasons. It is also evident that there is still a difficulty in predicting TEC values during disturbed conditions. The improvements and degradation in prediction accuracies are both close to the benchmark values which lends weight to the belief that diurnal, seasonal, solar and magnetic variabilities may be the major determinants of TEC variability

Application of neural networks to South African GPS TEC modelling

The propagation of radio signals in the Earth’s atmosphere is dominantly affected by the ionosphere due to its dispersive nature. Global Positioning System (GPS) data provides relevant information that leads to the derivation of total electron content (TEC) which can be considered as the ionosphere’s measure of ionisation. This paper presents part of a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Vertical total electron content (VTEC) was calculated for four GPS receiver stations using the Adjusted Spherical Harmonic (ASHA) model. Factors that influence TEC were then identified and used to derive input parameters for the NN. The well established factors used are seasonal variation, diurnal variation, solar activity and magnetic activity. Comparison of diurnal predicted TEC values from both the NN model and the International Reference Ionosphere (IRI-2001) with GPS TEC revealed that the IRI provides more accurate predictions than the NN model during the spring equinoxes. However, on average the NN model predicts GPS TEC more accurately than the IRI model over the GPS locations considered within South Africa

Simultaneous storm time equatorward and poleward large-scale TIDs on a global scale

We report on the first simultaneous observations of poleward and equatorward traveling ionospheric disturbances (TIDs) during the same geomagnetic storm period on a global scale. While poleward propagating TIDs originate from the geomagnetic equator region, equatorward propagating TIDs are launched from the auroral regions. On a global scale, we use total electron content observations from the Global Navigation Satellite Systems to show that these TIDs existed over South American, African, and Asian sectors. The American and African sectors exhibited predominantly strong poleward TIDs, while the Asian sector recorded mostly equatorward TIDs which crossed the geomagnetic equator to either hemisphere on 9 March 2012. However, both poleward and equatorward TIDs are simultaneously present in all three sectors. Using a combination of ground-based magnetometer observations and available low-latitude radar (JULIA) data, we have established and confirmed that poleward TIDs of geomagnetic equator origin are due to ionospheric electrodynamics, specifically changes in E × B vertical drift after the storm onset

Storm Time Global Observations of Largeâ Scale TIDs From Groundâ Based and In Situ Satellite Measurements

This paper discusses the ionosphere’s response to the largest storm of solar cycle 24 during 16â 18 March 2015. We have used the Global Navigation Satellite Systems (GNSS) total electron content data to study largeâ scale traveling ionospheric disturbances (TIDs) over the American, African, and Asian regions. Equatorward largeâ scale TIDs propagated and crossed the equator to the other side of the hemisphere especially over the American and Asian sectors. Poleward TIDs with velocities in the range â 400â 700 m/s have been observed during local daytime over the American and African sectors with origin from around the geomagnetic equator. Our investigation over the American sector shows that poleward TIDs may have been launched by increased Lorentz coupling as a result of penetrating electric field during the southward turning of the interplanetary magnetic field, Bz. We have observed increase in SWARM satellite electron density (Ne) at the same time when equatorward largeâ scale TIDs are visible over the Europeanâ African sector. The altitude Ne profiles from ionosonde observations show a possible link that stormâ induced TIDs may have influenced the plasma distribution in the topside ionosphere at SWARM satellite altitude.Key PointsIncreased SWARM in situ electron density toward high latitudes in presence of equatorward largeâ scale TIDsEvidence of equatorward TIDs in influencing altitudinal plasma distribution to the topside ionospherePossibility of poleward TIDs launched from the geomagnetic equatorial region with comparable velocity values in both hemispheresPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142539/1/jgra53978_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142539/2/jgra53978.pd

Simultaneous Occurrence of Traveling Ionospheric Disturbances, Farley Buneman and Gradient Drift Instabilities Observed by the Zhongshan SuperDARN HF Radar

We show that Traveling Ionospheric Disturbances (TIDs) may affect the Farley Buneman Instability (FBI) and Gradient Drift Instability (GDI) echoes referred to as the Near Range Echoes (NREs) in the SuperDARN radar backscatter from the lower part of the E‐region. TIDs and NREs are observed concomitantly by the Zhongshan SuperDARN radar (69.38°S, 76.38°E) in the far and near ranges, respectively. At the moment, there is no study about the effects of TIDs on the NREs caused by the FBI using the SuperDARN radars. The GDI are more likely to occur at a lower altitude while FBI occurs at a slightly higher altitude in the lower part of the ionospheric E‐region. We use the Spearman Correlation Coefficient (SCC) to show that a part of the NREs backscatter power could be statistically explained by the MSTIDs backscatter power received by the same radar. We also investigate the simultaneous occurrence rate of the NREs and MSTIDs during the 24th solar cycle. Seasonal variability shows that MSTIDs‐NREs events over Zhongshan mostly occur in summer and equinoxes during local night and morning. The majority of these events lasted between ∼4 and ∼8 hr. Most events disappeared early in the morning. Statistics of the Spearman correlation coefficient values show that ∼9% of NRE amplitude modulation could be due to the MSTIDs. There are almost equal numbers of negative and positive Spearman correlation coefficient values. The relative velocity between the E‐region NREs and the F‐region MSTIDs switching the electric field polarities between the crests and troughs could be the cause of those equal number of the Spearman correlation coefficient values. The orientation of the ionospheric current relative to the MSTID polarization electric field may also play a significant role in the reported Spearman correlation coefficient values. We argue that in some cases, the TIDs might have been close enough to the NREs altitude to modulate them directly by transporting the plasma up and down through shear or compression

Multi-instrument observations of large-scale atmospheric gravity waves/traveling ionospheric disturbances associated with enhanced auroral activity over Svalbard

This study reports on observations of large-scale atmospheric gravity waves/traveling ionospheric disturbances (AGWs/TIDs) using Global Positioning System (GPS) total electron content (TEC) and Fabry-Perot Interferometer’s (FPI’s) intensity of oxygen red line emission at 630 nm measurements over Svalbard on the night of 6 January 2014. TEC large-scale TIDs have primary periods ranging between 29 and 65 minutes and propagate at a mean horizontal velocity of ∼749–761 m/s with azimuth of ∼345°–347° (which corresponds to poleward propagation direction). On the other hand, FPI large-scale AGWs have larger periods of ∼42–142 minutes. These large-scale AGWs/TIDs were linked to enhanced auroral activity identified from co-located all-sky camera and IMAGE magnetometers. Similar periods, speed and poleward propagation were found for the all-sky camera (∼60–97 minutes and ∼823 m/s) and the IMAGE magnetometers (∼32–53 minutes and ∼708 m/s) observations. Joule heating or/and particle precipitation as a result of auroral energy injection were identified as likely generation mechanisms for these disturbances