Developing an ionospheric map for South Africa
- Authors: McKinnell, Lee-Anne , Okoh, D I , Cilliers, P J
- Date: 2010
- Language: English
- Type: Article
- Identifier: vital:6822 , http://hdl.handle.net/10962/d1004438 , http://dx.doi.org/10.5194/angeo-28-1431-2010
- Description: The development of a map of the ionosphere over South Africa is presented in this paper. The International Reference Ionosphere (IRI) model, South African Bottomside Ionospheric Model (SABIM), and measurements from ionosondes in the South African Ionosonde Network, were combined within their own limitations to develop an accurate representation of the South African ionosphere. The map is essentially in the form of a computer program that shows spatial and temporal representations of the South African ionosphere for a given set of geophysical parameters. A validation of the map is attempted using a comparison of Total Electron Content (TEC) values derived from the map, from the IRI model, and from Global Positioning System (GPS) measurements. It is foreseen that the final South African ionospheric map will be implemented as a Space Weather product of the African Space Weather Regional Warning Centre.
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- Date Issued: 2010
Present day challenges in understanding the geomagnetic hazard to national power grids
- Authors: Thompson, A W P , Kotze, P , Ngwira, C M , Lotz, Stefanus I , Gaunt, C T , Cilliers, P , Wild, J A , Opperman, Ben D L , McKinnell, Lee-Anne , Lotz, S I
- Date: 2010
- Language: English
- Type: Article
- Identifier: vital:6812 , http://hdl.handle.net/10962/d1004305
- Description: Power grids and pipeline networks at all latitudes are known to be at risk from the natural hazard of geomagnetically induced currents. At a recent workshop in South Africa, UK and South African scientists and engineers discussed the current understanding of this hazard, as it affects major power systems in Europe and Africa. They also summarised, to better inform the public and industry, what can be said with some certainty about the hazard and what research is yet required to develop useful tools for geomagnetic hazard mitigation.
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- Date Issued: 2010
Validation of University of New Brunswick Ionospheric Modeling Technique with ionosonde TEC estimation over South Africa
- Authors: Moeketsi, D M , McKinnell, Lee-Anne , Combrinck, W L
- Date: 2009-09-01
- Language: English
- Type: Article
- Identifier: vital:6809 , http://hdl.handle.net/10962/d1004302
- Description: For more than a decade, ionospheric research over South Africa has been carried out using data from ionosondes geographically located at Madimbo (28.38°S, 30.88°E), Grahamstown (33.32°S, 26.50°E), and Louisvale (28.51°S, 21.24°E). The objective has been modelling the bottomside ionospheric characteristics using neural networks. The use of Global Navigation Satellite System (GNSS) data is described as a new technique to monitor the dynamics and variations of the ionosphere over South Africa, with possible future application in high frequency radio communication. For this task, the University of New Brunswick Ionospheric Modelling Technique (UNB-IMT) was applied to compute midday (10:00 UT) GNSS-derived total electron content (GTEC). GTEC values were computed using GNSS data for stations located near ionosondes for the years 2002 and 2005 near solar maximum and minimum, respectively. The GTEC was compared with the midday ionosonde-derived TEC (ITEC) measurements to validate the UNB-IMT results. It was found that the variation trends of GTEC and ITEC over all stations are in good agreement and show a pronounced seasonal variation for the period near solar maximum, with maximum values ( 80 TECU) around autumn and spring equinoxes, and minimum values ( 22 TECU) around winter and summer. Furthermore, the residual ΔTEC = GTEC − ITEC was computed. It was evident that ΔTEC, which is believed to correspond to plasmaspheric electron content, showed a pronounced seasonal variation with maximum values ( 20 TECU) around equinoxes and minimum ( 5 TECU) around winter near solar maximum. The equivalent ionospheric and total slab thicknesses were also computed and comprehensively discussed. The results verified the use of UNB-IMT as one of the tools for future ionospheric TEC research over South Africa.
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A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results
- Authors: Habarulema, John B , McKinnell, Lee-Anne , Opperman, Ben D L
- Date: 2009
- Language: English
- Type: text , Article
- Identifier: vital:6813 , http://hdl.handle.net/10962/d1004323
- Description: 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.
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- Date Issued: 2009
Application of neural networks to South African GPS TEC modelling
- Authors: Habarulema, John B , McKinnell, Lee-Anne , Cilliers, Pierre J , Opperman, Ben D L
- Date: 2009
- Language: English
- Type: Article
- Identifier: vital:6807 , http://hdl.handle.net/10962/d1004193 , http://dx.doi.org/10.1016/j.asr.2008.08.020
- Description: 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.
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- Date Issued: 2009
Evaluating the IRI topside model for the South African region: An overview of the modelling techniques
- Authors: Sibanda, Patrick , McKinnell, Lee-Anne
- Date: 2009
- Language: English
- Type: text , Article
- Identifier: vital:6810 , http://hdl.handle.net/10962/d1004303
- Description: The representation of the topside ionosphere (the region above the F2 peak) is critical because of the limited experimental data available. Over the years, a wide range of models have been developed in an effort to represent the behaviour and the shape of the electron density (Ne) profile of the topside ionosphere. Various studies have been centred around calculating the vertical scale height (VSH) and have included (a) obtaining VSH from Global Positioning System (GPS) derived total electron content (TEC), (b) calculating the VSH from ground-based ionosonde measurements, (c) using topside sounder vertical Ne profiles to obtain the VSH. One or a combination of the topside profilers (Chapman function, exponential function, sech-squared (Epstein) function, and/or parabolic function) is then used to reconstruct the topside Ne profile. The different approaches and the modelling techniques are discussed with a view to identifying the most adequate approach to apply to the South African region’s topside modelling efforts. The IRI-2001 topside model is evaluated based on how well it reproduces measured topside profiles over the South African region. This study is a first step in the process of developing a South African topside ionosphere model.
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- Date Issued: 2009
Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks
- Authors: Habarulema, John B , McKinnell, Lee-Anne , Opperman, Ben D L
- Date: 2009
- Language: English
- Type: text , Article
- Identifier: vital:6806 , http://hdl.handle.net/10962/d1004192
- Description: 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.
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- Date Issued: 2009
Development of a regional GPS-based ionospheric TEC model for South Africa
- Authors: Opperman, Ben D L , Cilliers, Pierre J , McKinnell, Lee-Anne , Haggard, Raymond
- Date: 2007
- Language: English
- Type: Article
- Identifier: vital:6799 , http://hdl.handle.net/10962/d1003925
- Description: Advances in South African space physics research and related disciplines require better spatial and time resolution ionospheric information than was previously possible with the existing ionosonde network. A GPS-based, variable degree adjusted spherical harmonic (ASHA) model was developed for near real-time regional ionospheric total electron content (TEC) mapping over South Africa. Slant TEC values along oblique GPS signal paths are quantified from a network of GPS receivers and converted to vertical TEC by means of the single layer mapping function. The ASHA model coefficients and GPS differential biases are estimated from vertical TEC at the ionospheric pierce points and used to interpolate TEC at any location within the region of interest. Diurnal TEC variations with one minute time resolution and time-varying 2D regional TEC maps are constructed. In order to validate the ASHA method, simulations with an IRI ionosphere were performed, while the ASHA results from actual data were compared with two independent GPS-based methodologies and measured ionosonde data.
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- Date Issued: 2007
GPS TEC and ionosonde TEC over Grahamstown, South Africa: first comparisons
- Authors: McKinnell, Lee-Anne , Opperman, Ben D L , Cilliers, Pierre J
- Date: 2007
- Language: English
- Type: Article
- Identifier: vital:6800 , http://hdl.handle.net/10962/d1004163
- Description: The Grahamstown, South Africa (33.3°S, 26.5°E) ionospheric field station operates a UMass Lowell digital pulse ionospheric sounder (Digisonde) and an Ashtech geodetic grade dual frequency GPS receiver. The GPS receiver is owned by Chief Directorate Surveys and Mapping (CDSM) in Cape Town, forms part of the national TrigNet network and was installed in February 2005. The sampling rates of the GPS receiver and Digisonde were set to 1 s and 15 min, respectively. Data from four continuous months, March–June 2005 inclusive, were considered in this initial investigation. Data available from the Grahamstown GPS receiver was limited, and, therefore, only these 4 months have been considered. Total Electron Content (TEC) values were determined from GPS measurements obtained from satellites passing near vertical (within an 80° elevation) to the station. TEC values were obtained from ionograms recorded at times within 5 min of the near vertical GPS measurement. The GPS derived TEC values are referred to as GTEC and the ionogram derived TEC values as ITEC. Comparisons of GTEC and ITEC values are presented in this paper. The differential clock biases of the GPS satellites and receivers are taken into account. The plasmaspheric contribution to the TEC can be inferred from the results, and confirm findings obtained by other groups. This paper describes the groundwork for a procedure that will allow the validation of GPS derived ionospheric information with ionosonde data. This work will be of interest to the International Reference Ionosphere (IRI) community since GPS receivers are becoming recognised as another source for ionospheric information.
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- Date Issued: 2007
Mapping GPS-derived ionospheric Total Electron Content over Southern Africa during different epochs of solar cycle 23
- Authors: Moeketsi, D M , Combrinck, W L , McKinnell, Lee-Anne , Fedrizz, M
- Date: 2007
- Language: English
- Type: Article
- Identifier: vital:6802 , http://hdl.handle.net/10962/d1004165
- Description: The Southern African Development Community and the International Global Navigation Satellite Systems Service (GNSS) network of dual frequency Global Positioning System (GPS) receivers provide an opportunity to determine Total Electron Content (TEC) over Southern Africa by taking advantage of the dispersive nature of the ionospheric medium. For this task, the University of New Brunswick (UNB) ionospheric modelling technique which applies a spatial linear approximation of the vertical TEC above each station using stochastic parameters in Kalman filter estimation, primed with data from the Southern Africa GPS network, was used for mapping TEC at South African locations during selected days and hours of different epochs of solar cycle 23. Significant enhancements in the TEC value and features, which could be associated with frequent solar events, are evident around a day of extreme solar maximum. These observations are discussed and further investigated by analyzing the GOES 8 and 10 satellites X-ray flux (0.1–0.8 nm) and SOHO Solar EUV Monitor (26.0–34.0 nm) higher resolution data. Comparison of these physical quantities reveals that for each X-ray flare observed, there is an associated EUV flare event. The latter phenomenon causes photoionisation in the daytime ionosphere which results in significant TEC enhancement. The daytime UNB TEC compared with the International Reference Ionosphere (IRI) 2001 predicted TEC found both models to show a good agreement.
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- Date Issued: 2007
Neural network-based prediction techniques for global modeling of M(3000)F2 ionospheric parameter
- Authors: Oyeyemi, E O , McKinnell, Lee-Anne , Poole, Allon W V
- Date: 2007
- Language: English
- Type: text , Article
- Identifier: vital:6803 , http://hdl.handle.net/10962/d1004166
- Description: In recent times neural networks (NNs) have been employed to solve many problems in ionospheric predictions. This paper illustrates a new application of NNs in developing a global model of the ionospheric propagation factor M(3000)F2. NNs were trained with daily hourly values of M(3000)F2 from various ionospheric stations spanning the period 1964–1986 with the following temporal and spatial input parameters: Universal Time, geographic latitude, magnetic inclination, magnetic declination, solar zenith angle, day of the year, A16 index (a 2-day running mean of the 3-h planetary magnetic ap index), R2 index (a 2-month running mean of sunspot number), and the angle of meridian relative to the subsolar point. The performance of the NNs was verified by comparing the predicted values of M(3000)F2 with observed values from a few selected ionospheric stations and the IRI (International Reference Ionosphere) model (CCIR M(3000)F2 model) predicted values. The results obtained compared favourably with the IRI model. Based on the error differences, the result obtained justifies the potential of the NN technique for the predictions of M(3000)F2 values on a global scale.
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- Date Issued: 2007
Near-real time foF2 predictions using neural networks
- Authors: Oyeyemi, E O , McKinnell, Lee-Anne , Poole, Allon W V
- Date: 2006
- Language: English
- Type: text , Article
- Identifier: vital:6804 , http://hdl.handle.net/10962/d1004167
- Description: This paper describes the use of the neural network (NN) technique for the development of a near-real time global foF2 (NRTNN) empirical model. The data used are hourly daily values of foF2 from 26 worldwide ionospheric stations (based on availability) during the period 1976–1986 for training the NN and between 1977 and 1989 for verifying the prediction accuracy. The training data set includes all periods of quiet and disturbed geomagnetic conditions. Two categories of input parameters were used as inputs to the NN. The first category consists of geophysical parameters that are temporally or spatially related to the training stations. The second category, which is related to the foF2 itself, consists of three recent past observations of foF2 (i.e. real-time foF2 (F0), 2 h (F−2) and 1 h (F−1) prior to F0) from four control stations (i.e. Boulder (40.0°N, 254.7°E), Grahamstown (33.3°S, 26.5°E), Dourbes (50.1°N, 4.6°E) and Port Stanley (51.7°S, 302.2°E). The performance of the NRTNN was verified under both geomagnetically quiet and disturbed conditions with observed data from a few verification stations. A comparison of the root mean square error (RMSE) differences between measured values and the NRTNN predictions with our earlier standard foF2 NN empirical model is also illustrated. The results reveal that NRTNN will predict foF2 in near-real time with about 1 MHz RMSE difference anywhere on the globe, provided real time data is available at the four control stations. From the results it is also evident that in addition to the geophysical information from any geographical location, recent past observations of foF2 from these control stations could be used as inputs to a NN for near-real time foF2 predictions. Results also reveal that there is a temporal correlation between measured foF2 values at different locations.
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- Date Issued: 2006
An analysis of automatically scaled F1 layer data over Grahamstown, South Africa
- Authors: Jacobs, Linda , Poole, Allon W V , McKinnell, Lee-Anne
- Date: 2004
- Language: English
- Type: text , Article
- Identifier: vital:6808 , http://hdl.handle.net/10962/d1004194
- Description: This paper describes an analysis of automatically scaled F1 layer data over Grahamstown, South Africa (33.3°S, 26.5°E). An application for real time raytracing through the South African ionosphere was identified, and for this application real time evaluation of the electron density profile is essential. Raw real time virtual height data are provided by a Lowell Digisonde (DPS), which employs the automatic scaling software, ARTIST whose output includes the virtual-to-real height data conversion. Experience has shown that there are times when the raytracing performance is degraded because of difficulties surrounding the real time characterisation of the F1 region by ARTIST. The purpose of this investigation is to establish the extent of the problem, the times and conditions under which it occurs, with a view to formulating remedial alternative strategies, such as predictive modelling.
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- Date Issued: 2004
Neural network-based ionospheric modelling over the South African region
- Authors: McKinnell, Lee-Anne , Poole, Allon W V
- Date: 2004
- Language: English
- Type: Article
- Identifier: vital:6795 , http://hdl.handle.net/10962/d1003839
- Description: During the past decade, South African scientists have pioneered research in the field of ionospheric modelling using the technique of neural networks (NNs). Global ionospheric models have always been insufficient for the South African region owing to an historical paucity of available data. Within the past 10 years, however, three new ionospheric sounders have been installed locally and are operating continuously. These sounders are located at Grahamstown (33.3°S, 26.5°E), Louisvale (28.5°S, 21.2°E) and Madimbo (22.4°S, 30.9°E). The addition of a modern sounder at Grahamstown enlarged the ionospheric database for this station to 30 years, making this archive a considerable asset for ionospheric research. Quality control and online availability of the data has also added to its attraction. An important requirement for empirical modelling, but especially for employing NNs, is a large database describing the history of the relationship between the ionosphere and the geophysical parameters that define its behaviour. This review describes the path of South African ionospheric modelling over the past 10 years, the role of NNs in this development, the international collaborations that have arisen from this, and the future of ionospheric modelling in South Africa.
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- Date Issued: 2004