Present day challenges in understanding the geomagnetic hazard to national power grids
- 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
- 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.
- Full Text:
- Date Issued: 2010
- 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.
- Full Text:
- Date Issued: 2010
A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results
- Habarulema, John B, McKinnell, Lee-Anne, Opperman, Ben D L
- 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.
- Full Text:
- Date Issued: 2009
- 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.
- Full Text:
- Date Issued: 2009
Application of neural networks to South African GPS TEC modelling
- Habarulema, John B, McKinnell, Lee-Anne, Cilliers, Pierre J, Opperman, Ben D L
- 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.
- Full Text:
- Date Issued: 2009
- 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.
- Full Text:
- Date Issued: 2009
Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks
- Habarulema, John B, McKinnell, Lee-Anne, Opperman, Ben D L
- 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.
- Full Text:
- Date Issued: 2009
- 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.
- Full Text:
- Date Issued: 2009
Development of a regional GPS-based ionospheric TEC model for South Africa
- Opperman, Ben D L, Cilliers, Pierre J, McKinnell, Lee-Anne, Haggard, Raymond
- 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.
- Full Text:
- Date Issued: 2007
- 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.
- Full Text:
- Date Issued: 2007
GPS TEC and ionosonde TEC over Grahamstown, South Africa: first comparisons
- McKinnell, Lee-Anne, Opperman, Ben D L, Cilliers, Pierre J
- 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.
- Full Text:
- Date Issued: 2007
- 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.
- Full Text:
- Date Issued: 2007
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