Statistical analysis of the ionospheric response during storm conditions over South Africa using ionosonde and GPS data
- Authors: Matamba, Tshimangadzo Merline
- Date: 2015
- Subjects: Ionospheric storms -- South Africa -- Grahamstown , Ionospheric storms -- South Africa -- Madimbo , Magnetic storms -- South Africa -- Grahamstown , Magnetic storms -- South Africa -- Madimbo , Ionosondes , Global Positioning System
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5555 , http://hdl.handle.net/10962/d1017899
- Description: 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.
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Optimizing MIDAS III over South Africa
- Authors: Giday, Nigussie Mezgebe
- Date: 2014
- Subjects: Multi-Instrument Data Analysis System (MIDAS) , Global Positioning System , Ionosphere -- South Africa , Ionospheric electron density -- South Africa , Ionosondes -- South Africa , Tomography -- Scientific applications -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5517 , http://hdl.handle.net/10962/d1011277 , Multi-Instrument Data Analysis System (MIDAS) , Global Positioning System , Ionosphere -- South Africa , Ionospheric electron density -- South Africa , Ionosondes -- South Africa , Tomography -- Scientific applications -- South Africa
- Description: In this thesis an ionospheric tomographic algorithm called Multi-Instrument Data Anal- ysis System (MIDAS) is used to reconstruct electron density profiles using the Global Positioning System (GPS) data recorded from 53 GPS receivers over the South African region. MIDAS, developed by the Invert group at the University of Bath in the UK, is an inversion algorithm that produces a time dependent 3D image of the electron density of the ionosphere. GPS receivers record the time delay and phase advance of the trans- ionospheric GPS signals that traverse through the ionosphere from which the ionospheric parameter called Total Electron Content (TEC) can be computed. TEC, the line integral of the electron density along the satellite-receiver signal path, is ingested by ionospheric tomographic algorithms such as MIDAS to produce a time dependent 3D electron density profile. In order to validate electron density profiles from MIDAS, MIDAS derived NmF2 values were compared with ionosonde derived NmF2 values extracted from their respective 1D electron density profiles at 15 minute intervals for all four South African ionosonde stations (Grahamstown, Hermanus, Louisvale, and Madimbo). MIDAS 2D images of the electron density showed good diurnal and seasonal patterns; where a comparison of the 2D images at 12h00 UT for all the validation days exhibited maximum electron concentration during the autumn and summer and a minimum during the winter. A root mean square error (rmse) value as small as 0.88x 10¹¹[el=m³] was calculated for the Louisvale ionosonde station during the winter season and a maximum rmse value of 1.92x 10¹¹[el=m³] was ob- tained during the autumn season. The r² values were the least during the autumn and relatively large during summer and winter; similarly the rmse values were found to be a maximum during the autumn and a minimum during the winter indicating that MIDAS performs better during the winter than during the autumn and spring seasons. It is also observed that MIDAS performs better at Louisvale and Madimbo than at Grahamstown and Hermanus. In conclusion, the MIDAS reconstruction has showed good agreement with the ionosonde measurements; therefore, MIDAS can be considered a useful tool to study the ionosphere over the South African region.
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A feasibility study into total electron content prediction using neural networks
- Authors: Habarulema, John Bosco
- Date: 2008
- Subjects: Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5466 , http://hdl.handle.net/10962/d1005251 , Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Description: Global Positioning System (GPS) networks provide an opportunity to study the dynamics and continuous changes in the ionosphere by supplementing ionospheric measurements which are usually obtained by various techniques such as ionosondes, incoherent scatter radars and satellites. Total electron content (TEC) is one of the physical quantities that can be derived from GPS data, and provides an indication of ionospheric variability. This thesis presents 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. Three South African locations were identified and used in the development of an input space and NN architecture for the model. The input space includes the day number (seasonal variation), hour (diurnal variation), sunspot number (measure of the solar activity), and magnetic index(measure of the magnetic activity). An attempt to study the effects of solar wind on TEC variability was carried out using the Advanced Composition Explorer (ACE) data and it is recommended that more study be done using low altitude satellite data. An analysis was done by comparing predicted NN TEC with TEC values from the IRI2001 version of the International Reference Ionosphere (IRI), validating GPS TEC with ionosonde TEC (ITEC) and assessing the performance of the NN model during equinoxes and solstices. Results show that NNs predict GPS TEC more accurately than the IRI at South African GPS locations, but that more good quality GPS data is required before a truly representative empirical GPS TEC model can be released.
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Verification of Ionospheric tomography using MIDAS over Grahamstown, South Africa
- Authors: Katamzi, Zama Thobeka
- Date: 2008
- Subjects: Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5497 , http://hdl.handle.net/10962/d1005283 , Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Description: Global Positioning System (GPS) satellites and receivers are used to derive total electron content (TEC) from the time delay and phase advance of the radiowaves as they travels through the ionosphere. TEC is defined as the integralof the electron density along the satellite-receiver signal path. Electron densityprofiles can be determined from these TEC values using ionospheric tomographic inversion techniques such as Multi-Instrument Data Analysis System (MIDAS).This thesis reports on a study aimed at evaluating the suitability of ionospheric tomography as a tool to derive one-dimensional electron density profiles, using the MIDAS inversion algorithm over Grahamstown, South Africa (33.30◦S, 26.50◦E). The evaluation was done by using ionosonde data from the Louisvale (28.50◦S, 21.20◦E) and Madimbo (22.40◦S, 30.90◦E) stations to create empirical orthonormal functions (EOFs). These EOFs were used by MIDAS in the inversion process to describe the vertical variation of the electron density. Profiles derived from the MIDAS algorithm were compared with profiles obtained from the international Reference Ionosphere (IRI) 2001 model and with ionosonde profiles from the Grahamstown ionosonde station. The optimised MIDAS profiles show a good agreement with the Grahamstown ionosonde profiles. The South African Bottomside Ionospheric Model (SABIM) was used to set the limits within which MIDAS was producing accurate peak electron density (NmF2) values and to define accuracy in this project, with the understanding that the national model (SABIM) is currently the best model for the Grahamstown region. Analysis show that MIDAS produces accurate results during the winter season, which had the lowest root mean square (rms) error of 0.37×1011[e/m3] and an approximately 86% chance of producing NmF2 closer to the actual NmF2 value than the national model SABIM. MIDAS was found to also produce accurate NmF2 values at 12h00 UT, where an approximately 88% chance of producing an accurate NmF2 value, which may deviate from the measured value by 0.72×1011[e/m3], was determined. In conclusion, ionospheric tomographic inversion techniques show promise in the reconstruction of electron density profiles over South Africa, and are worth pursuing further in the future.
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The use of Landsat ETM imagery as a suitable data capture source for alien acacia species for the WFW programme
- Authors: Cobbing, Benedict Louis
- Date: 2007
- Subjects: Geographic information systems , Global Positioning System , Landsat satellites , Agriculture -- Remote sensing , Geography -- Remote sensing
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4856 , http://hdl.handle.net/10962/d1005532 , Geographic information systems , Global Positioning System , Landsat satellites , Agriculture -- Remote sensing , Geography -- Remote sensing
- Description: Geographic Information System technology today allows for the rapid analysis of vast amounts of spatial and non-spatial data. The power of a GIS can only be effected with the rapid collection of accurate input data. This is particularly true in the case of the South African National Working for Water (WFW) Programme where large volumes of spatial data on alien vegetation infestations are captured throughout the country. Alien vegetation clearing contracts cannot be generated, for WFW, without this data, so that the accurate capture of such data is crucial to the success of the programme. Mapping Invasive Alien Plant (IAP) data within WFW is a perennial problem (Coetzee, pers com, 2002), because not enough mapping is being done to meet the annual requirements of the programme in the various provinces. This is re-iterated by Richardson, 2004, who states that there is a shortage of accurate data on IAP abundance in South Africa. Therefore there is a need to investigate alternate methods of data capture; such as remote sensing, whilst working within the existing WFW data capture standards. The aim of this research was to investigate the use of Landsat ETM imagery as a data capture source for mapping alien vegetation for the WFW Programme in terms of their approved mapping methods, for both automated and manual classification techniques. The automated and manual classification results were compared to control data captured by differential Global Positioning Systems (DGPS). The research tested the various methods of data capture using Landsat ETM images over a range of study sites of varying complexity: a simple grassland area, a medium complexity grassy fynbos site and a complicated indigenous forest site. An important component of the research was to develop a mapping (classification) Ranking System based upon variables identified by WFW as fundamental in data capture decision making: spatial and positional accuracy, time constraints and cost constraints for three typical alien invaded areas. The mapping Ranking System compared the results of the various mapping methods for each factor for the study sites against each other. This provided an indication of which mapping method is the most efficient or suitable for a particular area.
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Ionospheric total electron content variability and its influence in radio astronomy
- Authors: Botai, Ondego Joel
- Date: 2006
- Subjects: Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5473 , http://hdl.handle.net/10962/d1005258 , Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Description: Ionospheric phase delays of radio signals from Global Positioning System (GPS) satellites have been used to compute ionospheric Total Electron Content (TEC). An extended Chapman profle model is used to estimate the electron density profles and TEC. The Chapman profle that can be used to predict TEC over the mid-latitudes only applies during day time. To model night time TEC variability, a polynomial function is fitted to the night time peak electron density profles derived from the online International Reference Ionosphere (IRI) 2001. The observed and predicted TEC and its variability have been used to study ionospheric in°uence on Radio Astronomy in South Africa region. Di®erential phase delays of the radio signals from Radio Astronomy sources have been simulated using TEC. Using the simulated phase delays, the azimuth and declination o®sets of the radio sources have been estimated. Results indicate that, pointing errors of the order of miliarcseconds (mas) are likely if the ionospheric phase delays are not corrected for. These delays are not uniform and vary over a broad spectrum of timescales. This implies that fast frequency (referencing) switching, closure phases and fringe ¯tting schemes for ionospheric correction in astrometry are not the best option as they do not capture the real state of the ionosphere especially if the switching time is greater than the ionospheric TEC variability. However, advantage can be taken of the GPS satellite data available at intervals of a second from the GPS receiver network in South Africa to derive parameters which could be used to correct for the ionospheric delays. Furthermore GPS data can also be used to monitor the occurrence of scintillations, (which might corrupt radio signals) especially for the proposed, Square Kilometer Array (SKA) stations closer to the equatorial belt during magnetic storms and sub-storms. A 10 minute snapshot of GPS data recorded with the Hermanus [34:420 S, 19:220 E ] dual frequency receiver on 2003-04-11 did not show the occurrence of scintillations. This time scale is however too short and cannot be representative. Longer time scales; hours, days, seasons are needed to monitor the occurrence of scintillations.
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