Lee-Anne McKinnell

Bio: Lee-Anne McKinnell is an academic researcher from South African National Space Agency. The author has contributed to research in topics: Total electron content & International Reference Ionosphere. The author has an hindex of 25, co-authored 73 publications receiving 2186 citations. Previous affiliations of Lee-Anne McKinnell include Rhodes University.

The International Reference Ionosphere 2012 – a model of international collaboration

Abstract: The International Reference Ionosphere (IRI) project was established jointly by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) in the late sixties with the goal to develop an international standard for the specification of plasma parameters in the Earth’s ionosphere. COSPAR needed such a specification for the evaluation of environmental effects on spacecraft and experiments in space, and URSI for radiowave propagation studies and applications. At the request of COSPAR and URSI, IRI was developed as a data-based model to avoid the uncertainty of theory-based models which are only as good as the evolving theoretical understanding. Being based on most of the available and reliable observations of the ionospheric plasma from the ground and from space, IRI describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 km to 2000 km. A working group of about 50 international ionospheric experts is in charge of developing and improving the IRI model. Over time as new data became available and new modeling techniques emerged, steadily improved editions of the IRI model have been published. This paper gives a brief history of the IRI project and describes the latest version of the model, IRI-2012. It also briefly discusses efforts to develop a real-time IRI model. The IRI homepage is at http://IRImodel.org.

The international reference ionosphere today and in the future

Abstract: The international reference ionosphere (IRI) is the internationally recognized and recommended standard for the specification of plasma parameters in Earth’s ionosphere. It describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 to 1,500 km. A joint working group of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) is in charge of developing and improving the IRI model. As requested by COSPAR and URSI, IRI is an empirical model being based on most of the available and reliable data sources for the ionospheric plasma. The paper describes the latest version of the model and reviews efforts towards future improvements, including the development of new global models for the F2 peak density and height, and a new approach to describe the electron density in the topside and plasmasphere. Our emphasis will be on the electron density because it is the IRI parameter most relevant to geodetic techniques and studies. Annual IRI meetings are the main venue for the discussion of IRI activities, future improvements, and additions to the model. A new special IRI task force activity is focusing on the development of a real-time IRI (RT-IRI) by combining data assimilation techniques with the IRI model. A first RT-IRI task force meeting was held in 2009 in Colorado Springs. We will review the outcome of this meeting and the plans for the future. The IRI homepage is at http://www.IRI.gsfc.nasa.gov.

Prediction of global positioning system total electron content using Neural Networks over South Africa

Abstract: Global positioning system (GPS) networks have provided an opportunity to study the dynamics and continuous changes in the ionosphere by supplementing ionospheric studies carried out using various techniques including 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 paper presents a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. Three South African locations were identified and used in the development of an input space and NN architecture for the model. The input space included the day number (seasonal variation), hour (diurnal variation), Sunspot Number (measure of the solar activity), and magnetic index (measure of the magnetic activity). An analysis was done by comparing predicted NN TEC with TEC values from the IRI-2001 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. For this feasibility model, GPS TEC was derived for a limited number of years using an algorithm still in the early phases of validation. However, 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.

On the global model for foF2 using neural networks

Abstract: [1] The use of neural networks (NNs) has been employed in this work to develop a global model of the ionospheric F2 region critical frequency, foF2. The main principle behind our approach has been to utilize parameters other than simple geographic coordinates, on which foF2 is known to depend, and to exploit the ability of NNs to establish and model this nonlinear relationship for predictive purposes. The foF2 data used in the training of the NNs were obtained from 59 ionospheric stations across the globe at various times from 1964 to 1986, on the basis of availability. To test the success of this approach, one NN (NN1) was trained without data from 13 stations, selected for their geographic remoteness, which could then be used to validate the predictions of the NN for those remote coordinates. These stations were subsequently included in our final NN (NN2). The input parameters consisted of day number (day of the year), universal time, solar activity, magnetic activity, geographic latitude, angle of meridian relative to subsolar point, magnetic dip angle, magnetic declination, and solar zenith angle. Comparisons between foF2 values determined using NNs and the International Reference Ionosphere (IRI) model (from Union Radio Scientifique Internationale (URSI) and International Radio Consultative Committee (CCIR) coefficients) with observed values are given with their root-mean-square (RMS) error differences for test stations. The results from NN2 are used to produce the global behavior of hourly values of foF2 and are compared with the IRI model using URSI and CCIR coefficients. The results obtained (i.e., RMS error differences), which compare favorably with the IRI models, justify this technique for global foF2 modeling.

Application of neural networks to South African GPS TEC modelling

Abstract: 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.

International Reference Ionosphere 2007: Improvements and new parameters

Abstract: The International Reference Ionosphere (IRI), a joint project of URSI and COSPAR, is the de facto international standard for the climatological specification of ionospheric parameters and as such it is currently undergoing registration as Technical Specification (TS) of the International Standardization Organization (ISO). IRI by charter and design is an empirical model based on a wide range of ground and space data. It describes monthly averages of ionospheric densities and temperatures in the altitude range 50–1500 km in the non-auroral ionosphere. Since its inception in 1969 the IRI model has been steadily improved with newer data and with better mathematical descriptions of global and temporal variation patterns. A large number of independent studies have validated the IRI model in comparisons with direct and indirect ionospheric measurements not used in the model development. A comparison with IRI is often one of the first science tasks by an ionospheric satellite or rocket team. This paper describes the latest version of the IRI model, IRI-2007, explaining the most important changes that are being introduced with this version. These include: (1) two new options for the topside electron density, (2) a new model for the topside ion composition, (3) the first-time inclusion of a model for the spread F occurrence probability, (4) a NeuralNet model for auroral E-region electron densities, (5) a model for the plasmaspheric electron temperature, and (6) the latest International Geomagnetic Reference Field (IGRF) model for the computation of magnetic coordinates including their changes due to the secular variation of the magnetic field.

International Reference Ionosphere 2016: From ionospheric climate to real‐time weather predictions

Abstract: The paper presents the latest version of the International Reference Ionosphere model (IRI-2016) describing the most important changes and improvements that were included with this version and discussing their impact on the IRI predictions of ionospheric parameters. IRI-2016 includes two new model options for the F2 peak height hmF2 and a better representation of topside ion densities at very low and high solar activities. In addition, a number of smaller changes were made concerning the use of solar indices and the speedup of the computer program. We also review the latest developments toward a Real-Time IRI. The goal is to progress from predicting climatology to describing the real-time weather conditions in the ionosphere.

The International Reference Ionosphere 2012 – a model of international collaboration

Abstract: The International Reference Ionosphere (IRI) project was established jointly by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) in the late sixties with the goal to develop an international standard for the specification of plasma parameters in the Earth’s ionosphere. COSPAR needed such a specification for the evaluation of environmental effects on spacecraft and experiments in space, and URSI for radiowave propagation studies and applications. At the request of COSPAR and URSI, IRI was developed as a data-based model to avoid the uncertainty of theory-based models which are only as good as the evolving theoretical understanding. Being based on most of the available and reliable observations of the ionospheric plasma from the ground and from space, IRI describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 km to 2000 km. A working group of about 50 international ionospheric experts is in charge of developing and improving the IRI model. Over time as new data became available and new modeling techniques emerged, steadily improved editions of the IRI model have been published. This paper gives a brief history of the IRI project and describes the latest version of the model, IRI-2012. It also briefly discusses efforts to develop a real-time IRI model. The IRI homepage is at http://IRImodel.org.

The international reference ionosphere today and in the future

Abstract: The international reference ionosphere (IRI) is the internationally recognized and recommended standard for the specification of plasma parameters in Earth’s ionosphere. It describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 to 1,500 km. A joint working group of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) is in charge of developing and improving the IRI model. As requested by COSPAR and URSI, IRI is an empirical model being based on most of the available and reliable data sources for the ionospheric plasma. The paper describes the latest version of the model and reviews efforts towards future improvements, including the development of new global models for the F2 peak density and height, and a new approach to describe the electron density in the topside and plasmasphere. Our emphasis will be on the electron density because it is the IRI parameter most relevant to geodetic techniques and studies. Annual IRI meetings are the main venue for the discussion of IRI activities, future improvements, and additions to the model. A new special IRI task force activity is focusing on the development of a real-time IRI (RT-IRI) by combining data assimilation techniques with the IRI model. A first RT-IRI task force meeting was held in 2009 in Colorado Springs. We will review the outcome of this meeting and the plans for the future. The IRI homepage is at http://www.IRI.gsfc.nasa.gov.

The Effects of Geomagnetic Disturbances on Electrical Systems at the Earth's Surface - An Update

Abstract: Abstract Geomagnetic disturbances have affected electrical systems on the ground for over 150 years. The first effects were noted on the early telegraph in the 1840s and in this century magnetic storms have caused power system blackouts and phone system outages. Affected systems include all those that use electrical conductors: whether for transmission of power or signals or where the conducting properties are incidental to their use such as with pipelines and railway tracks. In power systems geomagnetically induced currents cause partial saturation of power transformers producing transformer heating and distortion of the ac waveform leading to misoperation of relays and other equipment. On pipelines, induced currents may contribute to corrosion but also present a problem with the electrical surveys of the pipe performed to monitor the corrosion prevention systems. Severity of these effects depends on disturbance size, proximity to the auroral zone, and the conductivity structure of the Earth. Also significant are system parameters such as the use of higher resistance coatings on pipelines and the linking of power systems into larger networks. In this paper we have attempted to catalogue all the published reports of geomagnetic effects on electrical systems and show their occurrence in the context of the solar cycle and geomagnetic activity variations for the years 1844 to 1996.