Techniques for monitoring ionospheric dynamics

Abstract

Fluctuations in the ionospheric electron density can have consequences for a range of terrestrial systems including satellites, navigation and communications. Accurate modelling of these fluctuations is needed to ensure that affected systems perform effectively. Enhancing our understanding of the ionosphere can help to improve ionospheric models. In this project changes in the ionosphere are studied using existing and new approaches to enhance our understanding. The parameters investigated are the E region critical frequency (foE) and the corresponding height (hmE), F region critical frequency (foF2) and corresponding height (hmF2), and total electron content (TEC). These parameters were observed by ionosondes, and by a new technique that analyses signals transmitted between geostationary satellites of the Global Positioning System (GPS) constellation and single frequency receivers on the ground.

Ionosonde data were analysed over six Decembers, and GPS TEC over a full year. foF2 and GPS derived TEC were strongly correlated. The parameters hmF2 and foF2 were strongly anti-correlated, as were hmF2 and GPS derived TEC. E region parameters were found not to be well correlated with any other parameters. Attempts to use the IRI-2012 and IRI-2016 models to remove the diurnal cycle showed large discrepancies between ionosonde measurements and IRI time series. Removing the diurnal cycle showed that the observed correlations were mostly the result of solar forcing. One parameter pair, foE and hmE, showed a correlation of 0.5 without the diurnal cycle, which has not yet been explained. foF2 and hmF2 as well as foF2 and GPS derived TEC remained strongly correlated in geomagnetically disturbed conditions, but a range of responses were seen for disturbed correlations between hmF2 and GPS TEC.

This correlation analysis is a powerful tool which is used in this project to demonstrate and validates a new technique of TEC derivation using single frequency signals transmitted between geostationary satellites and ground-based GPS receivers. The correlation analysis showed good agreement over a year both between pairs of GPS receivers and between GPS receivers and ionosonde observations. Correlations between pairs of GPS receivers were consistently high during disturbed conditions, and good agreement was also seen between derived TEC and data from the Multi Instrument Data Analysis System (MIDAS). The analysis suggests that the technique is capable of routinely producing realistic TEC time series in both calm and disturbed geomagnetic conditions. The technique shows potential to become a routine method for real-time TEC derivation.

Date of Award	13 Feb 2019
Original language	English
Awarding Institution	University of Bath
Supervisor	Cathryn Mitchell (Supervisor) & Ivan Astin (Supervisor)