Adapting a climatology model to improve estimation of ionosphere parameters and subsequent validation with radio occultation and ionosonde data

Abstract

This paper reports on the adaptation and modification of a climatological model, the International Reference Ionosphere (IRI 2012 model) with the use of total electron content (TEC) data derived from the Global Navigation Satellite System (GNSS), and most importantly its subsequent validation with both radio occultation from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and ionosonde data. By adjusting the solar activity indices used within the standard IRI 2012 model with the aim of minimizing error differences between IRI TEC and GNSS TEC, the adjusted indices are used as drivers of the IRI 2012 model on a regional scale and results for electron density (Ne) profiles, maximum height of the F2 layer (hmF2), TEC, and critical frequency of the F2 layer (foF2) generated. Validation was done by direct comparison with ionosonde and COSMIC‐derived data parameters. By averaging results over low, equatorial, and midlatitude regions, the modified IRI 2012 gave an improvement of about 18% in estimating TEC during the storm period of 9 March 2012. An important result observed during our candidate period of study is that COSMIC data provides maximum electron density of the F2 layer (NmF2) and hmF2 closer to ionosonde data even during the disturbed period and is hence a suitable data set that can be incorporated into the climatological IRI model to improve its performance. The Ne profiles from the modified IRI 2012 model accurately approximates ionosonde Ne profiles especially below 300 km altitude but underestimates the ionosonde NmF2 and hence foF2 in midlatitude regions. In most cases both standard and modified IRI 2012 models match COSMIC data for topside electron density representation, making the COSMIC data set a valuable resource for the improvement of ionospheric climatological models.

On Imaging South African Regional Ionosphere Using 4D‐var Technique

“…Moreover, because IRI is empirical in nature, it does not accurately describe ionospheric dynamics in areas (e.g., Southern Hemisphere/within the African sector) or during times that suffered data paucity during early stages of model development (e.g. Habarulema, ; Habarulema & Ssessanga, ; McKinnell & Poole, ; Okoh et al, ; Ssessanga et al, ).…”

Reconstruction of Storm‐Time Total Electron Content Using Ionospheric Tomography and Artificial Neural Networks: A Comparative Study Over the African Region

“…A similar observation was highlighted in previous works that compared MIDAS reconstructions with IRI predictions (Chartier et al, ; Giday et al, ), and ANN estimations with IRI predictions (Habarulema et al, , ; Okoh et al, ; Watthanasangmechai et al, ). The underestimation of TEC by IRI model compared to MIDAS and ANN can be attributed to difference in altitude ranges TEC is estimated (Chartier et al, ; Habarulema & Ssessanga, ; Kenpankho et al, ). IRI model does generate TEC for the altitude range 60–2,000 km and the contribution of the plasmasphere is therefore not fully taken into account in IRI model.…”

“…For each station considered for validation, IRI TEC data were obtained by running the online IRI‐2016 model available at https://omniweb.gsfc.nasa.gov/vitmo/iri2016_vitmo.html, with NeQuick as topside option and STORM option on. It is also important to mention that IRI model provides TEC values up to the altitude of 2,000 km (Chartier et al, ; Habarulema & Ssessanga, ).…”

On the Development of a Method for Updating an Empirical Climatological Ionospheric Model by Means of Assimilated vTEC Measurements From a GNSS Receiver Network

“…Some authors in the past pursued the goal of assimilating GNSS‐derived measurements in empirical climatological ionospheric models like IRI and NeQuick (Nava et al, ) in order to improve the description that these climatological models provide (Barabashov et al, ; Habarulema & Ssessanga, ; Hernandez‐Pajares et al, ; Komjathy & Langley, ; Komjathy et al, ; Maltseva et al, ; Nava et al, , , ; Olwendo & Cesaroni, ; Ssessanga et al, ). The approaches used, corresponding strengths and weaknesses, and results achieved by these authors have been summarized by Pignalberi et al ().…”

“…The procedure has been implemented and tested over the South African region but can be successfully applied in every region where both GNSS receivers networks and ionosonde stations are available. that these climatological models provide (Barabashov et al, 2006;Habarulema & Ssessanga, 2016;Hernandez-Pajares et al, 2002;Komjathy & Langley, 1996;Komjathy et al, 1998;Maltseva et al, 2010;Nava et al, 2005Nava et al, , 2006Nava et al, , 2011Olwendo & Cesaroni, 2016;Ssessanga et al, 2015). The approaches used, corresponding strengths and weaknesses, and results achieved by these authors have been summarized by Pignalberi et al (2018a).…”