Assessment of improvement of the IRI model over Ethiopia for the modeling of the variability of TEC during the period 2013–2016

This paper discusses the monthly and seasonal variation of the total electron content (TEC) and the improvement of performance of the IRI model in estimating TEC over Ethiopia during the solar maximum (2013–2016) phase employing as reference the GPS derived TEC data inferred from four GPS receivers installed in different regions of Ethiopia; Assosa (geog 10.05°N, 34.55°E, Geom. 7.01°N), Ambo (8.97°N, 37.86°E, Geom. 5.42°N), Nazret (8.57°N, 39.29°E, Geom. 4.81°N) and Arba Minch (6.06°N, 37.56°E, Geom. 2.62°N). The results reveal that, in the years 2013–2016, the highest peak GPS-derived diurnal VTEC is observed in the March equinox in 2015 over Arba Minch station. Moreover, both the arithmetic mean GPS-derived and modelled VTEC values, generally, show maximum and minimum values in the equinoctial and June solstice months, respectively in 2014–2015. However, in 2013, the minimum and maximum arithmetic mean GPS-derived values are observed in the March equinox and December solstice, respectively. The results also show that, even though overestimation of the modelled VTEC has been observed on most of the hours, all versions of the model are generally good to estimate both the monthly and seasonal diurnal hourly VTEC values, especially in the early morning hours (00:00–03:00?UT or 03:00–06:00?LT). However, it has also been shown that the IRI 2007 and IRI 2012 versions generally perform best in matching the diurnal GPS derived TEC values as compared to that of the IRI 2016 version. In addition, the IRI 2012 version with IRI2001 option for the topside electron density shows the highest overestimation of the VTEC as compared to the other options. None of the versions of the IRI model are proved to be able to capture the effects of geomagnetic storms.     

Comparison of GPS TEC variations with IRI-2007 TEC prediction at equatorial latitudes during a low solar activity (2009–2011) phase over the Kenyan region

This work presents an analysis of the Total Electron Content (TEC) derived from the International GNSS Service (IGS) receivers at Malindi (mal2: 2.9^oS, 40.1^oE, dip −26.813^o), Kasarani (rcmn: 36.89^oE, 1.2^oS, dip −23.970^o), Eldoret (moiu: 35.3^oE, 0.3^oN, dip −21.037^o) and GPS-SCINDA (36.8^oE, 1.3^oS, dip −24.117^o) receiver located in Nairobi for the period 2009–2011. The diurnal, monthly and seasonal variations of the GPS derived TEC (GPS-TEC) and effects of space weather on TEC are compared with TEC from the 2007 International Reference Ionosphere model (IRI-TEC) using the NeQuick option for the topside electron density. The diurnal peaks in GPS-TEC is maximum during equinoctial months (March, April, October) and in December and minimum in June solstice months (May, June, July). The variability in GPS-TEC is minimal in all seasons between 0:00 and 04:00 UT and maximum near noon between 10:00 and 14:00 UT. Significant variability in TEC at post sunset hours after 16:00 UT (19:00 LT) has been noted in all the seasons except in June solstice. The TEC variability of the post sunset hours is associated with the occurrence of the ionization anomaly crest which enhances nighttime TEC over this region. A comparison between the GPS-TEC and IRI-TEC indicates that both the model and observation depicts a similar trend in the monthly and seasonal variations. However seasonal averages show that IRI-TEC values are higher than the GPS-TEC. The IRI-TEC also depicts a double peak in diurnal values unlike the GPS-TEC. This overestimation which is primarily during daytime hours could be due to the model overestimation of the equatorial anomaly effect on levels of ionospheric ionization over the low latitude regions. The IRI-TEC also does not show any response to geomagnetic activity, despite the STORM option being selected in the model; the IRI model generally remains smooth and underestimates TEC during a storm. The GPS-TEC variability indicated by standard deviation seasonal averages has been presented as a basis for extending the IRI-model to accommodate TEC-variability.