scholarly journals A study on the variability of ionospheric total electron content over the East African low-latitude region and storm time ionospheric variations

Radio Science ◽  
2016 ◽  
Vol 51 (9) ◽  
pp. 1503-1518 ◽  
Author(s):  
O. J. Olwendo ◽  
Yosuke Yamazaki ◽  
P. J. Cilliers ◽  
P. Baki ◽  
P. Doherty
2018 ◽  
Author(s):  
Geoffrey Andima ◽  
Emirant B. Amabayo ◽  
Edward Jurua ◽  
Pierre J. Cilliers

Abstract. In this paper, an empirical total electron content (TEC) model and trends in TEC over the African low latitude region are presented. GPS-derived TEC data from Malindi, Kenya (geographic coordinates 40.194° E, 2.996° S) and global ionospheric maps (GIMs) were used. We employed empirical orthogonal function (EOF) analysis method together with least square regression to model the TEC. The EOF-based TEC model was validated through comparisons with GIMs, GPS-derived TEC and TEC derived from the International Reference Ionosphere-2016 (IRI-2016) model for selected quiet and storm conditions. The single station EOF-based TEC model over Malindi satisfactory reproduced the known diurnal, semiannual and annual variations in the TEC. Comparison of the EOF-based TEC model results with TEC derived from IRI-2016 model showed that the EOF-based model predicted the TEC over Malindi with less errors than the IRI-2016. For the selected storms, the EOF-based TEC model simulated the storm time TEC response over Malindi better than the IRI-2016. In the case of the regional model, the EOF-based TEC model was able to reproduce the TEC characteristics in the equatorial ionization anomaly region. The EOF-based TEC model was then used as a background in estimating TEC trends. A latitudinal dependence in the trends was observed over the African low latitude region.


2019 ◽  
Vol 37 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Geoffrey Andima ◽  
Emirant B. Amabayo ◽  
Edward Jurua ◽  
Pierre J. Cilliers

Abstract. In this paper, an empirical total electron content (TEC) model and trends in the TEC over the African low-latitude region are presented. GPS-derived TEC data from Malindi, Kenya (geographic coordinates 40.194∘ E, 2.996∘ S), and global ionospheric maps (GIMs) were used. We employed an empirical orthogonal function (EOF) analysis method together with least-squares regression to model the TEC. The EOF-based TEC model was validated through comparisons with GIMs, the GPS-derived TEC and the TEC derived from the International Reference Ionosphere 2016 (IRI-2016) model for selected quiet and storm conditions. The single-station EOF-based TEC model over Malindi satisfactorily reproduced the known diurnal, semiannual and annual variations in the TEC. Comparison of the EOF-based TEC model results with the TEC derived from the IRI-2016 model showed that the EOF-based model predicted the TEC over Malindi with fewer errors than the IRI-2016. For the selected storms, the EOF-based TEC model simulated the storm time TEC response over Malindi better than the IRI-2016. In the case of the regional model, the EOF-based TEC model was able to reproduce the TEC characteristics in the equatorial ionization anomaly region. The EOF-based TEC model was then used as a background for estimating TEC trends. A latitudinal dependence in the trends was observed over the African low-latitude region.


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