Effects of local time on the variations of the total electron contents at an American and Asian longitudes and their comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 models during solar cycle 24

Ionospheric modelling is one of the major tools to study the behavior of the ionosphere. Ionospheric models have been useful in predicting the true state of the ionosphere particularly in regions where Global Positioning System (GPS) are not readily available. This research paper aims to study the longitudinal variations and the effects of local time on the total electron content (TEC) recorded in two different sectors (Asia and America) during the ascending, maximum and descending phases of solar cycle 24 (2011–2017) and also to compare its values to IRI-2016, IRI-Plas2017 and NeQuick-2 models in order to evaluate their performances. An hourly interval profile computed on seasonal basis were used to study the behaviors of TEC diurnally and seasonally. A monthly interval error profile plotted on annual basis was also used to investigate the deviations of the models from the GPS values. Our results showed that the peak values of TEC in the Asian and American sectors were recorded around the dawn,06:00UT (13:00LT) and dusk, 18:00UT (15:00LT) respectively. We also affirmed from our results that seasonal/winter anomalies were recorded in all the phases of the solar cycle in both sectors. Equinoctial Asymmetry was also observed to be predominant during different phases of the solar cycle in both sectors except during ascending and descending phases in the Asian and American sectors respectively. Out of the 168 months of data collated for this study, only 162 months of data were available. The IRI-2016, IRI-Plas2017 and NeQuick-2 models have 11.7%, 23.5% and 64.8% better performance in all the months under consideration. Therefore, the NeQuick-2 model had the best performance in both the Asian and American sectors. Finally, from the results of our statistical analysis, Mean Absolute Error (MAE) has ∼3 TECU lower than the Root Mean Square Error (RMSE) values in both sectors and in all the solar cycle phase. Hence, MAE can evaluate the performance of ionospheric models better than RMSE.