Assessment of ionosphere models at Banting: Performance of IRI-2007, IRI-2012 and NeQuick 2 models during the ascending phase of Solar Cycle 24. Issue 8 (15th April 2015) - Leong, S.K.; Musa, T.A.; Omar, K.; Subari, M.D.; Pathy, N.B.; Asillam, M.F.
Abstract The International Reference Ionosphere (IRI) and the NeQuick models have been recognised as the international standard for specifying Earth's ionospheric parameters. However, the performance of these ionosphere models needs to be validated due to data scarcity from South-East Asian region for model development. This work presents the performance evaluation of IRI-2007, IRI-2012 and NeQuick 2 in estimating ionospheric Total Electron Content (TEC) at Banting (Geographic: 2.78°N, 101.51°E; Geomagnetic: 7.11°S, 173.77°E). For this purpose, TEC values estimated from these models have been compared with TEC values derived from dual-frequency Global Positioning System (GPS) data for the year 2011 (ascending phase of Solar Cycle 24). The results show that equatorial TEC exhibits semi-annual, annual, and seasonal variations with maximum values appearing during equinoctial months and minimum during solstitial months. Generally, ionospheric TEC produced by IRI and NeQuick 2 models are in good agreement with observed TEC. For diurnal variation, the IRI-2007 and NeQuick 2 models show good agreement during post-noon and post-midnight, respectively. Good correlation is observed during noon-time for all models. Disagreements between ionospheric models and observed TEC are found during post-sunset and post-midnight periods, with TEC deviation in the level of 11–14 TECU can be anticipated at 95% probability. On the other hand, TEC calculation from IRI-2012 is better than IRI-2007 and NeQuick 2 for monthly variation. All models score correlation coefficient above 0.9 with the highest correlation noticed during solstitial months. TEC deviation above 10 and up to 15 TECU can be expected in October with 95% probability. Overall, this work reveals that IRI and NeQuick 2 models are capable of predicting TEC with good correlation in most cases.