Assessment of the predictive capabilities of NIGTEC model over Nigeria during geomagnetic storms - Paul Obiakara Amaechi (KeAi Communications Co., Ltd., 2021)
The Nigerian Total Electron Content (NIGTEC) is a regional neural network-based model developed by the Nigerian Centre for Atmospheric Research to predict the Total Electron Content (TEC) at any location over Nigeria. The addition of the disturbance storm time (Dst) index as one of NIGTEC's input layer neurons raises a question of its accuracy during geomagnetic storms. In this paper, the capability of NIGTEC in predicting the variability of TEC during geomagnetic storms has been assessed. TEC data predicted by NIGTEC is compared with those derived from Global Navigation Satellite System (GNSS) over Lagos (6.5oN, 3.4oE) and Toro (10.1oN, 9.12oE) during the intense storms in March 2012 and 2013. The model's predictive capability is evaluated in terms of Root Mean Square Error (RMSE). NIGTEC reproduced a fairly good storm time morphology in VTEC driven by the prompt penetration electric field and the increase in thermospheric O/N2. Nevertheless, it failed to predict the increase in TEC after the intense sudden impulse of 60 nT on 8 March 2012. And it could not capture the changes in VTEC driven by the storm time equatorward neutral wind especially during 18:00–24:00 UT. Consequently, the RMSEs were higher during this time window, and the highest RMSE value was obtained during the most intense storm in March 2012.