Short-term Adaptive Forecast Model for TEC over equatorial low latitude region

In today's world, satellite navigation is one of the most widely used navigational aids, which is why accurate positioning is of critical importance. The ionosphere's Total Electron Content (TEC) is a significant contributor to the positional error in signal traveling between a satellite and the earth and reduces the system's positional accuracy. The ionosphere adds an excess delay to the radio wave traversing through it, resulting in position estimation error. Since the delay is a function of the ionospheric parameter TEC, estimation of TEC can help in correcting the errors. The challenge in estimating TEC in the equatorial region is that it exhibits a non-deterministic or unpredictable characteristic due to the complex electrodynamics resulting from Equatorial Ionospheric Anomaly (EIA). In addition, space weather phenomena like geomagnetic storms further disturb the ionosphere causing irregular short-term disturbances. This study explores the inherent VTEC pattern during geomagnetic storm conditions, especially during the high solar activity period, and proposes a short-term adaptive segmented regression model to forecast VTEC. The study is undertaken over six years of high solar activity period in the 24th solar cycle. The forecast model uses both linear and polynomial autoregression coefficients of recent past data. The model's performance is evaluated for extreme conditions, including the high solar activity and geomagnetic storms, which are the most challenging scenario for TEC prediction. The ac-curacy of the predicted output is calculated in terms of RMSE and correlation coefficient. The results were also compared with IRI 2016 model. The proposed short-term prediction model thus aims to help fill the precision required by long-term forecast models by considering near real-time nonlinear dynamics in the ionosphere.