Forecasting of Global Ionospheric Perturbation Maps Using GIM and ARIMA as a Precursor of Earthquake

Summary The study of seismo-ionosphere interaction with respect to earthquake events using Total Electron Content (TEC) data deriving from receivers of global navigation satellite systems (GNSSs) are increasingly being used to detect pre-earthquake ionospheric anomalies. This is primarily because ionospheric anomaly variation has been considered to constitute one possible method to identify earthquake precursors. In this paper, we have reported significant evidence for pre-seismic ionospheric anomalies of TEC in the global ionosphere anomaly map (GIM) to visualize the perturbations before the 28 September 2018 Mw=7.5 Indonesia Tsunami. After distinguishing other anomalies related to the geomagnetic and solar activities, it is found to be of seismogenic origin. But the data availability has a delay of 3–5 days. To make it in real time we have used the statistical regression model (ARIMA) to forecast the real-time prediction model from the anomaly trend, which matches with the data derived from the GNSS with a promising accuracy and the predicted epicenters are also falling within 120 km of the real one. Statistical approach of forecasting worldwide TEC value prior to the earthquakes may provide some new and beneficial insights for the future study of ionospheric earthquake precursors.