LAUSR

Abstract Accurate modeling of ionospheric total electron content (TEC) is an important aspect for mitigating the threats of trans-ionospheric delay error in satellite communication, earth observation, space-based navigation, timing applications as well as space weather forecasting services. In recent years, singular spectrum analysis (SSA) has been proved to be a powerful technique giving a relatively accurate estimate in time-series analysis comparable to the contemporary methods. In the current study, the SSA has been implemented on the GPS-derived TEC during the low solar activity year of 2017 over Nepal region which locates itself almost in the vicinity of low-latitudes being sandwiched between India and Tibet, China. The country foresees an explicit investigation and modeling of ionospheric TEC variations and corresponding delay error to precisely accomplish the space-based trans-ionospheric applications. The semi-annual variability of TEC with higher magnitudes during equinoctial seasons and lower values during solstice seasons is clearly noticed in the diurnal plots which are further substantiated by the trajectory matrix of time-series. The decomposed modes in the principal component analysis (PCA) signifies diurnal (first), semidiurnal (second), semiannual (third), monthly (fourth) with higher orders representing associated noise errors in the signals. Correlation coefficients (CC) between the reconstructed and observed time-series demonstrates the SSA method could be a successful tool for forecasting the TEC series over the region. The results are compared with empirical global ionospheric maps (GIMs) and IRI-Plas 2017 models during different seasons, emphasizing the suitability of SSA technique for relatively better precise TEC forecasting over the region.