Interaction of global electron content with the Sun and solar wind during intense geomagnetic storms.

Assessment of solar and solar wind parameters driving the ionosphere model is essential for prediction of the ionospheric weather. In the present paper impact of the different solar, interplanetary and geomagnetic parameters on the global electron content (GEC) during intense space weather storms is investigated. Hourly GEC values are calculated from JPL global maps of total electron content GIM-TEC from 1995 to 2023. The sample comprises 90 intense storms from 1995 to 2023 associated with monthly peak of the weighted accumulation of the geomagnetic Apo (τ, t) index exceeding 90 nT. The 27 day weighted accumulation of the solar sunspot numbers SSN2 (τ), solar radio flux F10.7 (τ), the solar hydrogen emission Lyman _ α (τ) and the composite magnesium MgII (τ) indices are explored as precursors of GEC enhancements. As distinct from the positive ionosphere storm, the solar wind speed Vsw , the solar wind electric field Ey , merging electric field Em and Apo (τ, t) indices proved to be effective as potential drivers of the negative GEC depletion. The positive and negative dGEC deviations from hourly GEC are produced by subtracting a quiet reference GECav averaged during 24h prior the storm normalized by GECav. The hourly storm profiles Vsw(t) , Em(t) , Ey(t) , Apo (τ, t), Dst(t) , GEC(t) and dGEC(t) were reduced by method of superposed epochs. The zero epoch t 0 = 0 was taken at the peak Apo* (τ, t 0) and the storm time lasted for 48h from −12h prior t 0 and 35h afterwards. The best correlation of the positive storm dGECp amplitude is obtained with MgII (τ) and the negative storm dGECn with E m * and Apo* (τ, t 0) which are used to derive characteristics of five key points of storm-time dGEC (t) model: 1 – onset of the storm profile t 1 = t(dGECp) ; 2 – the amplitude dGECp max and its time t 2 (dGECp max); 3 – the time of transition t 3 (dGEC = 0) from the positive to negative (±) GEC storm; 4 – minimum negative disturbance dGECn min and its time t 4 (dGECn min), 5 – the end of the storm profile t 5 (dGECn). Analytical model of dGEC (t) is derived with Epstein step functions fitting 5 key points. Deviations dGEC (t) are inverted to GEC (t) using quiet reference pre-storm GECav. The model is validated for three intense storms on 26–28 February, 23–25 March and 23–25 April 2023. The results show improvement of dGEC forecast with RMS error reduced from 45 to 80% compared to results produced by the international reference ionosphere−plasmasphere model IRI-Plas. • Accumulation SSN2(τ), F10.7(τ), Lyman-α(τ), MgII(τ) show the best correlation of MgII(τ) with positive GEC storm. • Sample 90 intense storms for 1995–2023 are reduced by superposing with zero epoch at Apo (τ, t) > 90 nT. • Solar wind merging electric field Em proved to be the best precursor for Apo (τ , t), Dst(t) and negative GEC storm. • dGEC (t) forecasting model with MGII (τ) and Em field precursors shows RMSE improved by 45–80% compared to IRI-Plas. [ABSTRACT FROM AUTHOR]