Discussing Total Electron Content over the Solar Wind Parameters

Modeling and forecasting of Total Electron Content (TEC) values by an Artificial Neural Network model (ANNm) have high agreement on November 2003, 2004 superstorms. The work discusses Solar Wind Parameters (SWp) from OMNI (Operating Missions as a Node the Internet) TEC (TECU) data (International Reference Ionosphere) IRI-2012, IRI-2016 20, 2003 (Dst = –422 nT) 08, –374 Geomagnetic Storms (GSs). paper commences with 120-hour GS exhibition SWp proceeds correlation variables, their hierarchical tracks, inner dispersions. ANNm input output are introduced. performance for superstorms is adequate. Correlation Coefficient (R) Root Mean Square Error (RMSE) 97.5%, 1.17 TECU (IRI-2012), 97.9%, 1.09 (IRI-2016) 97.0%, 0.89 98.0%, 1.61 GS. effect R constant points out to dynamic pressure (nPa), magnetic field Bz component (nT), flow speed (km/s), proton density (1/cm3). Besides, absolute total error variance predicted GSs 0.06 (0.30%) 0.013 0.09 (0.49%) 0.016 storm 0.13 (0.73%) 0.033 0.11 (1.06%) 0.035 2004. It means that models considerable consistency over SWp.