Predicting the Effects of Solar Storms on the Ionosphere Based on a Comparison of Real-Time Solar Wind Data with the Best-Fitting Historical Storm Event

Abstract

This study presents a new modeling approach that aims for long time predictions (more than 12 h) of ionospheric disturbances driven by solar storm events. The proposed model shall run in an operational framework to deliver fast and precise localized warnings for these disturbances in the future. The solar wind data driven approach uses a data base of historical solar storm impacts covering two solar cycles to reconstruct future events and resulting ionospheric disturbances. The basic components of the model are presented and discussed in this study, and the strengths of the reconstruction based on historical events are presented by showing the good correlations for predicted and observed geomagnetic activity. Initial results on the ionospheric response are discussed for all historical events using global total electron content (GTEC) and in more detail using total electron content (TEC) maps for two specific case studies (including the St. Patrick’s Day geomagnetic storm during the 17 March 2015). Average root mean square error (RMSE) values of 3.90 and 5.21 TECU are calculated for these cases confirming good results for the current configuration of the model. Possible future improvements of the individual model parts, as well as the planned extensions and applications are discussed in detail.