A Global CIT Model Fusing Ground-Based GNSS and Space-Borne LEO Satellite Data for Monitoring the Geomagnetic Storm

The global computerized ionospheric tomography (CIT) based on the global navigation satellite system (GNSS) is an effective tool for monitoring the ionospheric responses to space weather events. However, the main challenge of global CIT is the ill-posed problem due to the unevenly distributed GNSS stations. In this study, we propose a global CIT model fusing ground-based GNSS and space-borne low Earth orbit (LEO) satellite data. The slant total electron content (STEC) observations from more than 600 GNSS stations and 34 LEO satellites are jointly used as the data source for CIT. The simulation experiment shows that compared with CIT based on only GNSS data (CITG), CIT based on GNSS + LEO data (CITGL) improves the voxel penetration rate by 18.31%. In the real data experiment, the root mean square error (RMSE) of the STEC obtained by CITGL is reduced by 24.59% on average compared to that obtained by CITG. The ionospheric electron density (IED) profiles and the total electron content (TEC) maps derived from CITGL results are of better accuracies than those derived from CITG results. CITGL is further applied for investigating the ionospheric variations around the geomagnetic storm on day of year (DOY) 308, 2021, and the results demonstrate that CITGL effectively reconstructs the 3-D distributions and the evolutions of the global ionospheric disturbances around the storm. In particular, CITGL captures the uplift of the hmF2 during the main phase of the storm.