Time-Dependent Ionospheric Tomography Based on Two-Step Reconstruction and Node Parameterization Algorithm

The precise reconstruction of ionospheric electron density (IED) fields with high spatial and temporal resolutions has always been challenging. Global navigation satellite system (GNSS) tomography is a powerful tool to resolve the spatial structure and temporal behavior of IED. This study proposes a novel two-step algorithm of ionospheric tomography for the reconstruction of IED fields with high time resolution. Linear time-dependent ionospheric tomography model based on the node-based parameterization method is established for the first time. In the two-step reconstruction method, the linear trends of IED over a long time are first inverted. Then, the modeling residuals are adopted to obtain deviation terms. In addition, the design matrix is adaptively adjusted because the vertical variation parameter of IED for each voxel is dynamically updated from the IED profiles after each iteration. The tomography (5 min) is validated with GPS data collected over a one-month period (September 2020) from 629 stations in the USA. According to the GPS, COSMIC-2, and Swarm validations, the proposed tomography approach outperforms voxel-based, traditional node parameterization, and linear time-dependent methods by 10%-40%. The performance of the tomographic modeling is further examined by using a high geomagnetic activity period of April 20-29, 2023 in the high solar activity year. Results show that the tomographic model is robust even during severe geomagnetic storms.