Regional ionospheric electron density modeling by assimilation of GPS-derived TEC into IRI-provided grids on May 8, 2016

Abstract

Retrieved vertical total electron content (VTEC) via dual-frequency GPS measurements is a valuable observation for regional VTEC modeling of the ionosphere (3D), and also ionospheric electron density (IED) modeling (4D). In the case of 4D modeling, spatial and temporal changes in IED are imaged. 4D reconstruction of IED in different ionosphere layers is not possible only by retrieved VTECs. In all IED modeling methods, in addition to VTEC observations, a priori knowledge of how electron density is distributed in different layers is required, which is often taken from global empirical models. One of these methods is data assimilation, in which the information of a global model is considered as background and both observations and background are used optimally for IED modeling. Data assimilation has more prominent importance in regions where the observations are sparse. In this study, a grid-based data assimilation method is proposed for IED modeling. The optimum interpolation method (OI) is presented with a modification to find the optimal variance factor related to the background covariance matrix. The covariance matrix of the background during the data assimilation interval is estimated by an optimization process. The method is utilized for regional assimilative IED modeling over Iran with sparse VTEC data from a low number of permanent GPS stations on May 8, 2016 which is the most active ionospheric day in that year. International reference ionosphere (IRI) is considered as background, and although it has a significant bias in the study region, the proposed method resulted in an accurate regional IED model. The model is evaluated in two ways. First, by measuring RMS of the differences between parts of VTECs that are excluded from observations as test data and the obtained VTECs from the model. Second, by examining the accuracy of ionospheric delay estimation via single-frequency positioning at a control station in Tehran. Despite the use of sparse data on an active ionospheric day and poor background accuracy in the study region, the constructed regional assimilative model is accurate both in RMS with test data and ionospheric delay estimation.