The estimation of the ionospheric electron density by kriging is based on the optimization of a parametric measurement covariance model. First, the extension of kriging with slant total electron content (STEC) measurements based on a spatial covariance to kriging with a spatial-temporal covariance model, assimilating STEC data of a sliding window, is presented. Secondly, a novel tomography approach by gradient enhanced kriging (GEK) is developed. Beyond the ingestion of STEC measurements, GEK assimilates ionosonde characteristics providing peak electron density measurements as well as\udgradient information. Both approaches deploy the 3D electron density model NeQuick as a priori information and estimate the covariance parameter vector within a maximum likelihood estimation for the dedicated tomography time stamp. The methods are validated in the European region for two periods covering quiet and active ionospheric conditions. The kriging with spatial\udand spatial-temporal covariance model is analysed regarding its capability to reproduce STEC, differential STEC and foF2. Therefore the estimates are compared to the NeQuick model results, the 2D TEC maps of the International GNSS Service and the DLR’s Ionospheric Monitoring and Prediction Center, and in case of foF2 to two independent ionosonde stations. Moreover,\udsimulated STEC and ionosonde measurements are used to investigate the electron density profiles estimated by the GEK in comparison to a kriging with STEC only. The results indicate a crucial improvement in the initial guess by the developed methods and point out the potential compensation for a bias in the peak height hmF2 by means of GEK.
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