Abstract. In relation to satellite applications like global navigation satellite systems (GNSS) and remote sensing, the electron density distribution of the ionosphere has significant influence on trans-ionospheric radio signal propagation. In this paper, we develop a novel ionospheric tomography approach providing the estimation of the electron density's spatial covariance and based on a best linear unbiased estimator of the 3-D electron density. Therefore a non-stationary and anisotropic covariance model is set up and its parameters are determined within a maximum-likelihood approach incorporating GNSS total electron content measurements and the NeQuick model as background. As a first assessment this 3-D simple kriging approach is applied to a part of Europe. We illustrate the estimated covariance model revealing the different correlation lengths in latitude and longitude direction and its non-stationarity. Furthermore, we show promising improvements of the reconstructed electron densities compared to the background model through the validation of the ionosondes Rome, Italy (RO041), and Dourbes, Belgium (DB049), with electron density profiles for 1 day.

The solar eclipse on March 20, 2015 was a fascinating event for people in Northern Europe. From a scientific point of view, the solar eclipse can be considered as an in situ experiment on the Earth's upper atmosphere with a well-defined switching off and on of solar irradiation. Due to the strong changes in solar radiation during the eclipse, dynamic processes were initiated in the atmosphere and ionosphere causing a measurable impact, for example, on temperature and ionization. We analyzed the behavior of total ionospheric ionization over Europe by reconstructing total electron content (TEC) maps and differential TEC maps. Investigating the large depletion zone around the shadow spot, we found a TEC reduction of up to 6 TEC units, i.e., the total plasma depletion reached up to about 50%. However, the March 20, 2015 eclipse occurred during the recovery phase of a strong geomagnetic storm and the ionosphere was still perturbed and depleted. Therefore, the unusual high depletion is due to the negative bias of up to 20% already observed over Northern Europe before the eclipse occurred. After removing the negative storm effect, the eclipse-induced depletion amounts to about 30%, which is in agreement with previous observations. During the solar eclipse, ionospheric plasma redistribution processes significantly affected the shape of the electron density profile, which is seen in the equivalent slab thickness derived by combining vertical incidence sounding (VS) and TEC measurements. We found enhanced slab thickness values revealing, on the one hand, an increased width of the ionosphere around the maximum phase and, on the other, evidence for delayed depletion of the topside ionosphere. Additionally, we investigated very low frequency (VLF) signal strength measurements and found immediate amplitude changes due to ionization loss at the lower ionosphere during the eclipse time. We found that the magnitude of TEC depletion is linearly dependent on the Sun's obscuration function. By modelling TEC depletion and knowing the Sun's obscuration function in advance, Global Navigation Satellite System (GNSS) operators may improve the broadcast ionospheric correction during a solar eclipse day.

Abstract. The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools to provide link specific ionospheric corrections as well as to study and monitor physical processes in the ionosphere.In this paper, we introduce a simultaneous multiplicative column-normalized method (SMART) for electron density reconstruction. Further, SMART+ is developed by combining SMART with a successive correction method. In this way, a balancing between the measurements of intersected and not intersected voxels is realised. The methods are compared with the well-known algebraic reconstruction techniques ART and SART. All the four methods are applied to reconstruct the 3-D electron density distribution by ingestion of ground-based GNSS TEC data into the NeQuick model.The comparative case study is implemented over Europe during two periods of the year 2011 covering quiet to disturbed ionospheric conditions. In particular, the performance of the methods is compared in terms of the convergence behaviour and the capability to reproduce sTEC and electron density profiles. For this purpose, independent sTEC data of four IGS stations and electron density profiles of four ionosonde stations are taken as reference. The results indicate that SMART significantly reduces the number of iterations necessary to achieve a predefined accuracy level. Further, SMART+ decreases the median of the absolute sTEC error up to 15, 22, 46 and 67 % compared to SMART, SART, ART and NeQuick respectively.

From the applications perspective the electron density is the major determining parameter of the ionosphere due to its strong impact on the radio signal propagation. As the most ionized ionospheric region, the F2 layer has the most pronounced effect on transionospheric radio wave propagation. The maximum electron density of the F2 layer, NmF2, and its height, hmF2, are of particular interest for radio communication applications as well as for characterizing the ionosphere. Since these ionospheric key parameters decisively shape the vertical electron density profiles, the precise calculation of them is of crucial importance for an accurate 3‐D electron density reconstruction. The vertical sounding by ionosondes provides the most reliable source of F2 peak measurements. Within this paper, we compare the following data assimilation methods incorporating ionosonde measurements into a background model: Optimal Interpolation (OI), OI with time forecast (OI FC), the Successive Correction Method (SCM), and a modified SCM (MSCM) working with a daytime‐dependent measurement error variance. These approaches are validated with the measurements of nine ionosonde stations for two periods covering quiet and disturbed ionospheric conditions. In particular, for the quiet period, we show that MSCM outperforms the other assimilation methods and allows an accuracy gain up to 75% for NmF2 and 37% for hmF2 compared to the background model. For the disturbed period, OI FC reveals the most promising results with improvements up to 79% for NmF2 and 50% for hmF2 compared to the background and up to 42% for NmF2 and 16% for hmF2 compared to OI.

No abstract