Satellite telecommunications, positioning and navigation systems require knowledge of the electron distribution in height Ne(h) to high-altitude orbits of satellites. One of the possibilities to construct such profiles is associated with the use of the ionospheric total electron content TEC. This paper is devoted to three advantages of the IRI-Plas model. They include introduction of the topside basis scale height Hsc, expansion of the IRI model to the plasmasphere, ingestion of experimental values of TEC. Testing of this model according to different satellite experiments (CHAMP, DMSP) shows the high efficiency of this model. The method of adaptation of the IRI-Plas model to the plasma frequency at altitudes of CHAMP and DMSP satellites allows us to produce behavior of Ne(h)-profiles during the disturbances, as well as to refine the values of TEC, which determine the accuracy of positioning. Results were obtained using data of the European area.

Machine learning can play a significant role in bringing new insights in GNSS remote sensing for ionosphere monitoring and modeling to service. In this paper, a set of multilayer architectures of neural networks is proposed and considered, including both neural networks based on LSTM and GRU, and temporal convolutional networks. The set of methods included 10 architectures: TCN, modified LSTM-/GRU-based deep networks, including bidirectional ones, and BiTCN. The comparison of TEC forecasting accuracy is performed between individual architectures, as well as their bidirectional modifications, by means of MAE, MAPE, and RMSE estimates. The F10.7, 10 Kp, Np, Vsw, and Dst indices are used as predictors. The results are presented for the reference station Juliusruh, three stations along the meridian 30°E (Murmansk, Moscow, and Nicosia), and three years of different levels of solar activity (2015, 2020, and 2022). The MAE and RMSE values depend on the station latitude, following the solar activity. The conventional LSTM and GRU networks with the proposed modifications and the TCN provide results at the same level of accuracy. The use of bidirectional neural networks significantly improves forecast accuracy for all the architectures and all stations. The best results are provided by the BiTCN architecture, with MAE values less than 0.3 TECU, RMSE less than 0.6 TECU, and MAPE less than 5%.

Manifestations of two solar flares of March 2022 were studied over Mexico. The flare effects in the lower ionosphere had a ~3 min delay from the X1.3-flare onset and ~5 min from the M9.6-flare onset. The maximal impact on the HF signal amplitude was ~(14–15) min after the onset of both flares. The X1.3-flare provoked the shortwave fadeout during ~6 min. The effects in the lower ionosphere lasted longer than the flares and the effects at the F2 region and higher altitudes only during the flares. The interpretation of results showed the following. (1) Based on the absorption level estimated with minimum frequency and signal amplitude on ionograms, the major role of X-ray radiation in the electron concentration increase in the lower ionosphere was confirmed. At the same time, the EUV radiation impact on the lower ionosphere cannot be totally discarded. The lower ionosphere recovery began before and lasted after the X1.3-flare end, being more rapid at Eglin than in Mexico. During M9.6-flare, the responses at the two observation points were rather synchronized due to the more similar illumination conditions at the two meridians. (2) According to the dI variations characterizing the F2 region and higher, the M9.6-flare provoked medium-scale and the X1.3-flare provoked both medium- and small-scale ionospheric irregularities. The response duration corresponded to the dI series filtered with (10–20) min windows. The dI curve during the flares was characterized by the И-form and depended more on the active region position and the flare class than on the solar zenith angle. The available data do not allow us to unambiguously identify the reason for the negative dI: the applied filtering procedure or the physical effect. (3) During both flares, the major EUV impact on the lower ionosphere was by the flux at 133.5 nm and on the F2 region and higher altitudes at 25.6 nm. In addition, during the M9.6-flare, EUV 28.4, 30.4 and 121.6 nm spectral bands also played an important role in the F2 response. During the X1.3-flare, the EUV 25.6 nm flux and X-ray flux impacts on the F2 region were of the same level. The weakest impact was caused by the emission in the EUV 28.4 nm spectral band on the absorption in the lower ionosphere during both flares and on the electron density in the F2 region and higher during the X1.3-flare.

Possible ionospheric effects of the Morelian meteoroid that passed and exploded over Mexico on 19 February 2020 (18 February 2020 local time) were estimated. The meteoroid trajectory, velocity and time of occurrence were calculated based on outdoor camera records. Modeling was used to estimate the meteoroid initial diameter, density, mass, velocity, energy and their change during its flight in the atmosphere. The ensemble of ionospheric scintillation indices calculated from the high-rate GNSS data and the filtered slant Total Electron Content data were used to reveal the presence of ionospheric disturbances generated by shock waves excited by the meteoroid flight and explosion. The first ionospheric responses to phenomena accompanying the meteoroid were detected (2.5–3.5) min after the explosion. The disturbances were attenuated quickly with distance from their source and were rarely recorded by GNSS receivers located more than 600 km from the meteoroid explosion site. The ionospheric disturbances of intermediate-scale, small-scale, shock-acoustic-wave-scale and sometimes medium-scale were revealed. The detected disturbances corresponded to the range of acoustic-gravity waves. An asymmetry of the disturbance manifestation in different directions was observed. The obtained results are in accordance with results of the observation of other meteoroids. Although the object was smaller and of less energy than other known meteoroids, it is an interesting case because, to the best of our knowledge, it isthe first known to us low-latitude meteoroid with the detected ionospheric effects.