On 6 September 2017, the Sun emitted two significant solar flares (SFs). The first SF, classified X2.2, peaked at 09:10 UT. The second one, X9.3, which is the most intensive SF in the current solar cycle, peaked at 12:02 UT and was accompanied by solar radio emission. In this work, we study ionospheric response to the two X‐class SFs and their impact on the Global Navigation Satellite Systems and high‐frequency (HF) propagation. In the ionospheric absolute vertical total electron content (TEC), the X2.2 SF caused an overall increase of 2–4 TECU on the dayside. The X9.3 SF produced a sudden increase of ~8–10 TECU at midlatitudes and of ~15–16 TECU enhancement at low latitudes. These vertical TEC enhancements lasted longer than the duration of the EUV emission. In TEC variations within 2–20 min range, the two SFs provoked sudden increases of ~0.2 TECU and 1.3 TECU. Variations in TEC from geostationary and GPS/GLONASS satellites show similar results with TEC derivative of ~1.3–1.7 TECU/min for X9.3 and 0.18–0.24 TECU/min for X2.2 in the subsolar region. Further, analysis of the impact of the two SFs on the Global Navigation Satellite Systems‐based navigation showed that the SF did not cause losses‐of‐lock in the GPS, GLONASS, or Galileo systems, while the positioning error increased by ~3 times in GPS precise point positioning solution. The two X‐class SFs had an impact on HF radio wave propagation causing blackouts at <30 MHz in the subsolar region and <15 MHz in the postmidday sector.

Systematic error arises when the total electron content (TEC) is estimated with the simultaneous use of phase and code GPS/GLONASS measurements. This is related to the different signal propagation times at 1 and 2 frequencies in the radio frequency path of the transmitting and receiving equipment, the so-called differential code biases. A differential code bias of 1 ns results in an error of ~2.9 TECU when TEC is determined. Differential code bias variations on a long time interval, which were obtained at the CODE laboratory, were analyzed. It has been found that the systematic variation in these biases and considerable seasonal variations apparently caused by the environmental state (temperature and humidity), which sometimes reach 20 TECU (in TEC units), are observed for several stations. The algorithm for determining differential code biases at an individual station and the results of correction for absolute slant TEC are also presented. Presented results show algorithm effectiveness for various geographical regions and solar activity.

While estimating ionospheric total electron content (TEC) using both pseudorange and phase GPS/GLONASS data, there occurs a systematic error caused by the difference in processing times of L1 and L2 signals through radio frequency paths of satellites and receivers, known as differential code biases (DCBs). A 1-ns DCB causes an ∼2.9TECU error in TEC estimation. Along with systematic DCB variations, seasonal variations, most likely related to variations in the receiver environment (temperature, humidity), also exist for some receivers and can reach in some cases up to ∼20TECU

We present the results of the radiotomographic imaging of the artificial ionospheric disturbances obtained in the recent experiments on the modification of the midlatitude ionosphere by powerful HF radiowaves carried out at the Sura heater. Radio transmissions from low orbital PARUS beacon satellites recorded at the specially installed network of three receiving sites were used for the remote sensing of the heated ionosphere. We discuss the possibility to generate acoustic‐gravity waves (AGWs) with special regimes of ionospheric heating (with the square wave modulation of the effective radiated power at the frequency lower than or of the order of the Brunt‐Vaisala frequency of the neutral atmosphere at ionospheric heights during several hours) and present radiotomographic images of the spatial structure of the disturbed volume of the ionosphere corresponding to the directivity pattern of the heater, as well as the spatial structure of the wave‐like disturbances, which are possibly heating‐induced AGWs, diverging from the heated area of the ionosphere. We also studied the HF propagation of the pumping wave through the reconstructed disturbed ionosphere above the Sura heater, showing the presence of heater‐created, field‐aligned irregularities that effectively serve as “artificial radio windows.”

Global navigation satellite systems (GNSS) provide a great data source about the ionosphere state. These data can be used for testing ionosphere models. We studied the performance of nine ionospheric models (Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC) both in the total electron content (TEC) domain—i.e., how precise the models calculate TEC—and in the positioning error domain—i.e., how the models improve single frequency positioning. The whole data set covers 20 years (2000–2020) from 13 GNSS stations, but the main analysis involves data during 2014–2020 when calculations are available from all the models. We used single-frequency positioning without ionospheric correction and with correction via global ionospheric maps (IGSG) data as expected limits for errors. Improvements against noncorrected solution were as follows: GIM IGSG—22.0%, BDGIM—15.3%, NeQuick2—13.8%, GEMTEC, NeQuickG and IRI-2016—13.3%, Klobuchar—13.2%, IRI-2012—11.6%, IRI-Plas—8.0%, GLONASS—7.3%. TEC bias and mean absolute TEC errors for the models are as follows: GEMTEC—−0.3 and 2.4 TECU, BDGIM—−0.7 and 2.9 TECU, NeQuick2—−1.2 and 3.5 TECU, IRI-2012—−1.5 and 3.2 TECU, NeQuickG—−1.5 and 3.5 TECU, IRI-2016—−1.8 and 3.2 TECU, Klobuchar—1.2 and 4.9 TECU, GLONASS—−1.9 and 4.8 TECU, and IRI-Plas—3.1 and 4.2 TECU. While TEC and positioning domains differ, new-generation operational models (BDGIM and NeQuickG) could overperform or at least be at the same level as classical empirical models.