Traveling ionospheric disturbances (TIDs) are the ionospheric signatures of atmospheric gravity waves. Their identification and tracking is important because the TIDs affect all services that rely on predictable ionospheric radio wave propagation. Although various techniques have been proposed to measure TID characteristics, their real‐time implementation still has several difficulties. In this contribution, we present a new technique, based on the analysis of oblique Digisonde‐to‐Digisonde “skymap” observations, to directly identify TIDs and specify the TID wave parameters based on the measurement of angle of arrival, Doppler frequency, and time of flight of ionospherically reflected high‐frequency radio pulses. The technique has been implemented for the first time for the Network for TID Exploration project with data streaming from the network of European Digisonde DPS4D observatories. The performance is demonstrated during a period of moderate auroral activity, assessing its consistency with independent measurements such as data from auroral magnetometers and electron density perturbations from Digisondes and Global Navigation Satellite System stations. Given that the different types of measurements used for this assessment were not made at exactly the same time and location, and that there was insufficient coverage in the area between the atmospheric gravity wave sources and the measurement locations, we can only consider our interpretation as plausible and indicative for the reliability of the extracted TID characteristics. In the framework of the new TechTIDE project (European Commission H2020), a retrospective analysis of the Network for TID Exploration results in comparison with those extracted from Global Navigation Satellite System total electron content‐based methodologies is currently being attempted, and the results will be the objective of a follow‐up paper.

Using 63 and 56 yr of continuous observations, we investigate the long‐term oscillations and residual linear trends, respectively, in the E‐ and F‐region ionosonde measured parameters of frequencies and height over Juliusruh, Europe. Using the Lomb‐Scargle periodogram (LSP) long‐term variations are estimated before the trend calculation. We found that the amplitude of the annual oscillation is higher than the 11‐yr solar cycle variation in the critical frequencies of the daytime E (foE) and Es (foEs) layers. In the F‐region, except for daytime hmF2, and nighttime foF2, the amplitude of the 11‐yr solar cycle variation is higher than the annual oscillation. The combination of the LSP estimated periods and their corresponding amplitudes and traditional regression analysis are used to construct a model for E‐ and F‐region ionospheric parameters. The modeled estimates are in good agreement with the observations. The trend calculation is derived by applying a least‐squares fit analysis to the residuals, subtracting the model from the observation. In the F‐region, both day (nighttime) foF2 and hmF2 show negative trends of −4.44 ± 1.78 (−4.30 ± 1.63) kHz/yr and −413 ± 47 (−574 ± 75) m/yr, respectively. The Piecewise linear trend of foF2 provides negative and positive trends in 1964–1996 and 1997–2019, respectively. In the E‐region, foEs show a negative trend of −2.00 ± 0.61 kHz/yr. The present investigation suggests that the greenhouse cooling effect and negative trend in the atomic oxygen (O) as well as wind shear variability could be the main drivers for the observed negative trends in the hmF2, foF2, and foEs, respectively.

Observations made using the LOw-Frequency ARray (LOFAR) between 10:15 and 11:48 UT on the 15th of September 2018 over a bandwidth of approximately 25–65 MHz contain discrete pseudo-periodic features of ionospheric origin. These features occur within a period of approximately 10 min and collectively last roughly an hour. They are strongly frequency dependent, broadening significantly in time towards the lower frequencies, and show an overlaid pattern of diffraction fringes. By modelling the ionosphere as a thin phase screen containing a wave-like disturbance, we are able to replicate the observations, suggesting that they are associated with small-scale travelling ionospheric disturbances (TIDs). This modelling indicates that the features observed here require a compact radio source at a low elevation and that the TID or TIDs in question have a wavelength <~30 km. Several features suggest the presence of deviations from an idealised sinusoidal wave form. These results demonstrate LOFAR’s capability to identify and characterise small-scale ionospheric structures.

In this work, we investigate various types of ionospheric disturbances observed over Europe following the earthquake that occurred in Turkey on 6 February 2023. By combining observations from Doppler sounding systems, ionosondes, and GNSS receivers, we are able to discern different types of disturbances, propagating with different velocities and through different mechanisms. We can detect co‐seismic ionospheric disturbances close to the epicenter, as well as ionospheric signatures of acoustic waves propagating as a consequence of propagating seismic waves. Unlike the vast majority of past ionospheric co‐seismic disturbance studies that are primarily based on Total Electron Content variations, reflecting disturbances propagating around the F‐region peak, the focus of the present study is the manifestation of disturbances at different ionospheric altitudes by exploiting complementary ionospheric remote sensing techniques. This is particularly highlighted through ionospheric earthquake‐related signatures established as specific ionogram deformations known as multiple‐cusp signatures which appear as additional cusps at the base of the F‐region attributed to electron density irregularities generated by Rayleigh surface waves that generate acoustic waves propagating up to the ionosphere. Therefore this study underlines the advantage that multi‐instrument investigations offer in identifying the propagation of earthquake‐related ionospheric disturbances at different ionospheric altitudes and distances from the earthquake epicenter.

Greenhouse gases such as carbon dioxide and methane that are causing climate change may cause long-term trends in the thermosphere and ionosphere. The paper aims to contribute to exploring long-term effects in the ionosphere focusing on the impact of solar activity changes. Peak electron density data derived from vertical sounding measurements covering 65 years at the ionosonde stations Juliusruh (JR055), Boulder (BC840), and Kokubunji (TO536), have been utilized to estimate the long-term behavior of daytime ionospheric F2 layer ionization in relation to the solar 10.7 cm radio flux index F10.7. In parallel, Global Navigation Satellite System (GNSS) based vertical total electron content (TEC) data over the ionosonde stations in combination with the peak electron density data have been used to derive the equivalent slab thickness τ for estimating long-term behavior in the period 1996–2022. A new approach has been developed for deriving production and loss term proxies for studying long-term ionization effects from F2 layer peak electron density and TEC data. The derived coefficients allow for estimating the long-term variation of atomic oxygen and molecular nitrogen concentrations including their ratio during winter months. The noon-time slab thickness values over Juliusruh correlate well with the decrease of F10.7 and the F2 layer peak height and enable estimating the neutral gas temperature. The equivalent slab thickness decreases by about 20 km per decade in the period 1996–2022, indicating a thermospheric cooling of about 100 K per decade for Juliusruh. Whereas the oxygen concentration decreases, the loss term, considered as a proxy for molecular components of the neutral gas, in particular N₂, increases with the long-term solar activity variation. Considering 11-year averages of the production and loss terms under wintertime conditions, the long-term study reveals for the O/N₂ ratio a percentage decrease of 5% per decade and for F10.7 about 3.1% per decade in a linear approach referred to the year 1970. Linear models of 11 years averaged NmF2 and foF2 from corresponding F10.7 show a very close correlation with the temporal variation of F10.7 until about 1990. The root mean square errors are in the order of 1.0–1.3 · 10¹⁰ m⁻³ for NmF2 and 0.03–0.05 MHz for foF2. After 1990 the linear models deviate from F10.7 at all selected mid-latitude ionosonde stations indicating a non-local effect.