In this work, we investigate various types of ionospheric disturbances observed over Europe after the earthquake 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 the co-seismic disturbances produced in the ionosphere close to the epicenter, as well the ionospheric signatures of acoustic waves propagating as a consequence of propagating seismic waves.

In the present study, using sixty-three and fifty-six years of continuous observations, we investigate the long-term oscillations and residual trends, respectively, in the E- and F-region ionosonde measured parameters over Juliusruh, Europe. Using the Lomb-Scargle periodogram (LSP) long-term variations are estimated before the trend estimation. We found that the amplitude of the annual oscillation is higher than the 11-year solar cycle variation in the critical frequencies of the daytime E (foE) and Es (foEs) layers. A weak semi-annual oscillation is also identified in the foE. In the F-region, except for daytime hmF2, and nighttime foF2, the amplitude of the 11-year solar cycle variation is higher than the annual oscillation. The LSP estimated periods and their corresponding amplitudes are used to construct a model E- and F-region ionospheric parameters that are in good agreement with the observation. The linear trend estimation is derived by applying a least-squares fit analysis to the residuals, subtracting the model from the observation. Except for the daytime foF2, all the other parameters like nighttime foF2, day and nighttime h’F, and hmF2 show a negative trend. Present results suggest that the greenhouse effect is a prime driver for the observed long-term trend in the F-region. Interestingly, weak negative trends in the foE and foEs are found which contradicts an earlier investigation. The present study suggests that the changes in the upper stratospheric ozone and mesosphere wind shear variability could be the main driver for the observed weak negative trends in the foE, and foEs, respectively.

The 15 January 2022 eruption of the Hunga volcano provides a unique opportunity to study the reaction of the ionosphere to large explosive events. In particular, this event allows us to study the global propagation of travelling ionospheric disturbances using various instruments. We focus on the detection of the ionospheric disturbances caused by this eruption over Europe, where dense networks of both ionosondes and GNSS receivers are available. This event took place on the day of a geomagnetic storm. We show how data from different instruments and from different observatories can be combined to clearly distinguish the TIDs produced by the eruption from those caused by concurrent geomagnetic activity. By comparing observations obtained from multiple types of instruments, we also show that TIDs produced by various mechanisms are present simultaneously, with different types of waves affecting different physical quantities.

The article proposes a straightforward Kalman filter-based method for computationally efficient ionospheric electron density multi-instrument imaging. The approach uses direct ionospheric measurements, such as ionosondes, and general physical assumptions to estimate the uncertainty associated with the previous reconstructed time step. Therefore the method does not require any electron density model of the ionosphere as a background. The uncertainty is represented by an inverse covariance matrix constructed with Gaussian Markov random fields, allowing the problem to be solved numerically with relatively high resolution. The experiments utilise measurements from dense ground-based GNSS and low Earth orbit beacon satellite receiver networks as well as ionosondes. A synthetic simulation study and real data validation with a specific EISCAT incoherent scatter radar measurement campaign is carried out over Northern European sector. The method can be controlled using parameters with probabilistic and physically realistic interpretations that can be applied to both simulated and real-world data. The results show that the approach is feasible for near real-time regional ionospheric imaging. Especially, the method can be seen as an expansion to local profile measurements field of view, but with sufficient measurement coverage, it also provides information further away from the specific instrument.