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Due to advances in remote sensing of the Earth’s Ionosphere through Total Electron Content (TEC) estimates by Global Navigation Satellite System (GNSS) receivers, it is possible to detect and characterize Travelling Ionospheric Disturbances (TIDs) in both post-processing and, to some extent, in near real-time (NRT). A reliable and precise TEC filtering technique must be adopted to characterize waves accurately. Specifically, TEC detrending is widely adopted to extract the amplitude and period of the detected ionospheric waves from the background ionospheric conditions. Therefore, this study aims to understand and compare how different TEC detrending techniques and their settings impact the ability to extract such parameters. We highlight that the novel Fast Iterative Filtering (FIF) and the Savitzky-Golay filter (SGOLAY) techniques are the most reliable overall compared with moving average (MA), multi-order numerical difference (DD), polynomial detrending (POLY) and Finite Impulse response (FIR) band-pass filter (BUTF). Moreover, the impact of general algorithm settings on the exracted TID period is investigated, such as the Ionospheric Piercing Point (IPP) height and elevation cut-off angle, showing that such parameters drastically impact the retrieved period, especially for slower TIDs. Finally, due to the growing interest in real-time (RT) detection and classification of TIDs, the study proposes techniques for accurately estimating the TID amplitude in an NRT scenario. Such NRT techniques are then compared with the widely used post-processing products, such as the calibrated vertical TEC (vTEC), showing a difference that is mostly lower than the typical noise level of GNSS receivers (0.05 TECu).

This work presents statistical models of the variability of plasma in the topside ionosphere based on observations made by the European Space Agency’s (ESA) Swarm satellites. The models were developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The configuration of the Swarm satellites, their near-polar orbits and the data products developed, enable studies of the spatial variability of the ionosphere at multiple scale sizes. The statistical modelling technique of Generalised Linear Modelling (GLM) was used to create models of both the electron density and measures of the variability of the plasma structures at horizontal spatial scales between 20 km and 100 km. Despite being developed using the Swarm data, the models provide predictions that are independent of these data. Separate models were created for low, middle, auroral and polar latitudes. The models make predictions based on heliogeophysical variables, which act as proxies for the solar and geomagnetic processes. The first and most significant term in the majority of the models was a proxy for solar activity. The most common second term varied with the latitudinal region. This was the Solar Zenith Angle (SZA) in the polar region, a measure of latitude in the auroral region, solar time in the mid-latitude region and a measure of latitude in the equatorial region. Other, less significant terms in the models covered a range of proxies for the solar wind, geomagnetic activity and location. In this paper, the formulation, optimisation and evaluation of these models are discussed. The models show very little bias, with a mean error of zero to two decimal places in 14 out of 20 cases. The models capture some, but not all, of the trends present in the data, with Pearson correlation coefficients of up to 0.75 between the observations and the model predictions. The models also capture some, but not all, of the variability of the ionospheric plasma, as indicated by the precision, which ranged between 0.20 and 0.83. The addition of the thermospheric density as an explanatory variable in the models improved the precision in the polar and auroral regions. It is suggested that, if the thermosphere could be observed at a higher spatial resolution, then even more of the variability of the plasma structures could be captured by statistical models. The formulation and optimisation of the models are presented in this paper. The capability of the model in reproducing the expected climatological features of the topside ionosphere, in supporting GNSS-based ionospheric observations and the performance of the model against the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM), are provided in a companion paper (Spogli L et al. 2024. J Space Weather Space Clim https://doi.org/10.1051/swsc/2024003).

Statistical models of the variability of plasma in the topside ionosphere based on the Swarm data have been developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The models can predict the electron density, its gradients for three horizontal spatial scales – 20, 50 and 100 km – along the North-South direction and the level of the density fluctuations. Despite being developed by leveraging on Swarm data, the models provide predictions that are independent of these data, having a global coverage, fed by various parameters and proxies of the helio-geophysical conditions. Those features make the Swarm-VIP models useful for various purposes, which include the possible support for already available ionospheric models and proxy of the effect of ionospheric irregularities of the medium scales that affect the signals emitted by Global Navigation Satellite Systems (GNSS). The formulation, optimisation and validation of the Swarm-VIP models are reported in Paper 1 (Wood et al. 2024. J Space Weather Space Clim. in press). This paper describes the performance assessment of the models, by addressing their capability to reproduce the known climatological variability of the modelled quantities, and the ionospheric weather as depicted by ground-based GNSS, as a proxy for the ionospheric effect on GNSS signals. Additionally, we demonstrate that, under certain conditions, the model can better reproduce the ionospheric variability than a physics-based model, namely the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM).

An accurate modeling of the ionosphere electron density is pivotal to guarantee the effective operation of communication and navigation systems, particularly during Space Weather events. Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI), their limitations in predicting ionospheric variability, especially under geomagnetically disturbed conditions, are acknowledged. The solution proposed in this work involves integrating real‐time, spatially distributed ionospheric measurements into climatological models through data assimilation. To enhance our predictive capabilities, we present an upgrade of the IRI UP data‐assimilation method, incorporating real‐time vertical total electron content (vTEC) maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. This approach involves updating the IRI F2‐layer peak electron density description through ionospheric indices, to finally produce real‐time maps over Italy of the ordinary critical frequency of the F2‐layer, foF2, which is crucial for radio‐propagation applications. The IRI UP–IONORING method performance has been evaluated against different climatological and nowcasting models, and under different Space Weather conditions, by showing promising outcomes which encourages its inclusion in the portfolio of ionospheric real‐time products available over Italy. The validation analysis highlighted also what are the current limitations of the IRI UP–IONORING method, particularly during nighttime for severely disturbed conditions, suggesting avenues for future enhancements. Plain Language Summary: Ensuring the smooth operation of communication and navigation systems based on both High‐Frequency and GNSS radio signals relies on accurately modeling the density of electrons in the ionosphere. Existing empirical models, like the International Reference Ionosphere (IRI), have limitations in predicting small‐scale spatial and temporal changes in the ionosphere, especially during severe Space Weather events. This work proposes a solution by incorporating real‐time ionospheric measurements into a background model through a process called data assimilation. Specifically, the IRI UP method has been upgraded by assimilating real‐time vertical total electron content maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. The performance of this upgraded method has been tested against different models and for different Space Weather conditions, showing promising results. These findings open avenues for future improvements contributing to enhancing our ability to predict and adapt to dynamic changes in the Earth's ionosphere, of which various communication and navigation technologies would benefit. Key Points: IRI UP method upgrade through the assimilation of real‐time vTEC maps from IONORING for nowcasting ionospheric conditions over ItalyIRI UP outputs real‐time foF2 maps over Italy through the ingestion of ionospheric effective indices maps in the background IRI modelIt has been successfully tested against several climatological and nowcasting models, and under different Space Weather conditions [ABSTRACT FROM AUTHOR]

In this study, we focus on the presence of the ionospheric third plasma density peak associated with the equatorial ionization anomaly (EIA) based on observations from the ESA's Swarm constellation. By statistically analyzing the third peaks observed by the Swarm A and B at two different altitudes, we found that such structure appears mainly around ±20° magnetic latitude (Mlat), namely the poleward of the EIA crests. In the meanwhile, the third peak shows prominent season and local time dependences, that are mainly observed in the summer hemisphere during solstice seasons and with the highest occurrence in the afternoon hours. However, no clear solar flux and magnetic activity dependences are found. By further analyzing the simultaneous neutral wind measurements from the ionospheric connection explorer satellites, we found that the summer-to-winter hemispheric meridional wind is responsible for causing the third peak as well as its seasonal dependence (higher occurrence in the summer hemisphere). In addition, the third-peak structure shows prominent longitudinal dependence. In regions where the magnetic declination directs eastward, it has a larger occurrence in the southern hemisphere, while in regions where the magnetic declination reverses, it has a larger occurrence in the northern hemisphere. Such a longitudinal dependence suggests that the zonal wind, which has a magnetic field-aligned component at favorable magnetic declination regions, contributes also to the formation of the third-peak structure. [ABSTRACT FROM AUTHOR]

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 (TIDs) using various instruments. We focus on detecting 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 observatories can be combined to distinguish the TIDs produced by the eruption from those caused by concurrent geomagnetic activity. The Lamb wavefront was detected as the strongest disturbance in the ionosphere, travelling between 300 and 340 m/s, consistent with the disturbances in the lower atmosphere. 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. This illustrates the importance of analysing data from multiple independent instruments in order to obtain a full picture of an event like this one, as relying on only a single data source might result in some effects going unobserved.

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. Key Points: The 2023 Turkey earthquake induced a spectrum of ionospheric disturbances as shown by networks of GNSS receivers, ionosondes and HF DopplerDisturbances appeared as shock acoustic wave‐induced traveling ionospheric disturbances in the near field and Rayleigh wave‐induced ionogram multiple‐cusp signature at longer distancesMulti‐instrument remote sensing techniques can detect ionospheric disturbances at a range of altitudes‐distances from the epicenter [ABSTRACT FROM AUTHOR]

We analyze the amplitude scintillation on L-band signals over San Miguel de Tucumán (Argentina), focusing on the multi-scale variability and speculating on the possible relationship between forcing factors from the geospace and the ionospheric response. The site is nominally located below the expected position of the southern crest of the Equatorial Ionospheric Anomaly (EIA). For this scope, we concentrate on the period 1–31 March 2011, during which one minor and one moderate storm characterize the first half of the month, while generally quiet conditions of the geospace stand for the second half. By leveraging on the Adaptive Local Iterative Filtering (ALIF) signal decomposition technique, we investigate the multi-scale properties of Global Navigation Satellite Systems (GNSS) amplitude scintillation and helio-geophysical parameters, looking for possible cause-effect mechanisms relating the former to the latter. Namely, we identify resonant modes in the Akasofu (ε) parameter as likely related to the frequency components in the time evolution found for the amplitude scintillation index, hence modulating the scintillation itself.

The effect of the Earth’s ionosphere represents the single largest contribution to the Global Navigation Satellite System (GNSS) error budget and abnormal ionospheric conditions can impose serious degradation on GNSS system functionality, including integrity, accuracy and availability. With the growing reliance on GNSS for many modern life applications, actionable ionospheric forecasts can contribute to the understanding and mitigation of the impact of the ionosphere on our technology based society. In this context, the Ionosphere Prediction Service (IPS) project was set up to design and develop a prototype platform to translate the forecast of the ionospheric effects into a service customized for specific GNSS user communities. To achieve this overarching aim, four different product groups dealing with solar activity, ionospheric activity, GNSS receiver performance and service performance have been developed and integrated into a service chain, which is made available through a web based platform. This paper provides an overview of the IPS project describing its overall architecture, products and web based platform.

This paper was written by a group of European researchers believing that now is the right time to frame the Space Weather and Space Climate discipline in Europe for future years. It is devoted to openly discussing the organisation and sustainability of the European Space Weather community and its assets in the (near) future. More specifically, we suggest that the European Space Weather community lacks a uniting organisation to help the community to sustain and develop the successful efforts made thus far. Our aim is not to draw a complete and exhaustive panorama of Space Weather throughout the world, nor even throughout Europe. It is not a new white paper on the science and applications: there exist many (e.g. Tsurutani et al., 2020 Nonlinear Processes Geophys 27(1): 75–119); nor another roadmap: several important have been published recently (e.g. Schrijver et al., 2015. Adv Space Res 55(12): 2745–2807; Opgenoorth et al., 2019. J Space Weather Space Clim 9: A37). Our aim is to question our practices and organisation in front of several changes that have occurred in the recent years and to set the ground to provide coordinated answers to these questions being posed in Europe, and to make these answers discussed throughout the world. This group was assembled first through a series of sessions devoted to the sustainability of Space Weather research during the European Space Weather Week (ESWW) series of meetings, specifically: ESWW 14 (2017), ESWW 15 (2018), and ESWW 16 (2019). It then grew from discussions and personal contacts. The authors do not pretend to identify the full range of opinions in Europe, although they do come from 13 different European countries with a large span of ages (around half are below the age of 40 years old at the time of writing) with a good gender balance ending with a diverse mix of young and motivated scientists and senior people who have played a role in shaping the Space Weather community in Europe. The questions and the propositions to organise Space Weather in Europe in the future result from their discussions through these meetings and through remote meetings during the pandemic. We wish to share them with all those who consider themselves as members of the European Space Weather community and/or are interested in its future and to propose actions. We do this, bearing in mind that Europe plays a key international role in Space Weather which extends beyond the ESA and EU/EC geographic area.

We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

Ionospheric scintillation can seriously impair the Global Navigation Satellite Systems (GNSS) receiver signal tracking performance, thus affecting the required levels of availability, accuracy and integrity of positioning that supports modern day GNSS based applications. We present results from the research work carried out under the Horizon 2020 European Commission (EC) funded Ionospheric Prediction Service (IPS) project. The statistical models developed to estimate the standard deviation of the receiver Phase Locked Loop (PLL) tracking jitter on the Global Positioning System (GPS) L1 frequency as a function of scintillation levels are presented. The models were developed following the statistical approach of generalized linear modelling on data recorded by networks in operation at high and low latitudes during the years of 2012–2015. The developed models were validated using data from different stations over varying latitudes, which yielded promising results. In the case of mid-latitudes, as the occurrence of strong scintillation is absent, an attempt to develop a dedicated model proved fruitless and, therefore, the models developed for the high and low latitudes were tested for two mid-latitude stations. The developed statistical models can be used to generate receiver tracking jitter maps over a region, providing users with the expected tracking conditions. The approach followed for the development of these models for the GPS L1 frequency can be used as a blueprint for the development of similar models for other GNSS frequencies, which will be the subject of follow on research.

The Hunga Tonga-Hunga Ha'apai volcano (Pacific Ocean) generated a cataclysmic explosion on 15 January 2022, triggering several atmospheric disturbances at a global scale, as a huge increase in the total electron content (TEC) in the ionosphere, and a pressure wave travelling in the troposphere. We collected and analysed data over the Mediterranean to study these disturbances, and in particular, (i) data from the barometric and infrasonic stations installed on Italian active volcanoes by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for investigating the tropospheric pressure waves; (ii) barometric data from the INGV-TROPOMAG and SIAS (Sicilian Agro-meteorological Information System) networks, for investigating the interaction between the orography and pressure waves; (iii) ionograms from the Advanced Ionospheric Sounder-INGV ionosonde at Gibilmanna (Sicily, Italy); (iv) data from the RING (Rete Italiana Integrata GNSS) network, to retrieve the ionospheric TEC; (v) soil CO2 flux data from the INGV surveillance network of Vulcano Island. The analysis of the ground-level barometric data highlights that pressure waves were reflected and diffracted by the topographic surface, creating a complex space–time dynamic of the atmospheric disturbances travelling over Sicily, driven by the interference among the different wavefronts. The ionograms show that a medium-scale travelling ionospheric disturbance (MSTID), with a horizontal wavelength of about 220 km and a period of about 35 min, propagated through the ionospheric plasma in the correspondence of the first barometric variations. Moreover, comparing detrended TEC and barometric data, we further confirmed the presence of the aforementioned MSTID together with its close relation to the tropospheric disturbance. [ABSTRACT FROM AUTHOR]