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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).

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.

A recently proposed self-consistent approach to the analysis of thermospheric and ionospheric long-term trends has been applied to Rome ionosonde summer noontime observations for the (1957–2015) period. This approach includes: (i) a method to extract ionospheric parameter long-term variations; (ii) a method to retrieve from observed foF1 neutral composition (O, O2, N2), exospheric temperature, Tex and the total solar EUV flux with λ

This work presents a contribution to the understanding of the ionospheric triggering of L-band scintillation in the region over São Paulo state in Brazil, under high solar activity. In particular, a climatological analysis of Global Navigation Satellite Systems (GNSS) data acquired in 2012 is presented to highlight the relationship between intensity and variability of the total electron content (TEC) gradients and the occurrence of ionospheric scintillation. The analysis is based on the GNSS data acquired by a dense distribution of receivers and exploits the integration of a dedicated TEC calibration technique into the Ground Based Scintillation Climatology (GBSC), previously developed at the Istituto Nazionale di Geofisica e Vulcanologia. Such integration enables representing the local ionospheric features through climatological maps of calibrated TEC and TEC gradients and of amplitude scintillation occurrence. The disentanglement of the contribution to the TEC variations due to zonal and meridional gradients conveys insight into the relation between the scintillation occurrence and the morphology of the TEC variability. The importance of the information provided by the TEC gradients variability and the role of the meridional TEC gradients in driving scintillation are critically described.

This paper presents research on polar cap ionosphere space weather phenomena conducted during the European Cooperation in Science and Technology (COST) action ES0803 from 2008 to 2012. The main part of the work has been directed toward the study of plasma instabilities and scintillations in association with cusp flow channels and polar cap electron density structures/patches, which is considered as critical knowledge in order to develop forecast models for scintillations in the polar cap. We have approached this problem by multi-instrument techniques that comprise the EISCAT Svalbard Radar, SuperDARN radars, in-situ rocket, and GPS scintillation measurements. The Discussion section aims to unify the bits and pieces of highly specialized information from several papers into a generalized picture. The cusp ionosphere appears as a hot region in GPS scintillation climatology maps. Our results are consistent with the existing view that scintillations in the cusp and the polar cap ionosphere are mainly due to multi-scale structures generated by instability processes associated with the cross-polar transport of polar cap patches. We have demonstrated that the SuperDARN convection model can be used to track these patches backward and forward in time. Hence, once a patch has been detected in the cusp inflow region, SuperDARN can be used to forecast its destination in the future. However, the high-density gradient of polar cap patches is not the only prerequisite for high-latitude scintillations. Unprecedented high-resolution rocket measurements reveal that the cusp ionosphere is associated with filamentary precipitation giving rise to kilometer scale gradients onto which the gradient drift instability can operate very efficiently. Cusp ionosphere scintillations also occur during IMF BZ north conditions, which further substantiates that particle precipitation can play a key role to initialize plasma structuring. Furthermore, the cusp is associated with flow channels and strong flow shears, and we have demonstrated that the Kelvin-Helmholtz instability process may be efficiently driven by reversed flow events.