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The polar ionosphere is often highly structured with significant plasma irregularities, influencing the Global Navigation Satellite System (GNSS) service that relies on trans-ionospheric radio waves. Due to the practical usage, there is a high demand for modeling and forecasting of ionospheric irregularities. In this study, we develop a climatological model based on the long-term dataset (2010-2021) of rate of change of the total electron content (TEC) index (ROTI) maps from the International GNSS Service (IGS). The IGS ROTI maps are daily averaged in magnetic coordinates. In order to develop a climatological model, the ROTI maps are decomposed into a few base functions and coefficients using the empirical orthogonal function (EOF) method. The EOF method converges very quickly, and the first four EOFs could reflect the majority (96%) of the total data variability. Furthermore, the first four EOF base functions reflect different drivers of ionospheric irregularities. For example, the first EOF reflects the averaged ROTI activity and the impact of the solar radiation characterized by F10.7; the 2nd EOF base function reflects the impact of interplanetary magnetic field (IMF) Bz and electric field; the 3rd and 4th EOF base functions reflect the dawn-dusk asymmetry in the auroral oval and polar cap, and therefore related to the IMF By. To build an empirical model, we fit the EOF coefficients using geophysical proxies from four different categories (namely, solar radiation, magnetic indices, IMF, and solar wind coupling function) based on linear regression. The preliminary data-model comparison shows satisfactory results with a good correlation coefficient and adequate errors.

Non-linear couplings of the Earth’s ionosphere with the geospace environment occur in a largely varying range of spatial and temporal scales. As some radio remote sensing techniques like GNSS measurements suffer from artificial radio frequency interference (RFI) at the smallest scales representing ionospheric scintillation, is it advantageous to have ionospheric scales observations based on in-situ measurements.We investigated the variability of the in-situ plasma density and magnetic field measured by Swarm satellites creating the climatology of their scales by leveraging the Fast Iterative Filtering (FIF) technique.FIF is able to provide a very fine time-frequency representation decomposing any non-stationary, nonlinear signals, into oscillating modes, called intrinsic mode components or functions (IMCs or IMFs), characterized by their specific frequency.The results are obtained by time-integrating the instantaneous time-frequency representations, provided through the so-called “IMFogram”. These IMFograms have the potential to show the greater details of the scale sizes and their variations, illustrating the time development of the multi-scale processes during various disturbances of geospace.

The 16 Hz plasma density measurements provided by the high-resolution faceplate onboard Swarm satellites can be utilized to reconstruct the one-dimensional spectral slope (p) of the power spectrum of the plasma density irregularity. The 16 Hz sampling rate at Swarm orbital features (speed of ~7.5 km/s on quasi-polar orbits) allows modelling spatial scales of about 500 m along the flight trajectory, which are slightly above the first Fresnel zone, the upper limit of the scale sizes of the irregularities causing scintillation on Global Navigation Satellite Systems (GNSS) signals. The p-value is a key parameter in estimating the scintillation strength and thus a Swarm ionospheric scintillation (SWIS) proxy is investigated. Such approach, once consolidated, will benefit the scientific community in studying, monitoring and modelling the small-scale irregularities; specially in contexts where ground based GNSS scintillation monitoring is not available, for example over the oceans.In this work, p-value from Swarm, combined with the reconstruction of the irregularity layer , are ingested to compute the amplitude scintillation index (S4) using Rino’s theory of weak scattering. In this work, the model formulation and sample results of S4 estimation from Swarm are demonstrated. Results of validating SWIS S4 against S4 from ground based GNSS scintillation for selected key ionospheric sectors are also shown. The results demonstrate that the model can capture the amplitude scintillation index inflation both at low and high latitudes, demonstrating the capability of detecting the equatorial and the (rare) polar amplitude scintillation from Swarm measurements.

Our modern society heavily relies on the Global Navigation Satellite System (GNSS) applications that utilize trans-ionospheric radio waves. However, these applications can be highly affected by ionospheric scintillations. The GNSS service can be particularly disturbed during severe geomagnetic storms. In this study, we investigate ionospheric scintillations during major geomagnetic storms (minimum Dst < -100 nT). We make use of a network of 11 GNSS scintillation receivers of type Septentrio PolaRxS, which is operated by the Norwegian Mapping Authority. The network covers a wide latitudinal range, from the polar cap to auroral and subauroral regions. Thus, it can capture the scintillation effect associated with variable phenomena at high latitudes, such as polar cap patches, plasma blobs, auroral precipitation, and ionospheric trough. Most previous studies have focused on geomagnetic conditions that are less active and mostly only report significant phase scintillations of GNSS signals at high latitudes. However, extreme events such as the St. Patrick’s Day storm on 17 March 2015 provide good candidates for severe GNSS disruptions. In the present study, we report significant GNSS amplitude and phase scintillations, as well as losses of signal lock. We also quantify the signal power drop and loss of signal lock during major storms. In addition, we relate severe GNSS disruptions to specific ionospheric plasma conditions and ionospheric phenomena (e.g., auroral blobs). The present study is important for understanding extreme space weather conditions and it can provide important information for the development of future GNSS receivers., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The objective of the work is to compare geomagnetic storm impact on the ionosphere parameters measured from ground-based GNSS permanent stations and Swarm satellites. The analyses compare the changes of vertical total electron content (VTEC) measured along the entire ionosphere cross-section to the variations of electron density (ED) on the orbit, at ~500 km altitude. The objective is how sensitive are the measures of electric field variations available on the Earth, with respect to those obtained from the satellite orbit. The study applies Swarm in-situ ED measured by Langmuir Probes (LP), topside TEC from onboard Swarm GNSS receivers and vertical TEC determined from ground-based GNSS stations available in the area of the Northern polar cap. Ground and satellite data were processed in different ways. Ground-based VTEC is available at number of stations providing heterogeneous but useful horizontal coverage. Therefore ROTI values were calculated from VTEC as gradient values capable to indicate the disturbances. These ROTI values were interpolated spatially to obtain maps. Swarm passes over the polar cap starting from 45° lasts for several minutes each, and repeat in this region approximately every 1.5 h. Such along-track collected small data samples are useless in horizontal correlation analysis. Therefore Swarm data disturbances, in this case, are extracted with the use of Fourier transform-based filtering and are also analyzed in the spectrograms based on short-term Fourier transform (STFT). The case study has used three geomagnetic storms, namely: the St. Patrick storm of March 17, 2015, the storm on June 22, 2015, and the storm on August 25-26, 2018. The results reveal differences in storm impact on VTEC measured by GNSS on the Earth, with respect to the storm influence on topside TEC and in-situ ED disturbances measured onboard the Swarm. The overall summary statistics provide some preliminary conclusions on different times of the reaction to the storm. Additionally, some interesting differences between FT filtering and a very popular moving average are shown, with respect to Swarm data. The research was done in the frame of the FORSWAR project (Forecasting Space Weather in the Arctic Region) funded by ESA.

The polar ionosphere is often highly irregular and turbulent with significant plasma structures. As a result, the satellite-based navigation and communication systems that rely on trans-ionospheric radio signals can be severely disrupted. In this study, we take advantage of the high-resolution (1 kHz) electron density observations of a polar orbiting satellite (NorSat-1) to address plasma structures at several 10s of meters that are responsible for scattering of High Frequency (HF) radar signals. The in-situ electron density data are taken from the winter season of 2017-2018. Though the solar activity is very low, NorSat-1 frequently observes significant plasma irregularities from several 10s km down to several decameter. These are often observed near the dayside cusp and dawnside auroral zone. The decameter-scale irregularities are positively correlated with intermediate-scale (10 km) density gradients, for both negative and positive gradients encountered by the satellite. The spatial distribution of electron density over two winter months in the Northern hemisphere along NorSat-1 orbits is constructed, which shows significant density increases in the cusp ionosphere (75º-80º MLAT) and in regions near the dawnside auroral oval. Intermediate scale density gradients and small-scale irregularities are clearly collocated with these density enhancements. These density enhancements and irregularities are likely induced by auroral particle precipitation/plasma dynamics. The power of decameter scale irregularities is also directly compared with the backscatter echo of HF radars.

The ionosphere is a dynamical system exhibiting nonlinear couplings with the other “spheres” characterizing the geospace environment. Such nonlinearity manifests also through the non-trivial, largely varying range of spatial and temporal scales. We investigate how the different scales of the in situ plasma density as provided by different data products measured by Swarm satellites relate to the same range of scales of the field-aligned currents from Swarm FAC dataset and how their intensifications reflect the various conditions of the geospace.The present study compares the spatio-temporal variability in the topside ionosphere by leveraging on the Fast Iterative Filtering (FIF) technique. FIF is able to reveal the hidden features of a time series, as it decomposes any nonstationary, nonlinear signals, like those provided by Langmuir probes onboard Swarm, into oscillating modes, called intrinsic mode components or functions (IMCs or IMFs), characterized by their specific frequencies. The instantaneous time-frequency representation of the IMFs is provided through the so-called “IMFogram” which illustrates the time development of the multi-scale processes. The IMFogram has the potentiality to show the finer details of the scale sizes which intensify during the various phases of geomagnetic storms.This work is performed in the framework of the Swarm Variability of Ionospheric Plasma (Swarm-VIP) project, funded by ESA in the “Swarm+4D-Ionosphere” framework (ESA Contract No. 4000130562/20/I-DT).

With the data from the Swarm satellite mission, we study the variability of ionospheric plasma parameters for low and high solar activities. We focus on the electron density measured by Swarm and derived parameters and analyze the variability of these parameters in the contexts of the Northern and Southern hemispheres, specific latitudinal regions, and the solar activity level. We consider two time intervals: with high solar activity (HSA) from August 2014 to July 2015 and with low solar activity (LSA) from January to December 2018. We show that the electron density is described mainly by three probability density functions (PDF): exponentiated Weibull, lognormal, and chi distributions. These results with PDFs can be applied to the modeling or prediction of ionospheric parameters in different regions. The best fit of PDFs was obtained for low and mid-latitudes, while at high latitudes and in the polar caps, the double-peaked features of the distribution require the fit of multiple PDFs. The electron density (Ne) distribution at low latitudes follows more a lognormal distribution, while in the high latitude region, the chi distribution prevails. Different results were obtained for the rate of change of density index (RODI) with two fitting PDFs: lognormal or exponentiated Weibull, where the best fits are for high latitudes and polar caps. We demonstrate high variability in the electron density and derived parameters at low latitudes and in the polar caps. Comparing both hemispheres, we obtained higher values of these parameters during the solar minimum in the Southern hemisphere at high latitudes and polar caps, while for the Northern hemisphere, higher values were obtained at low latitudes. The dependence on the satellite’s altitude was also considered. The main patterns in the diurnal variation of parameters in different regions do not depend on the level of solar activity (which affects only the maximum values). The largest asymmetry between both hemispheres in Ne diurnal distribution was obtained for the polar cap regions. Here a 50% decrease in Ne was observed in the Northern hemisphere during HSA in the early morning sector (04–07 Magnetic Local Time), which has not yet been observed in the Southern hemisphere. For the first time, such a global statistical characterization of the ionospheric plasma density based on the in situ data is presented.

We present an investigation of polar cap plasma structure lifetimes. We analyze both simulated data from ionospheric models (International Reference Ionosphere model and Mass Spectrometer Incoherent Scatter model) and in situ data from the Swarm satellite mission (the 16 Hz Advanced Plasma Density dataset). We find that the theoretical prediction that E-region conductance is a predictor of F-region polar cap plasma structure lifetimes is indeed supported by both in situ-based observations and by ionospheric models. In situ plasma structure lifetimes correlate well with the ratio of F- to E-region conductance. We present explicit predictions of small scale (∼1 km) structure lifetimes, which range from less than 1 h during local summer to around 3 h during local winter. We highlight a large discrepancy between the observational and theoretical scale-dependency of decay due to diffusion.

The electrostatic potential and plasma density variations around a point‐like charged object in a plasma flow are studied. These objects can represent small charged dust particles, for instance. The radiation patterns can be interpreted as the result of sound waves being radiated by the obstacle. For large electron to ion temperature ratios we find that radiation patterns develop for the sub‐as well as the supersonic case. The results are illustrated by numerical simulations using a hybrid Particle In Cell (PIC) code, where the electrons are treated as an isothermal massless fluid, giving a nonlinear Poisson equation. The analytical results are in good agreement with the numerical simulations.