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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.

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.

The aim of this work is to present a global ionospheric prediction model based on deep learning (DL) to forecast Total Electron Content 24 hours in advance under different space weather conditions. Three different DL techniques have been compared to select the most suitable for the purpose of an operational service: Long Short Term Memory (LSTM), Gated Recurrent Units (GRU) and Convolutional Neural Networks (CNN). The modeling approach inherits and extends what has been proposed by Cesaroni and co-authors (2020). We use TEC on 18 selected grid points of Global Ionospheric Maps (GIMs) as the target parameter and Kp index as the external input. We use a dataset from 2005-2016 for training and testing, we also analyze case studies from 2017 under different geomagnetic conditions. Results show that CNN models have better predictive capabilities than the other two DL models, even under geomagnetically disturbed conditions. Considering the first 24 hours of forecasting, CNN exhibits errors between 0.5 and 2 TECu, while LSTM and GRU errors can reach 3 TECu. We also show how all the proposed models outperform the two naive models: the so-called “frozen ionosphere” and a 27 days averaged model. Moreover, we implemented the models using incremental training to update them as new data arrives and thus the trained model is able to adapt to rapid changes within the previous 24 hs to the forecasting. Thus, the proposed model can be implemented in an operative manner for Space Weather applications and services.

Signal monitoring and recording station architectures based on software-defined radio (SDR) have been proposed and implemented since several years. However, the large amount of data to be transferred, stored, and managed when high sampling frequency and high quantization depth are required, poses a limit to the performance, mostly because of the data losses during the data transfer between the front-end and the storage unit. To overcome these limitations, thus allowing a reliable, high-fidelity recording of the signals as required by some applications, a novel architecture named SMART (Signal Monitoring, Analysis and Recording Tool) based on the implementation of Docker containers directly on a Network Attached Storage (NAS) unit is presented. Such paradigms allow for a fully open-source system being more affordable and flexible than previous prototypes. The proposed architecture reduces computational complexity, increases efficiency, and provides a compact, cost-effective system that is easy to move and deploy. As a case study, this architecture is implemented to monitor RFIs on Global Navigation Satellite System (GNSS) L1/E1 and L5/E5 bands. The sample results show the benefits of a stable, long-term capture at a high sampling frequency to characterize the RFIs spectral signature effectively.

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.

Radio Frequency (RF) signals transmitted by Global Navigation Satellite Systems (GNSS) are exploited as signals of opportunity in many scientific activities, ranging from sensing waterways and humidity of the terrain to the monitoring of ionospheric irregularities. The latter can be pursued by processing the GNSS signals through dedicated ground-based monitoring equipment, such as the GNSS Ionospheric Scintillation and TEC Monitoring (GISTM) receivers. Nonetheless, GNSS signals are susceptible to intentional or unintentional RF interferences (RFIs), which may alter the calculation of the scintillation indices, thus compromising the quality of the scientific data and the reliability of the derived space weather monitoring products. Upon the observation of anomalous scintillation indices computed by a GISTM receiver in the Mediterranean area, the study presents the results of the analysis and characterization of a deliberate, unclassified interferer acting on the L1/E1 GNSS frequencies, captured through an experimental setup based on a Software Defined Radio (SDR) architecture. The paper also hilights the adverse impacts of the interferer on the scintillation indices employed in scientific investigations. Additionally, a dataset of Intermediate Frequency (IF) signals samples affected by the RFI will be available at IEEE DataPort upon publication.

Regional Total Electron Content (TEC) Maps proffer better mitigation effects in ionospheric models which are needed to resolve ionospheric TEC gradient errors associated with space-based technologies such as Global Navigation Satellite Systems (GNSS) and Space-Based Augmentation Systems (SBAS). EGNOS (European Geostationary Navigation Overlay System) is a European SBAS system that provides integrity, accuracy, continuity and availability to critical GNSS applications like aviation and others over ECAC (European Civil Aviation Conference) area. The EGNOS Ionospheric model is built with the concept of the ordinary Planar fit technique. This paper focuses on modified Planar fit, ordinary Kriging and modified Kriging techniques to validate the EGNOS algorithm during different geophysical (geomagnetically quiet and disturbed) conditions. The structure of EGNOS was strictly adhered to during the study and only publicly available GNSS ground-based stations over the ECAC area are engaged in the study. The preliminary results obtained show that adapting modified Planar fit and Kriging techniques could improve the EGNOS services over the ECAC area, most especially the northern part near the high latitudes and the southern part near the low latitude regions.

The ionospheric equivalent slab thickness ($\tau $ τ ) is a parameter characterizing both the distribution of the plasma in the ionosphere and the shape of the corresponding vertical electron density profile. It is calculated as the ratio of the vertical total electron content (vTEC) to the ionospheric F2-layer electron density maximum (NmF2). Since its definition dated back in the 60s, a lot of information on the behavior of $\tau $ τ for different helio-geophysical conditions has been cumulated and the connection with several plasma properties has been also demonstrated. The beginning of the Global Positioning System (GPS) era in the 90s had a strong effect on the studies about $\tau $ τ because GPS signals allow to obtain the vTEC up to about 20000 km of altitude. Recently, $\tau $ τ has also found application in many data-assimilation methodologies, especially for the improvement of empirical ionospheric models based on near real-time data. All of these topics are reviewed and discussed in this paper based on the literature published in the last sixty years.Moreover, to highlight and summarize the main global climatological features of $\tau $ τ , in this work we selected thirty-two ionospheric stations globally distributed and co-located with ground-based Global Navigation Satellite System (GNSS) receivers, for the last two solar cycles. This allowed to collect a dataset of NmF2 and vTEC that represents the largest and most complete ever analyzed for studies concerning $\tau $ τ , which gave the chance to deeply investigate its spatial, diurnal, seasonal, and solar activity variations. The corresponding results are presented and discussed in the light of the existing literature.

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.

The state of the Earth’s ionosphere is an important aspect of the Sun-Earth system. It reflects dynamical coupling of the solar wind with the Earth’s magnetosphere. Its understanding has also an applied aspect in the context of the space weather effects. For example, ionospheric plasma irregularities impact the propagation of radio waves, and they can degrade radio communication or positioning with the Global Navigation Satellite Systems (GNSS). The European Space Agency’s Swarm+ 4DIonosphere initiative aims at advancing our understanding and characterisation of the processes in the ionosphere to better model and eventually predict the state of the ionosphere. Within this framework, through the project “Swarm Variability of Ionospheric Plasma” (Swarm-VIP), we analyse spatiotemporal characteristics of ionospheric plasma at different geomagnetic latitudes and uncover coupling between various scales in the ionosphere. Taking advantage of the orbital characteristics of the Swarm satellites and using complementary analysis techniques, such as wavelets or Fast Iterative Filtering, we ascertain the dominant scales at given geomagnetic conditions. The result of the study is a semi-empiric model of the ionosphere based on the generalised linear modeling approach. The model determines the probability of occurrence of different scales in ionospheric plasma with respect to geomagnetic conditions. It also gives insight into ionospheric structuring and related space weather effects. The Swarm-VIP model is provided globally, along the whole orbits of the Swarm satellites, and a special emphasis is put on the polar regions, Arctic and Antarctica, and the European sector, where the validation study is carried out with a network of the ground-based instruments.

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).

Periods of accelerated seismicity have been observed during the preparation process of many large earthquakes. This accelerating seismicity can be detected by the Accelerated Moment Release (AMR) method and its recent Revised version (R-AMR) when the two techniques are applied to earthquake catalogues. The main aim of this study is to investigate the seismicity preceding large mainshocks and possibly increase our comprehension of the underlying physics. In particular, we applied both the AMR and R-AMR to the seismicity preceding 14 large worldwide shallow earthquakes, i.e. with focal depth less than 40 km, with magnitude M > 6 for Mediterranean area, and M ≥ 6.4 in the rest of the world, occurred from 2014 to 2018. Twelve case studies were analysed in the framework of SwArm For Earthquake study project funded by ESA, comprising the period 2014–2016; two additional cases were also considered to confirm the goodness of the methodology outside the period of the project catalogues. In total, R-AMR shows better performances than AMR, in 11 cases out of 14. In particular, in four out of 14 cases (i.e. 28.6%), the R-AMR method shows that acceleration exists due to an evident clustering in time–space on the faults, thus guiding the convergence of the fit; in seven cases (i.e. 50%) the R-AMR discloses acceleration, although no clustering around the fault is present; the remaining three cases (i.e. 21.4%) show no emerging acceleration from background. Finally, when R-AMR is compared with simulations, we verify that in most of the cases the acceleration is real and not casual.

We investigate the response of the topside ionosphere, auroral and polar sectors, to the forcing of the geospace during September 2017. Specifically, we aim at characterizing such a response in terms of the involved spatial scales and of their intensification during the different auroral and polar cap activity conditions experienced in the selected month, that is characterized by severe geomagnetic storm conditions. For our purposes, we leverage on and compare various in situ plasma density data products provided by the Swarm constellation of the European Space Agency (ESA). The spatio-temporal variability of the involved scales in the plasma density observation is featured through the application of the Fast Iterative Filtering (FIF) signal decomposition technique and, for the first time in the ionospheric field, of a FIF-derived dynamical spectrum called “IMFogram”. The instantaneous time-frequency representation provided through the IMFogram illustrates the time development of the multi-scale processes with spatial and temporal resolutions higher than those obtained with traditional signal processing techniques. To demonstrate this, the IMFogram is tested against Fast Fourier and Continuous Wavelet Transforms. With our fine characterization, we highlight how scale cascading and intensification processes in the plasma density observations follow the ionospheric currents activity, as depicted through the auroral activity and polar cap indices, and through the field-aligned currents data product provided by Swarm.

Swarm is the first European Space Agency (ESA) constellation mission for Earth Observation. Three identical Swarm satellites were launched into near-polar orbits on 22 November 2013. Each satellite hosts a range of instruments, including a Langmuir probe, GPS receivers, and magnetometers, from which the ionospheric plasma can be sampled and current systems inferred. In March 2018, the CASSIOPE/e-POP mission was formally integrated into the Swarm mission through ESA’s Earthnet Third Party Mission Programme. Collectively the instruments on the Swarm satellites enable detailed studies of ionospheric plasma, together with the variability of this plasma in space and in time. This allows the driving processes to be determined and understood. The purpose of this paper is to review ionospheric results from the first seven years of the Swarm mission and to discuss scientific challenges for future work in this field.

The main climatological features of the ionospheric equivalent slab thickness (τ) for the Northern hemisphere midlatitudes are analyzed. F2-layer peak electron density values recorded at three midlatitude ionospheric stations (Chilton 51.5° N, 0.6° W, U.K.; Roquetes 40.8° N, 0.5° E, Spain; Wallops Island 37.9° N, 75.5° W, USA) and vertical total electron content values from colocated ground-based Global Navigation Satellite System receivers are used to calculate a dataset of τ values for the last two solar cycles, considering only magnetically quiet periods. Results are presented both as grids of binned medians and as boxplots as a function of local time and month of the year, for different solar activity levels. Corresponding trends are first compared to those output by the midlatitude empirical model developed by Fox et al. (Radio Sci 26:429–438, 1991) and then discussed in the light of what is known so far. From this investigation, the strong need to implement an improved empirical model of τ has emerged. Both Space Weather and Space Geodesy applications might benefit from such model. Therefore, both the dataset and the methodology described in the paper represent a first fundamental step aimed at implementing an empirical climatological model of the ionospheric equivalent slab thickness. The study highlighted also that at midlatitudes τ shows the following main patterns: daytime values considerably smaller than nighttime ones (except in summer); well-defined maxima at solar terminator hours; a greater dispersion during nighttime and solar terminator hours; no clear and evident solar activity dependence.

IONORING (IONOspheric RING) is a tool capable to provide the real-time monitoring and modeling of the ionospheric Total Electron Content (TEC) over Italy, in the latitudinal and longitudinal ranges of 35°N–48°N and 5°E–20°E, respectively. IONORING exploits the Global Navigation Satellite System (GNSS) data acquired by the RING (Rete Integrata Nazionale GNSS) network, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system provides TEC real-time maps with a very fine spatial resolution (0.1° latitude x 0.1° longitude), with a refresh time of 10 min and a typical latency below the minute. The TEC estimated at the ionospheric piercing points from about 40 RING stations, equally distributed over the Italian territory, are interpolated using locally (weighted) regression scatter plot smoothing (LOWESS). The validation is performed by comparing the IONORING TEC maps (in real-time) with independent products: (i) the Global Ionospheric Maps (GIM) - final product- provided by the International GNSS Service (IGS), and (ii) the European TEC maps from the Royal Observatory of Belgium. The validation results are satisfactory in terms of Root Mean Square Error (RMSE) between 2 and 3 TECu for both comparisons. The potential of IONORING in depicting the TEC daily and seasonal variations is analyzed over 3 years, from May 2017 to April 2020, as well as its capability to account for the effect of the disturbed geospace on the ionosphere at mid-latitudes. The IONORING response to the X9.3 flare event of September 2017 highlights a sudden TEC increase over Italy of about 20%, with a small, expected dependence on the latitude, i.e., on the distance from the subsolar point. Subsequent large regional TEC various were observed in response to related follow-on geomagnetic storms. This storm is also used as a case event to demonstrate the potential of IONORING in improving the accuracy of the GNSS Single Point Positioning. By processing data in kinematic mode and by using the Klobuchar as the model to provide the ionospheric correction, the resulting Horizontal Positioning Error is 4.3 m, lowering to, 3.84 m when GIM maps are used. If IONORING maps are used as the reference ionosphere, the error is as low as 2.5 m. Real-times application and services in which IONORING is currently integrated are also described in the conclusive remarks.

A new method for analyzing travelling ionospheric disturbances (TIDs) is developed by using two B-spline basis functions of degree 4 on the Total Electron Content (TEC) data from the ground-based Global Positioning System (GPS) receivers. This method enhances the spatial resolution to about 0.1° (geographic latitude) × 0.1° (geographic longitude), which is useful in studying all scales (small, medium and large) TIDs. Using this method, we investigated TIDs and their associated scintillation on 18–19 July 2013 at Southern Hemisphere and found phase scintillation is more sensitive than amplitude scintillation to the TIDs at South Pole. To see the full impact of TIDs on scintillation, we have used a proxy phase scintillation index, calculated using geodetic GPS receivers over Antarctica. We have verified the presence of TIDs during these two days by using a Global Navigation Satellite System (GNSS)-TEC single station approach and SuperDARN slant range signals. Our results show the TEC fluctuations are associated with ionospheric scintillation. The shape of TIDs, their elongation and flattening along/across the geographic latitude/longitude, seems to be related to the magnitude and occurrence of ionospheric scintillations. Magnetospheric particle precipitation boost TEC gradients and generate stronger amplitude scintillation, however, large-scale plasma irregularities cause overall enhancement in magnitude of the phase scintillation index. Due to the high turbulence in the polar ionosphere, TIDs change their shapes quite quickly and/or may disappear in the background ionosphere. B-spline TIDs analysis method is very useful in identifying the visible as well as hidden TIDs parts in the polar ionosphere. For the first time, ionospheric scintillation has been investigated in the vicinity of TIDs at high- latitude in the southern hemisphere. Further, the presented B-spline TIDs analysis method is unique and simple in itself as it uses GPS receiver processed TEC data as the primary input. Our results show that at polar latitude it is not necessary that TIDs always appear near the high TEC regions. Usefulness of the B-spline TIDs detection method has been demonstrated in analyzing TIDs at all geographic locations and different solar activity conditions by comparing B-spline TIDs method produced results with the previous case studies.

This paper presents a comparison of the vertical total electron content (vTEC) estimated over Italy using two different approaches: the GPS Global Ionosphere Maps (GIMs) and the so-called “calibration technique” developed by Ciraolo in 2007. The study has been carried out at a regional level by considering three Italian dual-frequency stations of the GPS permanent network “Rete Integrata Nazionale GPS (RING)”. The GPS receivers are permanently installed at Madesimo (geographical coordinates: 46.5 N, 9.4 E), Rome (geographical coordinates: 41.8 N, 12.5 E) and Resuttano (geographical coordinates: 37.7 N, 14.1 E), respectively in the north, center and south of Italy. Time windows selected for the analysis include periods of both low (July 2008 to June 2009) and high (September 2013 to August 2014) solar activity. The two datasets have also been studied considering both quiet and disturbed geomagnetic activity conditions. Moreover, the effects of an extreme geomagnetic storm have been investigated in March 2015 when the well-known St. Patrick storm occurred. Overall, GIM estimated values are always higher than those calibrated by the Ciraolo procedure for all the considered datasets. The differences between the two methods increase as the latitude decreases, and they increase as the solar activity intensifies. The outcomes of this study shall be helpful when applying GlMs at a regional level.

The Istituto Nazionale di Geofisica e Vulcanologia (INGV) has a long tradition in collecting scientific data to support upper atmosphere physics research. In addition to the historical equipment no...

We investigate the reliability of the phase scintillation index determined by receiving Global Navigation Satellite System (GNSS) signals at ground in the high-latitudes. To the scope, we report about the capabilities of recently introduced detrending scheme based on the signal decomposition provided by the Fast Iterative Filtering (FIF) technique. This detrending scheme enables a fine tuning of the cutoff frequency for phase detrending used in the phase scintillation index definition, aimed at disentangling diffraction and refraction effects. On a single case study based on GPS and Galileo data taken by a GNSS Ionospheric Scintillation Monitor Receiver (ISMR) in Concordia Station (Antarctica), we show how the FIF-based detrending allows deriving adaptive cutoff frequencies, whose value changes minute-by-minute. They are found to range between 0.4 Hz and 1.2 Hz. This allows better accounting for diffractive effects in phase scintillation index calculation and also showing the limitations on the use of such index, being still widely used in the community, both to characterize the features of ionospheric irregularities and to adopt mitigation solutions.

Made available in DSpace on 2022-05-01T09:47:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 We estimate the zonal drift velocity of small-scale ionospheric irregularities at low latitude by leveraging the spaced-receivers technique applied to two GNSS receivers for scintillation monitoring installed along the magnetic parallel passing in Presidente Prudente (Brazil, magnetic latitude 12.8°S). The investigated ionospheric sector is ideal to study small-scale irregularities, being located close to the expected position of the southern crest of the equatorial ionospheric anomaly. The measurement campaign took place between September 2013 and February 2014, i.e. equinox and summer solstice seasons under solar maximum, during which the probability of formation of small-scale irregularities is expected to maximize. We found that the hourly average of the velocity increases up to 135 m/s right after the local sunset at ionospheric altitudes and then smoothly decreases in the next hours. Such measurements are in agreement with independent estimations of the velocity made by the Incoherent Scatter Radar located at the Jicamarca Radio Observatory (magnetic latitude 0.1°N), by the Boa Vista Ionosonde (magnetic latitude 12.0°N), and by applying a recently-developed empirical regional short-term forecasting model. Additionally, we investigated the relationship with the percentage occurrence of amplitude scintillation; we report that it is exponentially dependent on the zonal velocity of the irregularities that cause it. Istituto Nazionale di Geofisica e Vulcanologia SpacEarth Technology Space Research Centre of the Polish Academy of Sciences Instituto Federal de Educação Ciência e Tecnologia de São Paulo Universidade Estadual Paulista “Júlio de Mesquita Filho” University of Salento Universidade Estadual Paulista “Júlio de Mesquita Filho”

We contribute to the debate on the identification of phase scintillation induced by the ionosphere on the global navigation satellite system (GNSS) by introducing a phase detrending method able to provide realistic values of the phase scintillation index at high latitude. It is based on the fast iterative filtering signal decomposition technique, which is a recently developed fast implementation of the well-established adaptive local iterative filtering algorithm. FIF has been conceived to decompose nonstationary signals efficiently and provide a discrete set of oscillating functions, each of them having its frequency. It overcomes most of the problems that arise when using traditional time–frequency analysis techniques and relies on a consolidated mathematical basis since its a priori convergence and stability have been proved. By relying on the capability of FIF to efficiently identify the frequencies embedded in the GNSS raw phase, we define a method based on the FIF-derived spectral features to identify the proper cutoff frequency for phase detrending. To test such a method, we analyze the data acquired from GPS and Galileo signals over Antarctica during the September 2017 storm by the ionospheric scintillation monitor receiver (ISMR) located in Concordia Station (75.10° S, 123.33° E). Different cases of diffraction and refraction effects are provided, showing the capability of the method in deriving a more accurate determination of the $$\sigma_{\phi }$$ σ ϕ index. We found values of cutoff frequency in the range of 0.73–0.83 Hz, providing further evidence of the inadequacy of the choice of 0.1 Hz, which is often used when dealing with ionospheric scintillation monitoring at high latitudes.

Applying a multi-parametric approach, we already investigated the preparatory phase of several medium and large (M6.0 ~ M8.3) earthquakes occurred in the last 6 years in different locations in the World. In some cases, a chain of processes from the lithosphere to atmosphere and ionosphere has been successfully detected (e.g. M7.8 Ecuador 2016: Akhoondzadeh, 2018, ASR, https://doi.org/10.1016/j.asr.2017.07.014; Italian seismic sequence (M6.5) 2016-2017: Marchetti et al., 2019, RSoE, https://doi.org/10.1016/j.rse.2019.04.033; M7.5 Indonesia 2018: Marchetti et al., 2019, JAES, https://doi.org/10.1016/j.jseaes.2019.104097). These analyses underline the importance to study all the “spheres” that surround the Earth as suggested by a Geosystemic approach (De Santis et al., 2019, Entropy, https://doi.org/10.3390/e21040412). To analyse the anomalies that occur in the atmosphere we typically calculate the mean and standard deviation of the “historical time series” of the investigated parameter based on around 40 years of data, and then we superpose the value of the same quantity in the earthquake year. If the value overpasses two standard deviations of the historical time series, we define this day/parameter as anomalous. Applying the same methodology presented in previous works that studied climatological parameters such as skin temperature, total column water vapour, aerosols, and SO2, which seem to provide anomalies possibly related to the earthquake preparation phase (e.g. Piscini et al., 2017, PAGeoph, https://doi.org/10.1007/s00024-017-1597-8), here we investigate more atmospheric parameters proposed as possible precursors in the Lithosphere Atmosphere Ionosphere Coupling (LAIC) models (Pulinets and Ouzounov, 2011, JAES, https://doi.org/10.1016/j.jseaes.2010.03.005) such as methane and surface concentration of carbon monoxide. Other parameters, such as dimethylsulfide could be useful in other geophysical events, such as the volcano eruptions (Piscini et al. PAGeoph 2019, https://doi.org/10.1007/s00024-019-02147-x).In this study, we also apply a Worldwide Statistical Correlation (WSC), as it was successfully applied to Swarm satellites electromagnetic anomalies and earthquakes, providing some statistical evidence for such perturbations in ionosphere before the occurrence of M5.5+ earthquakes (De Santis et al., 2019, Sci. Rep., https://doi.org/10.1038/s41598-019-56599-1).The statistical approaches applied to these climatological data, provided by meteorological agencies such as ECMWF and NOAA, provides some interesting concentrations of atmospheric anomalies, preceding from days to several weeks the occurrence of the largest earthquakes from 1980 to 2017.The study of several chemical and physical (e.g. aerosol particles) components in the atmosphere, the involved physical processes, the chemical reactions and chemical constraints (such as the elements lifetime and interactions in the atmosphere) can help to distinguish which LAIC model is more reliable to produce the observed anomalies before the occurrence of a large earthquake.

The Space Weather effects on the ionosphere considerably affect several modern technology infrastructures, such as telecommunication systems, power networks and in general systems relying on satellite navigation. The polar regions have always been a natural laboratory for the analysis of these phenomena and regular observations are required to gain better knowledge about the relationships between the ionized atmosphere and the others atmospheric layers as well as to provide support to civil aviation and maritime for the safety of the polar routes.The Istituto Nazionale di Geofisica e Vulcanologia (INGV) has a long history in acquiring ionospheric data in the polar regions and currently operates in the Arctic two permanent observatories in Svalbard (Ny-Ålesund and Longyearbyen), Norway, equipped with three GNSS receivers for scintillation and TEC measurement. An additional receiver will be installed soon at the Thule Air Base (Greenland).The uninterrupted data production from these instruments and the necessity to provide near real-time access to this information makes it necessary to develop suited procedures and ad-hoc IT infrastructures. To address these needs the INGV designed the SWIT system (Space Weather Information Technology) for data management and the web-platform eSWua (electronic Space Weather upper atmosphere) for data dissemination. With regard to the Arctic region, the information-flow from Svalbard stations is provided by optical fibre connections and the SWIT-DBMS operates the ingestion of this data at the INGV central repository within 15 minutes or less. The eSWua website offers a GUI for near real-time and historical data visualization, while web-based tools and a RESTful web-service will provide free access to the data at different processing levels. The planning and design of this infrastructure takes advantage of the experience gained from ongoing projects like the NADC (the Italian National Antarctic Data Center).In this paper the state of the art of the INGV Arctic and Antarctic data management system for the Ionospheric and space weather data and the efforts undertaken to improve the access and availability of these information are presented and discussed.

The National Antarctic Data Center (NADC) is the ICT infrastructure designed to gather, handle, publish and provide access to the large amount of scientific data collected by several projects in th...

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The variations of the hourly observations of the critical frequency foF2, recorded at the Ionospheric Observatory of Rome by the AIS-INGV ionosonde (geographic coordinates 41.82° N, 12.51° E; geomagnetic coordinates 41.69° N, 93.97° E) during the low activity periods at the turn of solar cycles 21–22, 22–23 and 23–24, are investigated. Deviations of foF2 greater than ± 15% with respect to a background level, and with a minimum duration of 3 h, are here considered anomalous. The dependence of these foF2 anomalies on geomagnetic activity has been accurately investigated. Particular attention has been paid to the last deep solar minimum 2007–2009, in comparison with the previous solar cycle minima. The lack of day-time anomalous negative variations in the critical frequency of the F2 layer, is one of the main findings of this work. Moreover, the analysis of the observed foF2 anomalies confirms the existence of two types of positive F2 layer disturbances, characterised by different morphologies and, different underlying physical processes. A detailed analysis of four specific cases allows the definition of possible scenarios for the explanation of the mechanisms behind the generation of the foF2 anomalies.