Geomagnetically induced currents (GICs), occurring as a result of space weather events, represent a hazard for the secure and safe operation of electrical power grids and oil/gas pipelines. The most exposed countries are those at high latitudes where, in the past, the occurrence of intense GICs has seriously damaged part of their power networks. However, very powerful space weather events have resulted in intense GICs also at middle and low latitudes. The GIC index is a proxy of the geoelectric field, and it can be estimated straightforwardly from magnetic observatory data. In this work, the GIC index is computed to investigate the possible impact of space weather events on the Italian territory. We first calculate the GIC index using data from the magnetic observatories of Castello Tesino, Duronia, and Lampedusa, together covering the whole Italian latitudinal extension, and show its behavior during the 2015 St. Patrick's day storm. Then, we consider measurements from the two longest running Italian magnetic observatories, that is, Castello Tesino and L'Aquila, and estimate the GIC index over more than 20 years of observations. A preliminary characterization of the general risk to which the Italian power grid network is exposed is given. Results show that during periods of high magnetic activity, potentially detrimental GICs could flow through the power network, especially at the highest Italian latitudes that are characterized by a low conductivity lithosphere.

Forecasting geomagnetic indices represents a key point to develop warning systems for the mitigation of possible effects of severe geomagnetic storms on critical ground infrastructures. Here we focus on SYM‐H index, a proxy of the axially symmetric magnetic field disturbance at low and middle latitudes on the Earth's surface. To forecast SYM‐H, we built two artificial neural network (ANN) models and trained both of them on two different sets of input parameters including interplanetary magnetic field components and magnitude and differing for the presence or not of previous SYM‐H values. These ANN models differ in architecture being based on two conceptually different neural networks: the long short‐term memory (LSTM) and the convolutional neural network (CNN). Both networks are trained, validated, and tested on a total of 42 geomagnetic storms among the most intense that occurred between 1998 and 2018. Performance comparison of the two ANN models shows that (1) both are able to well forecast SYM‐H index 1 h in advance, with an accuracy of more than 95% in terms of the coefficient of determination R²; (2) the model based on LSTM is slightly more accurate than that based on CNN when including SYM‐H index at previous steps among the inputs; and (3) the model based on CNN has interesting potentialities being more accurate than that based on LSTM when not including SYM‐H index among the inputs. Predictions made including SYM‐H index among the inputs provide a root mean squared error on average 42% lower than that of predictions made without SYM‐H.

The scaling features of electron density fluctuations during the St. Patrick's magnetic storm (17 March 2015) are analyzed to try to characterize the possible turbulent nature of the ionosphere during the development of the geomagnetic storm. The electron density values recorded by two of the three satellites of Swarm constellation during a period of 7 days (16–22 March 2015) around the storm peak are analyzed at middle‐ and high‐latitude regions in both hemispheres. The analysis reveals interesting patterns in the scaling properties of electron density fluctuations and a possible explanation for the occurrence of high values of the Rate of change Of the electron Density Index (RODI). Indeed, the obtained results seem to suggest that very high values of RODI, which describes the structuring of the plasma within a fixed time and is used as an ionospheric disturbance index, are correlated with the antipersistent character of electron density fluctuations and with the values around 5/3 of the power spectral density scaling exponent. These features are independent of the different phases of the analyzed geomagnetic storm and seem to support the idea of a fluid and/or magnetohydrodynamic turbulence as the main responsible of the high values of RODI recorded at high latitudes in the auroral and polar cap regions.

This paper discusses the occurrence of Global Positioning System (GPS) loss of lock events obtained by considering total electron content (TEC) measurements carried out by the three satellites of the European Space Agency Swarm constellation from December 2013 to December 2020, which represents the longest dataset ever used to perform such an analysis. After describing the approach used to classify a GPS loss of lock, the corresponding occurrence is analyzed as a function of latitude, local time, season, and solar activity to identify well-defined patterns. Moreover, the strict relation of the occurrence of the GPS loss of lock events with defined values of both the rate of change of electron density index (RODI) and the rate of change of TEC index (ROTI) is highlighted. The scope of this study is, on one hand, to characterize the background conditions of the ionosphere for such events and, on the other hand, to pave the way for their possible future modeling. The results shown, especially the fact that GPS loss of lock events tend to happen for well-defined values of both RODI and ROTI, are of utmost importance in the light of Space Weather effects mitigation.

The global statistical median behavior of the electron temperature (T_e) in the topside ionosphere was investigated through in-situ data collected by Langmuir Probes on-board the European Space Agency Swarm satellites constellation from the beginning of 2014 to the end of 2020. This is the first time that such an analysis, based on such a large time window, has been carried out globally, encompassing more than half a solar cycle, from the activity peak of 2014 to the minimum of 2020. The results show that Swarm data can help in understanding the main features of T_e in the topside ionosphere in a way never achieved before. T_e data measured by Swarm satellites were also compared to data modeled by the empirical climatological International Reference Ionosphere (IRI) model and data measured by Jicamarca (12.0°S, 76.8°W), Arecibo (18.2°N, 66.4°W), and Millstone Hill (42.6°N, 71.5°W) Incoherent Scatter Radars (ISRs). Moreover, the correction of Swarm T_e data recently proposed by Lomidze was applied and evaluated. These analyses were performed for two main reasons: (1) to understand how the IRI model deviates from the measurements; and (2) to test the reliability of the Swarm dataset as a new possible dataset to be included in the underlying empirical dataset layer of the IRI model. The results show that the application of the Lomidze correction improved the agreement with ISR data above all at mid latitudes and during daytime, and it was effective in reducing the mismatch between Swarm and IRI T_e values. This suggests that future developments of the IRI T_e model should include the Swarm dataset with the Lomidze correction. However, the existence of a quasi-linear relation between measured and modeled T_e values was well verified only below about 2200 K, while for higher values it was completely lost. This is an important result that IRI T_e model developers should properly consider when using the Swarm dataset.

Recent findings on the nature of magnetic field fluctuations in the high‐latitude ionospheric regions have suggested the existence of scaling features, which are the signature of the occurrence of turbulence. These features mainly characterize the magnetic field fluctuations in those regions where the field‐aligned currents flow. Here, we investigate the nature of the Earth's magnetic field fluctuations using the high‐resolution (50 Hz) magnetic measurements from the European Space Agency Earth's observation mission Swarm. Our study indicates that spatiotemporal anomalous scaling features characterize low‐frequency magnetic field fluctuations in the high‐latitude ionospheric regions of field‐aligned currents at spatial scales in the range 0.8–80 km (timescales in the range 0.1–10 s). The signature of a multifractal nature of these fluctuations suggests a highly complex structure of the field‐aligned currents. Our results support the view of inhomogeneous (filamentary) field‐aligned currents, which can have relevant implications in the comprehension of the physical processes responsible for the magnetospheric‐ionospheric coupling and ionospheric heating.