On March 28, 2025, at 06:20:52 UTC (12:50:52 LT), a catastrophic Mw 7.7 earthquake occurred in central Myanmar-Burma, marking one of the most devastating seismic events in recent history. The earthquake occurred along the Sagaing Fault (SF), a highly active right-lateral strike-slip fault that accommodates the northward motion of the Indian Plate relative to the Sunda Plate. A multiparametric approach has been applied in order to study the preparation phase of this great earthquake, analyzing data from ground, atmosphere and satellite, with a total of eleven kinds of potential earthquake precursors. The results show a sigmoid pattern of all anomalies before and during the earthquake occurrence, typical of a critical system approaching a critical point. The sequence of the anomalies and their space and time concentration support the lithosphere-atmosphere-ionosphere coupling (LAIC) model.

A thermal infrared (TIR) camera was installed at Mefite Lake in Valle d’Ansanto, Irpinia (Italy), to assess whether small variations in cold CO2 flux can be resolved thermally. To our knowledge, this is the first systematic attempt to extract short-period degassing dynamics from TIR data at Mefite. Infrared thermal images taken over a three-hour nighttime interval revealed the spatial distribution and extent of natural CO2 emissions. The high sampling frequency of one minute detected unexpected thermal variability from the source. The extent of temperature variations across the entire site reached almost 3 °C, with durations typically ranging from a few minutes to tens of minutes. Spectral analysis of the temperature time series reported a 1/f-type noise pattern, with significant periods of 2–3 min, 5 min, 26 min, and 61 min observed at different locations. Further intermediate periods were observed at individual points. Differences and delays in temperature variations appeared to be related to distance from the structure’s centre and the presence of water. These temperature fluctuations were interpreted as changes in the gaseous emission flow caused by a few kPa of CO2 escaping due to pressure variations. The gas thermally interacts with the underlying soil, adding or removing heat at the surface. These results demonstrate that high-frequency infrared thermography provides a sensitive and practical tool for quantifying short-term flux variability at natural CO2 vents and for improving the characterisation of their degassing dynamics.

Monthly median foF2 values derived from manual and automatic interpretation of the ionograms at the ionospheric observatory of Rome (41.8 degrees N; 12.5 degrees E) over a 17-year period from 2006 to 2022 were considered in this study. The data were analyzed for the hours between 00 and 23 UT, employing two methods when using autoscaled data: one using only exact hour data, as it is made when using manual interpretations, and another incorporating a quarter-hour before and after the hour. ARTIST and Autoscala software were used for the automatic interpretation of the ionograms respectively from the DPS-4 and AIS-INGV ionosondes. Statistical significance of the differences between the medians obtained using automatic and manual values was determined using standard Student's t-tests, and the mean and standard deviation of the differences were also computed for the whole dataset and for each hour of the day separately, along with the corresponding Mean Absolute Errors and Root Mean Square Errors. While the overall differences were not statistically significant in every case, small significant differences (< 0.1 MHz) were obtained during daytime hours for Autoscala, while mainly at night for ARTIST, demonstrating a slight overall underestimation of the monthly medians from automatic interpretation. Only small differences were found between Autoscala and ARTIST medians, which can therefore be considered equivalent, despite slightly superior performance demonstrated by Autoscala, even when including quarters-hour data. These findings indicate that the foF2 values obtained from ARTIST and Autoscala can reliably substitute manual interpretations for monthly medians computation. (c) 2026 The Author(s). Published by Elsevier B.V. on behalf of COSPAR. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Oblique ionosondes provide an effective means to probe the ionosphere over regions where vertical sounders cannot be deployed, such as oceans or complex terrain. By deploying multiple simple receivers, they also enable a denser spatial sampling of ionospheric conditions. However, extracting ionospheric parameters from oblique ionograms remains challenging due to the long propagation paths and shallow incidence angles of the signals. To address this, verticalization techniques are applied to convert oblique ionograms into equivalent vertical ones, facilitating the retrieval of critical ionospheric parameters. Since 2023, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) has developed and deployed new Software Defined Radio (SDR)-based Pseudo Random Code (PRC) oblique ionosondes, establishing the first nodes of the IonoNet network across Italy. The system operates in a multistatic configuration with separated transmitting and receiving sites in northern, central, and southern Italy, enabling the investigation of ionospheric variability over distances of several hundred kilometres. The Autoscala software is used for real-time ionogram scaling and electron density profile derivation, supporting ionospheric monitoring and alerting applications. The network aims to improve regional ionospheric mapping, validate theoretical models, and explore potential lithosphere-ionosphere coupling processes. (c) 2026 The Author(s). Published by Elsevier B.V. on behalf of COSPAR. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Understanding the variability of the thermosphere–ionosphere (T–I) system across different conditions is especially important, as its state critically affects the operation and safety of numerous low Earth orbit (LEO) satellites. In the absence of routine thermospheric monitoring, ionosonde measurements and satellite data can be used to retrieve key aeronomic parameters at mid-latitudes during noontime via the THERION (THERmospheric parameters from IONosonde observations) method.This study applies the THERION technique to analyze the T–I response in the European and American longitudinal sector to two recent severe geomagnetic storms (October 2024 and January 2025). Validated ionosonde data from Rome, Juliusruh, Millstone Hill and Eglin were used to assess ionospheric variability and derive thermospheric parameters such as neutral composition, temperature, and wind. Results are compared with outputs from the MSISE00 empirical model, highlighting THERION's improved capability in capturing thermospheric dynamics under storm conditions.Additional datasets—including co-located GNSS-derived TEC, geomagnetic field data from the INTERMAGNET network, and interplanetary/magnetospheric conditions—were integrated to provide a comprehensive view of the events and the unique T-I coupling processes associated with each storm.This study is carried out within the Space It Up project funded by the Italian Space Agency, ASI, and the Ministry of University and Research, MUR, under contract n. 2024-5-E.0 - CUP n. I53D24000060005.

The Tonga-Kermadec zone stands out as one of the most active areas in the world for continuous subduction processes characterizing the area. In the recent few years, it has been affected by two important geophysical events: first a strong earthquake of M7.2 on June 15, 2019, with the epicentre in Kermadec Islands (New Zealand), and then an exceptional eruption of Hunga Tonga-Hunga Ha’apai volcano on January 15, 2022. We focused our attention on the phenomena appearing before, during and soon after each event, employing a multi-parametric and multi-layer approach in order to analyse the geodynamics of the entire area and the involved lithosphere-atmosphere-ionosphere coupling (LAIC). In details, for the lithosphere we conducted a seismic analysis of the earthquake sequence culminating with the mainshock on June 15, 2019, and of those preceding the big eruption, within a circular area with Dobrovolsky strain radius corresponding to that of an equivalent seismic event of magnitude equal to the energy released during the eruption. Moving to the atmosphere, we considered some parameters possibly influenced by seismic and volcanic events, using the CAPRI algorithm to the ECMWF datasets to detect anomalies in their values. Finally, by observing satellite data, we analysed the magnetic field and electron burst precipitations, potentially correlated to the events. All these observations, along with their similarities and differences, provide a better insight of the complex tectonic context.

The nature of the long-term changes in the upper atmosphere morphology at mid-latitude remains a subject of debate, particularly regarding whether these changes are purely driven by geomagnetic and solar activities or whether forcing from the lower atmosphere, such as CO2 variations, may play a role. To contribute to this debate, we investigate the nature of the long-term trends of the ionospheric and thermospheric parameters by leveraging on ionosonde data digitally recorded at the Rome Observatory since 1976. The following parameters have been investigated under sunlit conditions (12:00 Local Time): critical frequency of the F1 layer (foF1); critical frequency of the F2 layer (foF2), atomic oxygen concentration at 300 km ([O]); ratio between atomic oxygen and molecular nitrogen concentrations at 300 km altitude ([O]/[N2]); exospheric temperature (Tex); thermospheric density at 300 km (ρ). The ionospheric parameters are manually scaled from digital ionograms, whereas thermospheric parameters are retrieved using the THERmospheric parameters from IONosonde observations (THERION) method, which utilises ionosonde observations and a physical model of the ionospheric F region. To investigate the influence of the solar and geomagnetic activity on long term variations, we consider the solar radio flux at 10.7 cm (F10.7) and the geomagnetic disturbance index Ap. To identify the various frequency/period components of the time series under consideration and identify the trends, we leverage the high scale/time resolution offered by the Fast Iterative Filtering (FIF) algorithm. A regression analysis of thermosphere/ionosphere parameters against geomagnetic/solar activity indices has then been conducted to investigate the drivers of long-term variability. Our findings reveal that the identified trends are predominantly controlled by external drivers, particularly long-term solar and geomagnetic activity variations.. The adopted methodology, based on regression modelling, demonstrates that variability in F10.7 and Ap accounts for nearly all of the observed changes, with the exception of atomic oxygen ([O]), which displays a slightly higher unexplained variability (~7%). The inclusion of CO2 concentration as an additional driver improves the regression model for [O]. However, the effect remains statistically limited, indicating that the impact of CO2 on thermospheric cooling might be of little significance. Further studies with extended time series are necessary to better quantify this relationship and evaluate its importance. These results highlight the predominant influence of solar and geomagnetic activity in determining upper atmosphere long-term trends at mid-latitudes.

On 8 May 2024, the solar active region AR13664 started releasing a series of intense solar flares. Those of class X released between 9 and 11 May 2024 gave rise to a chain of fast Coronal Mass Ejections (CMEs) that proved to be geoeffective. The Storm Sudden Commencement (SSC) of the resulting geomagnetic storm was registered on 10 May 2024 and it is, to date, the strongest event since November 2003. The May 2024 storm, named hereafter Mother’s Day storm, peaked with a Dst of –412 nT and stands out as a “standard candle” storm affecting modern era technologies prone to Space Weather threats. Moreover, the recovery phase exhibited almost no substorm signatures, making the Mother’s Day storm as a perfect storm example. Despite the plethora of notable near Earth environment modifications that are still under investigation, in this paper we concentrate on the Space Weather effects over the Mediterranean sector, with a focus on Italy. In fact, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) manages a dense network of GNSS receivers (including scintillation receivers), ionosondes and magnetometers in the Mediterranean area, which facilitated for a detailed characterization of the modifications induced by the storm. Concerning the geomagnetic field, observatories located in Italy recorded a SSC with a rise time of only 3 minutes and a maximum variation of around 600 nT. The most notable ionospheric effect following the arrival of the disturbance was a significant decrease in plasma density on 11 May, resulting in a pronounced negative ionospheric storm registered on both the critical F2-layer frequency (foF2) and the Total Electron Content (TEC). Another negative effect was recorded on 13 May, while no signatures of composition changes and, specifically, to a decrease of the [O]/[N ] ratio. The IRI UP IONORING 2 data-assimilation procedure, recently developed to nowcast foF2 over Italy, proved to be quite reliable during this extreme event, being characterised just by an overestimation during the main phase of the storm, when the electron density and the height of the F region decreased and increased, respectively. Relevant outcomes of the work relate to the Rate Of TEC change Index (ROTI), which shows unusually high spatially distributed values on the nights of 10 and 11 May. The ROTI enhancements on 10 May might be linked to Stable Auroral Red (SAR) arcs and an equatorward displacement of the main ionospheric trough. Instead, the ROTI enhancements on 11 May might be triggered by a joint action of low-latitude plasma pushed poleward by the pre-reversal enhancement (PRE) in the post-sunset hours and wave-like perturbations propagating from the North. Furthermore, the storm generated immediate attention of the general public to Space Weather effects, including mid-latitude visible phenomena like SAR arcs. This paper outlines the report of the Space Weather Monitoring Group (SWMG) of the INGV Environment Department and its effort to disseminate information about this exceptional event.

The coupling processes among the lithosphere, atmosphere, and ionosphere (LAI) during the earthquake preparation phase are still an open scientific debate. Comprehensive LAI coupling effects around the 2022 Ms6.8 Luding earthquake in China are investigated with a multi-parameter and multi-layer approach, including the b-value, revised accelerated moment release, Earth resistivity, ELF magnetic field emissions, atmospheric electric field, surface temperature, foF2 from ionosonde, GNSS TEC, Ne and magnetic field from CSES and Swarm satellites, and energetic electrons from CSES and NOAA satellites. It is found that the anomalies start from the lithospheric parameters as Earth resistivity and b-values 1–2 years before to reflect the local stress loading in the seismic region, then the ionospheric and atmospheric disturbances occur and accelerate −50 days before and −15 days before, and finally the electrons precipitate a few days before. The simultaneous perturbations in LAI illustrate the thermodynamic coupling channel, such as on 24 August, −12 days before. Meanwhile, the abundant developed ionospheric anomalies without atmospheric disturbances demonstrate the electromagnetic coupling way from the lithosphere to the ionosphere directly. Finally, the results demonstrate a two-way model of LAIC: one way is characterized by a slow chain of processes, of thermodynamic nature, starting from the ground and proceeding to the above atmosphere and ionosphere, showing an exponential trend in the cumulative number of anomalies; the second way is characterized by oscillating electromagnetic coupling between the lithosphere and ionosphere, showing intermittent fluctuations in the corresponding cumulative number of anomalies.

A comparison of three types of ionosonde data from Europe during an interplanetary coronal mass ejection (ICME)- and a corotating interaction region (CIR)-driven geomagnetic storm event is detailed in this study. The selected events are 16–20 March 2015 for the ICME-driven storm and 30 May to 4 June 2013 for the CIR-driven one. Ionospheric data from three European ionosonde stations, namely Pruhonice (PQ), Sopron (SO) and Rome (RO), are investigated. The ionospheric F2-layer responses to these geomagnetic events are analyzed with the ionospheric foF2 and h’F2 parameters, the calculated deltafoF2 and deltahF2 values, the ratio of total electron content (rTEC) and Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) satellite Global Ultraviolet Imager (GUVI) thermospheric [O]/[N2] measurement data. The storm-time and the quiet-day mean values are also compared, and it can be concluded that the quiet-day curves are similar at all the stations while the storm-time ones show the latitudinal dependence during the development of the storm. As a result of the electron density comparison, during the two events, it can be concluded that the sudden storm commencement (SSC) that characterized the ICME induced a traveling atmospheric disturbance (TAD) seen in the European stations in the main phase, while this is not seen in the CIR-driven ionospheric storm, which shows a stronger and more prolonged negative effect in all the stations, probably due to the season and the depleted O/N2 ratio.

On 6 February 2023, Turkey experienced its most powerful earthquake in over 80 years, with a moment magnitude (Mw) of 7.7. This was then followed by a second earthquake of Mw 7.6 just nine hours later. According to the lithosphere–atmosphere–ionosphere coupling (LAIC) models, such a significant seismic activity is expected to cause anomalies across various observables, from the Earth’s surface to the ionosphere. This multidisciplinary study investigates the preparatory phase of these two major earthquakes by identifying potential precursors across the lithosphere, atmosphere, and ionosphere. Our comprehensive analysis successfully identified and collected various anomalies, revealing that their cumulative occurrence follows an accelerating trend, either exponential or power-law. Most anomalies appeared to progress from the lithosphere upward through the atmosphere to the ionosphere, suggesting a sequential chain of processes across these geospheres. Notably, some anomalies deviated from this overall trend, manifesting as oscillating variations. We propose that these anomalies support a two-way coupling model preceding major earthquakes, highlighting the potential role of fluid chemistry in facilitating these processes.

This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach.

The comparison of three types of ionosonde data from Europe during an Interplanetary Coronal Mass Ejection (ICME) and a Stream Interaction Regions (SIRs) / Corotating Interaction Regions (CIRs) -driven geomagnetic storm event is detailed in this study. The selected events are 16-20 March 2015 for the ICME-driven and 30 May to 04 June 2013 for the SIR/CIR-driven one. Ionospheric data from three European ionosonde stations, namely Pruhonice (PQ), Sopron (SO) and Rome (RO), are investigated. The ionospheric F2-layer responses to these geomagnetic events are analyzed with the ionospheric foF2 and h’F2 parameter, the calculated deltafoF2 and deltahF2 values, ratio of Total Electron Content (rTEC) and Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) satellite Global Ultraviolet Imager (GUVI) thermospheric [O]/[N2] measurement data. The storm-time and the quiet day mean values are also compared, and it can be concluded that the quiet day curves are similar at all stations while the storm-time ones showed the latitudinal dependence during the development of the storm. As a result of the electron density comparison, during the two events it can be concluded that SSC that characterized the ICME induced a Travelling Atmospheric Disturbance (TAD) seen in the European stations, while this is not in the SIR/CIR-driven ionospheric storm, which showed a stronger and more prolonged negative effect in all stations probably due to the season.

Three earthquakes of comparable magnitude and in different tectonic contexts occurred on 15 June 2019 (M7.2) in New Zealand (Kermadec Islands), on 6 July 2019 (M7.1) in California (Ridgecrest) and on 21 May 2021 (M7.3) in China (Maduo) (dates in UT). We applied a multiparameter - multilayer approach to lithospheric, atmospheric and ionospheric data, the latter taken from CSES and Swarm satellites, before the mentioned large earthquakes to detect potential pre-earthquake anomalies. In all case studies, we note the following: a) similar precursor times of occurrences, confirming the Rikitake law for which the larger the earthquake magnitude the longer the anticipation time of the precursor and b) a clear acceleration of the possible precursory anomalies before each mainshock, as typical of critical systems approaching a critical state. We propose an interpretative model to take into account the chain of detected phenomena.

Several empirical formulations used over time to estimate the fundamental ionospheric parameter hmF2 have been compared in this study. These are the first formulation proposed by Shimazaki (1955) (SHI-1955) as a function of the propagation parameter M(3000)F2, the more accurate BSE-1979 formula proposed by Bilitza et al. (1979) and firstly adopted by the International Reference Ionosphere (IRI) model, and the newest Altadill-Magdaleno-Torta-Blanch (AMTB-2013) (Altadill et al., 2013) and SHU-2015 (Shubin, 2015) mod-els, obtained with a different approach with no explicit dependence on any ionospheric parameter and added as alternative options in the IRI-2016. The evaluation of the accuracy of the available formulation is performed by comparing the modeled values of hmF2 with those simultaneously obtained with independent measurements from the Incoherent Scatter Radar (ISR) installed at the Millstone Hill ionospheric station. The database considered consists of 3626 measurements, thus allowing the evaluation of the results for different helio-geophysical conditions. SHI-1955 and BSE-1979 formulations are evaluated also using input data manually scaled from ionograms recorded at the same location, with the aim of evaluating their accuracy when updated with validated data rather than modeled ones. The SHU-2015 is confirmed the best option in any condition, while AMTB-2013 turns out to perform poorly during night, when SHI-1955 and BSE-1979 fed by validated data can be used for trend analyses due to the high correlation with ISR data. Despite this, BSE-1979 performs better with modeled parameters as input, in terms of RMSE and mean deviation from ISR data. The use of SHI-1955 with CCIR-modeled M(3000)F2 is discouraged under daytime conditions even for long trend analyses.(c) 2023 COSPAR. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).

A new method to define a background for the ionospheric electron density (Ne) is proposed, making use of mid-latitude measurements under different solar conditions from the Langmuir Probes onboard CHAMP and three identical Swarm satellites. In particular, CHAMP measurements during the years 2004 and 2009, and Swarm observations during 2016 and 2017 have been considered in the 15°-wide latitudinal belt from 35°N to 50°N, and from 0° to 360° in longitude. CHAMP/Swarm in-situ Ne measurements have been then used to check and compare this new defined background with the one computed directly from IRI-2016 Ne output at satellite altitude. The distributions of the relative deviations between the two backgrounds, and of positive and negative anomalies (i.e., Ne variations from each background greater than 30%) with respect to the geomagnetic activity levels have been evaluated under each investigated condition, namely year/satellite, season, night-time or noon hours. Results of this comparison highlight a general overestimation of Ne from IRI during noon hours, while a better agreement between the two backgrounds is found during night-time. However, an underestimation of IRI with respect to Swarm-derived background is found for 2017 data. Finally, the analysis of 2004 plasma data suggests that the IRI-2016 model can be used as a background during periods characterized by high levels of geomagnetic activity. Due to the difficulties to construct a background for satellite data, the proposed method can be considered an useful tool for analyses of electron density variations at the heights of the satellites in Low Earth Orbits (LEO).