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Powerful lightning strikes generate broadband electromagnetic signals. At Extremely Low Frequencies (ELF), the signal partly leaks into the ionosphere and produces whistlers that can be detected by satellites. Indeed, the satellites of the European Space Agency (ESA) Swarm Earth Explorer mission can detect those signals during 250 Hz burst‐mode acquisition campaigns of their Absolute Scalar Magnetometers (ASM). The dispersion of these whistlers depends on their propagation path and the distribution of ionization in the ionosphere crossed along that path. In this paper, we introduce a technique to derive a new measure of ionosphere electron content, the Total square‐Root Electron Content (TREC), using the arrival times of two frequencies of the whistler signal. We validate this approach by using data from ionosondes and from in situ measurements of the electron density at Swarm location. This technique brings new opportunities for sounding the ionosphere in regions poorly observed by other techniques. Plain Language Summary A lightning strike generates an electromagnetic impulse that propagates within Earth's atmosphere and eventually leaks out into the ionosphere. As it propagates through the ionosphere toward low‐Earth orbiting (LEO) satellites, it gets converted into a so‐called whistler, with high frequencies arriving earlier than low frequencies. This frequency dispersion depends on the state of the ionosphere. Here, we analyse such whistler waves detected by magnetometers onboard the European Space Agency Swarm satellites to recover information about the state of the ionosphere below the satellites. We first introduce a new metric, the Total Root Electron Content (TREC), which quantifies the cumulative value of the square root of electron density along the path of the whistler. We next propose a method to recover the TREC from the analysis of the whistler dispersion. We finally validate this method by using independently derived ionospheric electron density profiles to infer expected TREC values. Our results show that whistlers detected by LEO satellites can be used to locally improve the widely used empirical International Reference Ionosphere model. Such whistler inferred TREC values could be used to sound the ionosphere above places difficult to sample with conventional measuring techniques, and help better model and understand the highly dynamic ionosphere. Key Points Total square‐Root Electron Content (TREC) is a new measure of the ionospheric electron content for electromagnetic signals in the ELF band A method to retrieve TREC from fractional‐hop whistlers in the ELF detected by the ESA Swarm mission is proposed The method is validated using TREC computed with independently constrained electron density profiles close to the Swarm whistler locations

We report thermospheric exospheric temperature and composition responses on the 15 January 2022 Tonga volcanic eruption. The temperature and composition profiles are inversed from three ionosonde (MHJ45, EG931, FF051) observed electron density profiles (∼150–200 km) using our new method (Li, Ren, et al., 2023, https://doi.org/10.1029/2022ja030988). The retrieved exospheric temperatures all showed obvious eruption‐induced perturbations, with maximum disturbance magnitude of ∼200 K at MHJ45 and ∼100 K at EG931 and FF051. The temperature variations were related to eruption‐excited thermospheric waves and their propagation with different speeds. While column ∑O/N2 had no evident changes similar to temperatures, which were basically consistent with GOLD observations. In comparison, higher thermospheric O/N2 has larger eruption‐related changes, maybe due to the exponential increase of thermospheric wave amplitudes with height. The application of our inversion method, combined with continuous observations and global coverage of ionosonde data, provide a possibility to further investigate thermospheric responses to different geophysical conditions. Plain Language Summary Extreme volcanic eruptions and resulted tsunami at 04:14:45 UT on 15 January 2022 generated a series of atmospheric waves, which can propagate out globally and up into the thermosphere. The ionosphere responses on this eruption, relative to thermosphere, have been reported a lot due to the large amounts of ionospheric observations. Here, we used the new method proposed by Li, Ren, et al. (2023), https://doi.org/10.1029/2022ja030988 to inverse daytime thermospheric parameters (neutral temperature and composition) from ionospheric electron density profiles (∼150–200 km). We selected ionosonde data at three stations (MHJ45, EG931, FF051) to verify the thermospheric responses during this eruption. The retrieved temperature at three stations showed the obvious eruption‐induced perturbations, but ∑O/N2 not, which were basically consistent with GOLD observations. However, O/N2 in higher thermosphere had larger eruption‐related changes. The comparison with GOLD observations and observed F2 layer peak electron densities verified the credibility of our inversion method again. Thus, the application of the method to the continuous and high‐covering ionosonde data provides a possibility to further investigate thermospheric responses to different geophysical conditions. Key Points Inversed exospheric temperatures showed obvious eruption‐induced perturbations on the 15 January 2022 Tonga eruption ∑O/N2 had no evident eruption‐induced changes similar to the temperature, neither in our inversion data nor in GOLD observations Ionosonde can expand the understanding of thermospheric responses to different geophysical conditions by our inversion method

A new theory for the study of the reactivity in Organic Chemistry, named Molecular Electron Density Theory (MEDT), is proposed herein. MEDT is based on the idea that while the electron density distribution at the ground state is responsible for physical and chemical molecular properties, as proposed by the Density Functional Theory (DFT), the capability for changes in electron density is responsible for molecular reactivity. Within MEDT, the reactivity in Organic Chemistry is studied through a rigorous quantum chemical analysis of the changes of the electron density as well as the energies associated with these changes along the reaction path in order to understand experimental outcomes. Studies performed using MEDT allow establishing a modern rationalisation and to gain insight into molecular mechanisms and reactivity in Organic Chemistry.

After the arrival of Akatsuki spacecraft of Japan Aerospace Exploration Agency at Venus in December 2015, the radio occultation experiment, termed RS (Radio Science), obtained 19 vertical profiles of the Venusian atmosphere by April 2017. An onboard ultra-stable oscillator is used to generate stable X-band downlink signals needed for the experiment. The quantities to be retrieved are the atmospheric pressure, the temperature, the sulfuric acid vapor mixing ratio, and the electron density. Temperature profiles were successfully obtained down to ~ 38 km altitude and show distinct atmospheric structures depending on the altitude. The overall structure is close to the previous observations, suggesting a remarkable stability of the thermal structure. Local time-dependent features are seen within and above the clouds, which is located around 48–70 km altitude. The H 2 SO 4 vapor density roughly follows the saturation curve at cloud heights, suggesting equilibrium with cloud particles. The ionospheric electron density profiles are also successfully retrieved, showing distinct local time dependence. Akatsuki RS mainly probes the low and middle latitude regions thanks to the near-equatorial orbit in contrast to the previous radio occultation experiments using polar orbiters. Studies based on combined analyses of RS and optical imaging data are ongoing. Graphical abstract .

Topside ionospheric electron density (Ne) and its control on the variabilities in nocturnal ionospheric irregularities is examined globally using electron density measurements from COSMIC‐2 and Swarm satellite, along with the Swarm satellite‐based Ionospheric Plasma Irregularity (IPIR) index for low and high solar activity (LSA and HSA) periods of 2019–2020 and 2023–2024 respectively. Seasonal and solar cycle variations of topside Ne and IPIR indices are examined, highlighting their direct relationship. The study also reveals the connection between the F region peak altitude at the equator and the peak electron density (NmF2) at the crest region. The longitudinal pattern of topside Ne is controlled by the Equatorial Ionization Anomaly (EIA), and this pattern is similarly reflected in topside irregularities. Three or four peaked structures are observed in the postsunset longitudinal pattern of topside irregularities and electron density during the March–April (MA) and June–July (JJ) months, while 2 peaked structures manifest in December–January (DJ) months for HSA and LSA. These patterns are attributed to the combined effects of topside Ne associated modulation of F region dynamo, magnetic meridian alignment with sunset terminator, and lower atmospheric tides. The relationship between the altitudinal extent of irregularities with topside Ne and Ne gradients at the geomagnetic equator in Trivandrum shows a direct linear dependence on a day‐to‐day basis. The results suggest that the background topside Ne has a significant effect on the strength and altitudinal extent of ionospheric irregularities on a day‐to‐day level.

Atmospheric refraction often influences the localization accuracy of ground-based radar for detecting space targets. Traditional methods generally utilize the measured troposphere and ionosphere data from the local station for atmospheric refraction correction and thus neglect the influence of atmospheric horizontal inhomogeneity. However, in practice, a horizontally inhomogeneous ionosphere often causes considerable residual errors in the measured range and elevation angle after refraction correction, especially for targets with low elevation angles. The ionospheric electron density profile along the wave propagation path is significantly different from that in the vertical direction of the local station, which further brings about challenges in the modeling and correction of atmospheric refraction errors. To address the above challenge, the effect of a horizontally inhomogeneous ionosphere on the range and elevation angle measured by ground-based radar is analyzed, and a geographic division modeling strategy for the ionospheric electron density along the propagation path for atmospheric refraction correction is proposed in this paper. The simulation results show that the oblique electron density distribution obtained from the proposed model agrees well with the results calculated by the International Reference Ionosphere (IRI) model, and the proposed methodology effectively suppresses residual errors in radar atmospheric refraction correction in the low-elevation detection case.

Accurate estimates of the ionospheric electron density are essential for various space-weather applications but are challenging at high latitudes due to strong spatial and temporal variability driven by auroral precipitation and complex ionospheric convection. This study presents an assimilative empirical model designed to improve regional electron-density estimates in Northern Scandinavia. The model uses ionogram images, the local magnetic field, the auroral electrojet, the ring current and solar-activity indices as inputs. These inputs are fused by a multimodal neural network and trained with incoherent-scatter-radar (ISR) observations of electron density profiles as the target. The model remains functional with only a subset of input, with modest accuracy degradation. Comparative analysis demonstrates that our neural-network-based assimilative model outperforms the ARTIST 4.5 ionogram scaler and the state-of-the-art E-CHAIM model, especially during auroral activity. Overall, our model achieves an R2 score of 0.74 on an independent test dataset, whereas ARTIST 4.5 and E-CHAIM obtain R2 values of −0.08 and 0.34, respectively. These results indicate that the model can provide reliable, continuous electron-density estimates at high latitudes, even under auroral conditions. This methodology can be extended to develop empirical ionospheric models for other regions with historical ISR data and to invert ionograms to electron-density profiles when ISR observations are unavailable.

Culverwell et al. (2023, https://doi.org/10.1029/2023SW003572) described a new one‐dimensional variational (1D‐Var) retrieval approach for ionospheric GNSS radio occultation (GNSS‐RO) measurements. The approach maps a one‐dimensional ionospheric electron density profile, modeled with multiple “Vary‐Chap” layers, to bending angle space. This paper improves the computational performance of the 1D‐Var retrieval using an improved background model and validates the approach by comparing with the COSMIC‐2 profile retrievals, based on an Abel Transform inversion, and co‐located (within 200 km) ionosonde observations using all suitable data from 2020. A three or four layer Vary‐Chap in the 1D‐Var retrieval shows improved performance compared to COSMIC‐2 retrievals in terms of percentage error for the F2 peak parameters (NmF2 and hmF2). Furthermore, skill in retrieval (compared to COSMIC‐2 profiles) throughout the bottomside (∼90–300 km) has been demonstrated. With a single Vary‐Chap layer the performance is similar, but this improves by approximately 40% when using four‐layers.

The threefold daytime electron density increases, along with strong poleward meridional winds exceeding 200 m/s were captured by Sanya Incoherent Scatter Radar (SYISR) during the geomagnetic storm of 12 November 2025. The great ionospheric enhancements were extending to mid‐latitudes over 40° observed by total electron content (TEC) from Beidou geostationary satellites. Thermosphere‐Ionosphere Electrodynamics Global Circulation Model (TIEGCM) reproduced the observed features during this storm. In particular, the traveling atmospheric disturbances (TADs) with a poleward phase speed of ∼710 m/s were present during the simulated TEC enhancements. Analysis of the O+ continuity equation revealed that the great ionospheric increases were dominated by sharp shear in the poleward meridional winds associated with TADs. Moreover, meridional wind vertical shear was the primary controlling factor, with horizontal shear acting as a secondary contributor. These findings demonstrated that strong meridional wind shear drives the accumulation of ionospheric electron density, regardless of the wind direction.

Impacts of solar flare vary at different parts of the lower ionosphere depending on it’s proximity to the direct exposure of incoming solar radiation. The quantitative analysis of this phenomena can be attributed to ‘solar zenith angle (χ(t))’ profile over ionosphere. We numerically solve the ‘electron continuity equation’ to obtain the lower ionospheric electron density profile (Ne(t)). The electron production rate (q(t)) is governed by the (i) X-ray profile (ϕ(t)) of the flare, (ii) χ(t)-values during the flare occurrence etc. For analyzing the X-ray profile during flares, we use the GOES-15 satellite observations. Since we’re working on electron continuity equation based simplified ionospheric model, we confined our analysis for comparatively stable mid-latitude ionosphere only. We choose three flares each from C, M and X-classes for Ne(t)-profile computation. We observe that temporal Ne(t)-profiles differ when computed for lower ionosphere over different discrete latitudes. Further, we compute the spatial Ne(t)-profile across mid-latitude at the time when ϕ(t)=ϕmax. Now we assume that, these flares repeat themselves every day of a year (DoY) at the same time of a day and we compute Ne(t)-profiles for each day. We found a seasonal effect on Ne(t)-profile due to solar flare. Further, we investigate the response time delay (Δt) of the lower ionosphere, which is the time difference between incidence of X-ray and the respective change in Ne(t)-profiles during solar flares. Strong seasonal effects on Ne(t)-profile and Δt are the unique results of this work.