Sigiava Aminalragia-Giamini

The geomagnetic superstorm in May 2024 represents the most extreme space weather event over the past two decades, offering a unique opportunity to investigate radiation belt electron dynamics under exceptionally strong solar wind driving conditions. Observations from the Arase satellite show that relativistic electron fluxes dropped by several orders of magnitude during the storm main phase. Although magnetopause shadowing and wave‐driven losses are established mechanisms, the response of radiation belt electrons to superstorm‐level solar wind driving remains poorly constrained. Using the Versatile Electron Radiation Belt model, we present the first physics‐based simulation of the May 2024 electron dropout. Utilizing multi‐satellite and ground‐based observations, we show that the decades‐long, widely adopted Kp‐driven radial diffusion parameterization fails to represent radial transport under superstorm conditions, substantially misrepresenting both the timing and magnitude of enhanced diffusion relative to observed ultra‐low‐frequency wave activity. Accurate modeling of the observed extreme dropout requires precise specification of the onset of enhanced radial diffusion, which should coincide with the nearly simultaneous storm‐time magnetopause compression. These coupled processes drive the dramatic depletion, followed by scattering from whistler‐mode plasma waves.

The geomagnetic storm in May 2024 represents the most extreme space weather event over the past twenty years, providing a unique opportunity to investigate energetic particle dynamics under exceptionally strong solar wind driving conditions. Among the various particle populations affected by such extreme storms, outer radiation belt electrons are of particular interest because they respond rapidly to storm-time magnetospheric reconfigurations and pose significant hazards to satellites operating in near-Earth space.Observations from the Arase satellite reveal that MeV radiation belt electron fluxes dropped by several orders of magnitude during the main phase of the May 2024 superstorm. This extreme dropout coincided with intense magnetopause compression to a minimum standoff distance of L~3.7, estimated using the Space Weather Modeling Framework, and enhanced ultra-low-frequency (ULF) Pc5 wave activity derived from SuperMAG. To investigate the physical mechanisms controlling this extreme electron loss, we performed simulations using the Versatile near‐Earth environment of Radiations Belts and ring current (VERB) model, systematically examining the roles of magnetopause shadowing, radial diffusion, and local wave-driven scattering.We find that commonly used empirical radial diffusion models, parameterized by Kp, fail to reproduce the observed electron flux profiles during this event. Instead, accurately capturing the extreme electron dropout requires that enhanced radial diffusion be properly timed relative to magnetopause compression and storm-time wave activity. In addition, stronger plasmaspheric hiss scattering is necessary to reproduce losses at lower L*. These results demonstrate that extreme radiation belt electron dropout during superstorms is controlled by the coupled timing of magnetopause compression, radial diffusion, and local scattering processes, emphasizing the importance of physically timed transport and loss representations in extreme storm modeling.

Specification models for radiation belts are essential for the design of radiation resistant, long-lasting spacecraft. Using the available in-situ measurements allows these models to virtually describe the average space radiation environment. However, their dependence on observations will make them suffer from data gaps which may lead to poor assessment of degradation risks. To counter this problem, one can have access to continuous descriptions of the radiation belt dynamics on long time periods through climate reanalysis. This operation consists in the assimilation of historical measurements in radiation belt simulations over solar-cycle-long periods, allowing for a physics-based filling of data gaps and the re-calibration of the radiation belt codes on long simulations. The obtained database of continuous historical distributions may serve later in the elaboration of space climatology models and a new generation of physics-based specification models. Yet, the success of climate reanalysis operation is strongly dependent on the numerical stability of the data assimilation procedure that can be deteriorated in the low earth orbit region for instance. Hence, we present in this paper, the climate reanalysis of the trapped electron dynamics using the Salammbô code for the 2014–2022 period, with promising results when compared to standard specification models. We also present the methodology followed to stabilize the assimilation in the low earth orbit.

Radial diffusion in planetary radiation belts is a dominant transport mechanism resulting in the energization and losses of chargedparticles by large-scale electromagnetic fluctuations. In this work we exploit the extensive radial diffusion coefficients (DLL) database createdin the framework of the Horizon 2020 SafeSpace project, which spans 9 years of hourly DLL coefficients, to investigate the spatiotemporaldistributions of the coefficients. Our results indicate that the radial distribution of the magnetic and electric component of theDLL, as well as their sum, the total DLL, can be well described by a power law function of L* in the [4.3–7.7] range. We show that the L*-dependent spectral index varies significantly and is far from constant as assumed and implemented in many semi-empirical models. Weexamine the quasi-periodic behavior of the radial profiles of the DLL throughout most of the 24th Solar cycle, which the data cover, andfind an approximately 420 days dominant periodicity. This periodic behavior is linked (in terms of cross-wavelet analysis) with solaractivity, nevertheless, its origin remains unclear. The uncovered features are important for understanding DLL behavior and driversas well as for current and future modelling efforts.

Radial diffusion, driven by Ultra-Low Frequency (ULF) waves in the Pc4–5 band (2–25 mHz), has been established as one of the most important mechanisms that influences the dynamics of electrons in a quite broad energy range, as it can lead to both energization and loss of relativistic electrons in the outer Van Allen radiation belt. The same has been observed in other planetary magnetospheres. The dependence of ULF wave power spectral density and radial diffusion coefficients (DLL) on solar wind parameters has been investigated by some studies, but their relationship on the various solar and interplanetary drivers is far from well-studied and understood. In this study, we use the “SafeSpace” database (https://synergasia.uoa.gr/modules/document/?course=PHYS120), which contains radial diffusion coefficients and ULF wave power spectral density, and was created using magnetic and electric field measurements from the THEMIS satellites in the 2011–2019 time-period. We conduct an extensive statistical analysis of DLL in order to investigate the relationships between the magnetic and electric components as well as their dependence on interplanetary drivers (i.e. High Speed Streams and Interplanetary Coronal Mass Ejections). Our results reveal an energy dependence of the radial diffusion coefficients as well as significant variations of the DLL spectral profiles as a function of Roederer’s L*. Our findings highlight statistical, as well as physical, characteristics and aspects of DLL which are not included in most semi-empirical models typically used in radiation belt simulations, thus potentially introducing significant biases in the estimation of the outer belt relativistic electron environment. Further discussion will be devoted to the uncertainties of such efforts as well as the possible contribution of magnetosheath processes (e.g., jets and electron injections from the foreshock) and solar wind mechanisms (periodic density structures).The work leading to this paper has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101081772 for the FARBES (Forecast of Actionable Radiation Belt Scenarios) project.

Context. In recent years, mesoscales have gained scientific interest because they have been determined to be important in a broad range of phenomena throughout heliophysics. The solar wind mesoscale structures include periodic density structures (PDSs), which are quasi-periodic increases in the density of the solar wind that range from a few minutes to a few hours. These structures have been extensively observed in remote-sensing observations of the solar corona and in in situ observations out to 1 AU, where they manifest as radial length scales greater than or equal to the size of the Earth’s dayside magnetosphere, that is, from tens to hundreds of Earth radii (R_E). While the precise mechanisms that form PDSs are still debated, recent studies confirmed that most PDSs are of solar origin and do not form through dynamics during their propagation in the interplanetary space. Aims. We further investigate the origin of PDSs by exploring the thermodynamic signature of these structures. To do this, we estimate the values of the effective polytropic index (Y) and the entropy of protons, which in turn are compared with the corresponding values found for the solar wind. Methods. We used an extensive list of PDS events spanning more than two solar cycles of Wind measurements (the entire Wind dataset from 1995 to 2022) to investigate the thermodynamic signatures of PDSs. With the use of wavelet methods, we classified these PDSs as coherent or incoherent, based on the shared periodic behavior between proton density and alpha-to-proton ratio, and we derive the proton polytropic index. Results. Our results indicate that the coherent PDSs exhibit lower Y values (Ῡ≈1.54) on average and a higher entropy than the values in the entire Wind dataset (Ῡ≈1.79), but also exhibit similarities with the magnetic cloud of an interplanetary coronal mass ejection. In contrast, incoherent PDSs exhibit the same Y values as those of the entire Wind dataset.

The H2020 SafeSpace project aims at the implementation of a space weather safety prototype, in particular to predict the deep charging hazard. The proposed service is built on a Sun‐to‐Earth chain of physical codes that propagates physical information and uncertainties in order to model the outer radiation belt dynamics. In this paper, we present the inner magnetosphere section of the SafeSpace pipeline that relies on solar wind driven and hourly updated models that describe the trapped electron environment (VLF waves, cold plasma and seed population densities), as well as the physical processes to which the trapped electrons are subjected to, such as radial diffusion and wave particle interactions. Then, this physical configuration is poured into the Salammbô‐EnKF model, a data assimilation radiation belt model which provides a global forecast of the densities across the radiation belts. We have compared the forecasting performance of this new modeling pipeline to a reference model during the St. Patrick's Day storm in 2015. We show that the new SafeSpace implementation shows closer results to the observations in addition to a better forecast within the prediction horizon.

During the second half of 2019, the Earth’s magnetosphere was impacted by a sequence of Corotating Interaction Regions (CIRs) during four consecutive solar rotations. Based on the solar wind properties, the CIRs can be divided in four groups, with the 3rd group, which arrived on August-September 2019, resulting in significant multi-MeV electron enhancements, up to ultra-relativistic energies of 9.9 MeV.Each CIR group has a different effect on the outer radiation belt electron populations; we investigate them by exploiting combined measurements from the Van Allen Probes, THEMIS, and Arase satellites. We produce Phase Space Density (PSD) radial profiles and inspect their dependence on the values of the first and second adiabatic invariants (μ,K), ranging from seed to ultra-relativistic electrons and from near-equatorial to off equatorial mirroring populations, respectively.Focusing on the 3rd CIR group, and in order to assess the relative contribution of radial diffusion and gyro-resonant acceleration, we perform numerical simulations of the radiation belt environment, combining several relevant models: EMERALD (NKUA), GEO model (NKUA), Salammbô (ONERA), VLF model (IAP), Plasmaspheric model (BIRA-IASB), FARWEST (ONERA). We further compare the temporal evolution of the simulated electron PSD with the above observations.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 for the SafeSpace project.

Radial diffusion is one of the dominant physical mechanisms driving acceleration and loss of electrons in the outer radiation belt. Therefore, the accurate estimation of radial diffusion coefficients (D_LL) is crucial for detailed radiation belt modeling. In recent years several semi‐empirical (SE) models have been developed for the estimation of radial diffusion coefficients which predominantly rely on parameterizations of the Kp index. However, several studies have suggested that the estimations derived from such models can have large deviations from actual (measurement derived) D_LL values. In this work we have used the extensive D_LL database created in the framework of the Horizon 2020 SafeSpace project which spans 9 years of hourly D_LL calculations to develop a model which uses solely solar wind parameters for the derivation of D_LL values. The Electric and MagnEtic RAdiaL Diffusion (EMERALD) model is able to derive simultaneously the magnetic and electric components ( and , respectively) of the radial diffusion coefficient, and furthermore, provide realistic confidence levels on their estimation, which allows the transition from a deterministic paradigm to a robust probabilistic one. Evaluations on the performance of the EMERALD model are shown by comparing its outputs to the D_LL data, and examining the reproduction of various D_LL characteristics. Finally, comparisons with widely used SE models are shown and discussed.