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The three Swarm satellites provide an optimum, low Earth orbit (LEO) and multi‐spacecraft platform, to explore for the first time the local correlation between field‐aligned currents (FACs), auroral electrojets, and magnetic perturbations at the Earth's surface. By combining Swarm and ground magnetic field data, one can investigate systematically the full correlation chain, whose final link controls the ground induced currents and related space weather effects. We introduce an integrated FAC product, the Sheet FAC (SFAC) index, as a convenient measure of the in‐situ FAC data, and explore the correlations SFAC‐AE, SFAC‐PEJ and SFAC‐dH, with AE the standard auroral electrojet index, PEJ the local, Swarm based, polar electrojet index, and dH the horizontal magnetic field perturbation at the Earth's surface. Given the good SFAC‐dH correlation, we also suggest an extension of SFAC to higher LEO satellites, which cannot observe any more the electrojet currents, but are fully capable to monitor SFAC. Plain Language Summary ‘Space weather’ resembles, to some extent, ordinary weather. Likewise, storms in space, termed ‘magnetic storms’, have common features with ordinary storms. Just like ordinary storms, magnetic storms can cause damage, and similar to ordinary weather, space weather needs to be monitored and, ideally, predicted. The SFAC index, introduced in the paper, is shown to be a potentially useful tool for such goals, able to capture local effects. This is essential for efficient monitoring. Moreover, the SFAC index can be extended to many satellites, which is important too. Just like for ordinary weather, space weather prediction requires measurements of key parameters that are used as input by specific models. The more and denser the measurements, the better the output, namely the prediction. Key Points The newly introduced SFAC index is shown to be robust and appropriate for space weather monitoring by low Earth orbit satellites SFAC appears to be able to capture local features related to magnetospheric dynamics, as driven, in particular, by bursty bulk flows While the introduction of SFAC takes advantage of Swarm features, the index can be extended to other low Earth orbit satellites

This paper presents a multi-parameter global statistical model of extreme horizontal geomagnetic field fluctuations (d B H /d t ), which are a useful input to models assessing the risk of geomagnetically induced currents in ground infrastructure. Generalised Pareto (GP) distributions were fitted to 1-min measurements of |d B H /d t | from 125 magnetometers (with an average of 28 years of data per site) and return levels (RL) predicted for return periods (RP) between 5 and 500 years. Analytical functions characterise the profiles of maximum-likelihood GP model parameters and the derived RLs as a function of corrected geomagnetic latitude, λ . A sharp peak in both the GP shape parameter and the RLs is observed at |λ| = 53° in both hemispheres, indicating a sharp equatorward limit of the auroral electrojet region. RLs also increase strongly in the dayside region poleward of the polar cusp (|λ| > 75°) for RPs > 100 years. We describe how the GP model may be further refined by modelling the probability of occurrences of |d B H /d t | exceeding the 99.97th percentile as a function of month, magnetic local time, and the direction of the field fluctuation, d B H , and demonstrate that these patterns of occurrence align closely to known patterns of auroral substorm onsets, ULF Pc5 wave activity, and (storm) sudden commencement impacts. Changes in the occurrence probability profiles with the interplanetary magnetic field (IMF) orientation reveal further details of the nature of the ionospheric currents driving extreme |d B H /d t | fluctuations, such as the changing location of the polar cusp and seasonal variations explained by the Russell-McPherron effect.

Abrupt variations of auroral electrojets can induce geomagnetically induced currents, and the ability to model and forecast them is a pressing goal of space weather research. We report an auroral electrojet spike event that is extreme in magnitude, explosive in nature, and global in spatial extent that occurred on 24 April 2023. The event serves as a fundamental test of our understanding of the response of the geospace system to solar wind dynamics. Our results illustrate new and important characteristics that are drastically different from existing knowledge. Most important findings include (a) the event was only of ∼5‐min duration and was limited to a narrow (2°–3°) band of diffuse aurora; (b) the longitudinal span covered the entire nightside sector, possibly extending to the dayside; (c) the trigger seems to be a transient solar wind dynamic pressure pulse. In comparison, substorms usually last 1–2 hr and span almost the entire latitudinal width of the auroral oval. Magnetic perturbation events (MPEs) span hundreds km in radius. Both substorms and MPEs are mainly driven by disturbances in the magnetotail. A possible explanation is that the pressure pulse compresses the magnetosphere and enhances diffuse precipitation of electrons and protons from the inner plasma sheet, which elevates the ionospheric conductivity and intensifies the auroral electrojet. Therefore, the event exhibits a potentially new type of geomagnetic disturbance and highlights a solar wind driver that is enormously influential in driving extreme space weather events. Plain Language Summary Auroral electrojets are horizontal electric currents that flow in the auroral ionosphere, and extreme auroral electrojet activities can induce geomagnetically induced currents that damage high‐voltage power transformers and increase steel corrosion of pipeline networks. Understanding what drives the extreme events is therefore a pressing goal of space weather research. We report an auroral electrojet spike event that is extreme in magnitude, explosive in nature, and global in spatial extent that occurred on 24 April 2023. The event serves as a fundamental test of our understanding of the response of the geospace system to solar wind dynamics. Most important findings include (a) the event was only of ∼5‐min duration and was limited to a narrow band of diffuse aurora; (b) the longitudinal span covered the entire nightside sector; (c) the trigger seems to be a transient solar wind dynamic pressure pulse. These features differ drastically from other widely known geomagnetic disturbances such as substorms or magnetic perturbation events, and signify a potentially new type of disturbance. A possible explanation is that the solar wind pressure pulse compresses the magnetosphere, enhances diffuse precipitation of particles into the ionosphere, and elevates the ionospheric conductivity. Key Points An abrupt and intense auroral electrojet enhancement occurred during the storm of 24 April 2023 This extreme event differs from typical geomagnetic disturbances in terms of magnitude, spatiotemporal extent, and physical driver The event was triggered by a solar wind pressure pulse, which enhanced diffuse auroral precipitation and ionospheric conductivity

The relationship between solar-wind conditions and substorm activity is modelled with an approach based on an echo state network. Substorms are a fundamental physical phenomenon in the magnetosphere–ionosphere system, but the deterministic prediction of substorm onset is very difficult because the physical processes that underlie substorm occurrences are complex. To model the relationship between substorm activity and solar-wind conditions, we treat substorm onset as a stochastic phenomenon and represent the stochastic occurrences of substorms with a non-stationary Poisson process. The occurrence rate of substorms is then described with an echo state network model. We apply this approach to two kinds of substorm onset proxies. One is a sequence of substorm onsets identified from auroral electrojet intensity, and the other is onset events identified from activity of Pi2 pulsations, which are irregular geomagnetic oscillations often associated with substorm onsets. We then analyse the response of substorm activity to solar-wind conditions by feeding synthetic solar-wind data into the echo state network. The results indicate that the effect of the solar-wind speed is important, especially for Pi2 substorms. A Pi2 pulsation can often occur even if the interplanetary magnetic field (IMF) is northward, while the activity of auroral electrojets is depressed during northward IMF conditions. We also observe spiky enhancements in the occurrence rate of substorms when the solar-wind density abruptly increases, which might suggest an external triggering due to a sudden impulse of solar-wind dynamic pressure. It seems that northward turning of the IMF also contributes to substorm occurrences, though the effect is likely to be minor.

Learning from successful applications of methods originating in statistical mechanics, complex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between normal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards. This review provides a systematic overview on existing nonlinear dynamical systems-based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems approaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlinear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales.

Interplanetary (IP) shocks are perturbations observed in the solar wind. IP shocks correlate well with solar activity, being more numerous during times of high sunspot numbers. Earth‐bound IP shocks cause many space weather effects that are promptly observed in geospace and on the ground. Such effects can pose considerable threats to human assets in space and on the ground, including satellites in the upper atmosphere and power infrastructure. Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. We predict shock counts to be around 275 ± 10, which is ∼47% higher than the shock occurrence in SC24 (187 ± 8), but still smaller than the shock occurrence in SC23 (343 ± 12). With the perspective of having more IP shocks on the horizon for SC25, we briefly discuss many opportunities in space weather research for the remainder years of SC25. The next decade or so will bring unprecedented opportunities for research and forecasting effects in the solar wind, magnetosphere, ionosphere, and on the ground. As a result, we predict SC25 will offer excellent opportunities for shock occurrences and data availability for conducting space weather research and forecasting.

The dynamics of the Earth's magnetosphere exhibits strongly fluctuating patterns as well as non-stationary and non-linear interactions, more pronounced during magnetospheric substorms and magnetic storms. This complex dynamics comprises both stochastic and deterministic features occurring at different time scales. Here we investigate the stochastic nature of the magnetospheric substorm dynamics by analysing the Markovian character of SuperMAG SME and SML geomagnetic indices. By performing the Chapman-Kolmogorov test, the SME/SML dynamics appears to satisfy the Markov condition at scales below 60 minutes. The Kramers-Moyal analysis instead highlights that a purely diffusive process is not representative of the magnetospheric dynamics, thus a model that includes both diffusion and Poisson-jump processes is used to reproduce the SME dynamical features at small scales. A discussion of the similarities and differences between this model and the SME properties is provided with a special emphasis on the metastability of the Earth's magnetospheric dynamics. Finally, the relevance of our results in the framework of Space Weather is also addressed.

Ultralight dark matter, such as kinetically mixed dark-photon dark matter (DPDM) or axionlike-particle dark matter (axion DM), can source an oscillating magnetic-field signal at Earth's surface. Previous work searched for this signal in a publicly available dataset of global magnetometer measurements maintained by the SuperMAG collaboration. This ``low-fidelity\" dataset reported measurements with a 1-minute time resolution, allowing the search to set leading direct constraints on DPDM and axion DM with Compton frequencies \\(f_DM1/(1\\,min)\\) [corresponding to masses \\(m_DM710^-17\\,eV\\)]. More recently, a dedicated experiment undertaken by the SNIPE Hunt collaboration has also searched for this same signal at higher frequencies \\(f_DM0.5\\,Hz\\) (or \\(m_DM210^-15\\,eV\\)). In this work, we search for this signal of ultralight DM in the SuperMAG ``high-fidelity\" dataset, which features a 1-second time resolution, allowing us to probe the gap in parameter space between the low-fidelity dataset and the SNIPE Hunt experiment. The high-fidelity dataset exhibits lower geomagnetic noise than the low-fidelity dataset and features more data than the SNIPE Hunt experiment, making it a powerful probe of ultralight DM. Our search finds no robust DPDM or axion DM candidates. We set constraints on DPDM and axion DM parameter space for \\(10^-3\\,Hz f_DM0.98\\,Hz\\) (or \\(410^-18\\,eV m_DM410^-15\\,eV\\)). Our results are the leading direct constraints on both DPDM and axion DM in this mass range, and our DPDM constraint surpasses the leading astrophysical constraint in a narrow range around \\(m_A'210^-15\\,eV\\).

Ultralight dark matter, such as kinetically mixed dark-photon dark matter (DPDM) or axionlike-particle dark matter (axion DM), can source an oscillating magnetic-field signal at Earth's surface. Previous work searched for this signal in a publicly available dataset of global magnetometer measurements maintained by the SuperMAG collaboration. This \"low-fidelity\" dataset reported measurements with a 1-minute time resolution, allowing the search to set leading direct constraints on DPDM and axion DM with Compton frequencies \\(f_\\mathrm{DM}\\leq1/(1\\,\\mathrm{min})\\) [corresponding to masses \\(m_\\mathrm{DM}\\leq7\\times10^{-17}\\,\\mathrm{eV}\\)]. More recently, a dedicated experiment undertaken by the SNIPE Hunt collaboration has also searched for this same signal at higher frequencies \\(f_\\mathrm{DM}\\geq0.5\\,\\mathrm{Hz}\\) (or \\(m_\\mathrm{DM}\\geq2\\times10^{-15}\\,\\mathrm{eV}\\)). In this work, we search for this signal of ultralight DM in the SuperMAG \"high-fidelity\" dataset, which features a 1-second time resolution, allowing us to probe the gap in parameter space between the low-fidelity dataset and the SNIPE Hunt experiment. The high-fidelity dataset exhibits lower geomagnetic noise than the low-fidelity dataset and features more data than the SNIPE Hunt experiment, making it a powerful probe of ultralight DM. Our search finds no robust DPDM or axion DM candidates. We set constraints on DPDM and axion DM parameter space for \\(10^{-3}\\,\\mathrm{Hz}\\leq f_\\mathrm{DM}\\leq0.98\\,\\mathrm{Hz}\\) (or \\(4\\times10^{-18}\\,\\mathrm{eV}\\leq m_\\mathrm{DM}\\leq4\\times10^{-15}\\,\\mathrm{eV}\\)). Our results are the leading direct constraints on both DPDM and axion DM in this mass range, and our DPDM constraint surpasses the leading astrophysical constraint in a narrow range around \\(m_{A'}\\approx2\\times10^{-15}\\,\\mathrm{eV}\\).

Geomagnetically induced currents or GICs are signatures of a rapidly time-varying magnetic field (dB/dt) and occur mainly during substorms and storms. When, where and why exactly GICs may occur, is still vague. Thus, we investigated storms for the last 40 years (from 1980 with a storm-list created by W.T. Walach) and analyzed the negative and positive dB/dt spikes (threshold of 500 nT/min) in the north and east component using a worldwide coverage (SuperMAG). Our analysis confirmed the existence of two dB/dt spikes \"hotspots\" located in the pre-midnight and in the morning MLT sector, independently of the geographic location of the stations. The associated physical ionospheric phenomena are most probably substorm current wedge (SCW) onsets and westward travelling surges (WTS) in the evening sector, and wave- or vortex-like current flows in Omega bands in the morning sector. Additionally, we observed a spatio-temporal evolution of the negative northern dB/dt spikes. The spikes initially occur in the pre-midnight sector, and then develop in time towards the morning sector. This spatio-temporal sequence is correlated with bursts in the AE index, and can be repeated several times throughout a storm. Finally, we investigated the intensity (Dst and AE) of the storms compared to the number of dB/dt spikes, but we did not find any correlation. This result implies that moderate storm with many spikes can be as (or more) dangerous for ground-based infrastructures than a major storm with fewer dB/dt spikes. Our findings may help to improve the GICs forecast to accurately predict dB/dt spikes.