Orals: Mon, 4 May, 14:00–15:45 | Room 0.94/95
Predicting the intrinsic structure and kinematics of coronal mass ejections (CMEs) in a reliable and timely manner remains one of the central goals of space weather forecasting agencies and research efforts. Specifically, the most prominent properties of interest include whether a CME will impact a given target (i.e., the hit/miss problem), when a CME will arrive at that target (i.e., the arrival time problem), and a CME’s internal magnetic structure upon arrival (i.e., the Bz problem). However, significant challenges still prevent a full characterisation of CMEs from their solar origin through their interplanetary propagation, and thus limit our ability to accurately predict their space weather effects. These include difficulties in determining a CME’s pre-eruptive configuration, its early evolution in the corona, and its propagation in a structured and dynamic solar wind. Furthermore, beyond the traditional focus on modelling and predicting CME impacts at Earth, both the research and operational communities have begun to extend their efforts towards space weather forecasting at other locations in the solar system relevant to future human exploration, particularly Mars.
In this presentation, we will first provide an overview of the current status of CME predictions in interplanetary space and the primary issues that are necessary to overcome to improve real-time forecasts. We will review existing operational pipelines as well as more innovative approaches currently employed or under development within the research community. Finally, we will reflect on potential pathways towards improved CME prediction capabilities, considering advances in both modelling and forecasting methodologies as well as the role of future spacecraft observations that are expected to provide better constraints for existing prediction pipelines.
How to cite: Palmerio, E.: Space Weather Predictions of Coronal Mass Ejections: Current Status and Paths for Improvements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7368, https://doi.org/10.5194/egusphere-egu26-7368, 2026.
We present the Solar Wind Scoreboard, which is hosted by NASA’s Community Coordinated Modeling Center (CCMC) and developed with the community as part of the COSPAR ISWAT initiative. The Solar Wind Scoreboard will serve the space weather and science community as a hub for real-time solar wind predictions at Earth, Mars, and other locations of interest. It will allow users to view the ensemble of community-contributed models and compare their performance during extreme space weather events. Our overarching objective is to build an open platform that allows us to identify science models that show potential to improve operational services. In this presentation, we will share our progress from the COSPAR ISWAT Workshop in Cape Canaveral, FL, USA, focusing on the open information architecture, including metadata standards, automated prediction submissions, and front-end development. Additionally, we will discuss how the Solar Wind Scoreboard integrates with existing CCMC Scoreboards and feeds into the new Geospace Scoreboard. We will share lessons learned from running models like AWSoM (University of Michigan) and ICARUS (KU Leuven) in real-time, and how we integrate their results into the Scoreboard. Finally, we will outline future plans and how we envision broader community engagement in line with open science principles.
How to cite: Reiss, M., Mays, L., Kuznetsova, M., Perri, B., Baratashvili, T., Henley, E., Sokolov, I., and Koban, G.: The Solar Wind Scoreboard hosted by NASA’s CCMC, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21079, https://doi.org/10.5194/egusphere-egu26-21079, 2026.
The International Sunspot Number (SN V2.0) is one of the longest and most detailed available series in astrophysics and its accuracy and stability is important for a large variety of scientific domains, not the least of which is the evolution of the Earth Climate.
Since its recalibration and release in 2015, SN V2.0 has been the subject of sustained scrutiny within the scientific community yet no community-wide audit has covered the first full decade of that recalibration through the rise of Solar Cycle 25. A systematic assessment of the long-term stability of SN V2.0 is thus in order. In parallel, the American Sunspot Number, which has been computed continuously since the mid-20th century, experienced documented inconsistencies in the 1990s, as highlighted in previous studies (Schaefer, 1997). However, a comprehensive evaluation of its long-term behavior in the subsequent decades is still lacking.
In this work, we analyze the temporal stability of SN V2.0 over multi-decadal timescales. We compare SILSO SN V2.0 with AAVSO Ra, and independent proxies such as Sunspot areas, F10.7, Nobeyama microwave fluxes, Mg II, ISGI aa, and SDO/HMI unsigned field to diagnose the long-term behavior of both indices. We examine their mutual consistency, sensitivity to calibration changes, and suitability for long-term comparative studies. This analysis allows us to assess the relative robustness of each index, identify potential residual biases, and evaluate their reliability for studies of long-term solar variability. We conclude by discussing implications for future sunspot number reconstructions and by outlining perspectives for maintaining stable, homogeneous solar activity indices over extended timescales.
How to cite: Chandrashekhar, K., Lefevre, L., and Riggs, J.: Sunspot Number V2.0 Through Solar Cycle 25: A Long-term Multi-Proxy Stability Analysis., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19117, https://doi.org/10.5194/egusphere-egu26-19117, 2026.
The overall level of activity of the solar cycle, as seen in the sunspot number (SSN) record, paces both the amplitude and occurrence rates of extreme space weather events [1] and the state of the ionosphere [2]. Predictions of future solar activity levels can be critical to assess system resilience and for planning. For example, under-prediction of current cycle 25 led to under-estimation of drag in LEO, with significant impact on satellite operations [3,4]. SSN predictions on solar cycle timescales are however challenging as no two past cycles have the same amplitude or duration. One method is that of precursors, that is, the upcoming cycle strength is found to correlate with properties of the preceding cycle [5]. The Hilbert transform of 13 month smoothed SSN since 1749 is used to construct a uniform clock for the Schwabe solar cycle which establishes a clear switch on and off of geomagnetic activity seen at earth [1] and which correlates with the morphology of the solar cycle [6]. Timings from the clock can be mapped back to the observed SSN time-series and used to hindcast each cycle SSN maximum from the properties of its preceding cycle. The last 25 solar cycles are hindcasted with good fidelity by this method. Linear correlation between the cycle maximum and properties of the preceding cycle identified from the solar cycle clock has coefficient of determination exceeding 0.7 and Pearson correlation coefficient exceeding 0.8. This new method is used to predict the maximum of upcoming solar cycle 26.
[1] S. C. Chapman, S. W. McIntosh, R. J. Leamon, N. W. Watkins (2020) Quantifying the solar cycle modulation of extreme space weather, Geophys. Res. Lett. doi:10.1029/2020GL087795
[2] M. A. Cafolla, S. C. Chapman, N. W. Watkins, X. Meng, O. P. Verkhoglyadova (2025) Dynamics of TEC High Density Regions seen in JPL GIMs: Variations with Latitude, Season and Geomagnetic Activity, Space Weather doi:10.1029/2024SW004307
[3] W. S. Shambaugh (2024) Doing battle with the sun: lessons from LEO and operating a satellite constellation in the elevated atmospheric drag environment of solar cycle 25, Proceedings, The 4S Symposium 2024. https://arxiv.org/abs/2406.08342
[4] X. Wang et al., (2025) Premature Reentry of the Binar CubeSats due to underestimation of solar and geomagnetic activities and its implication for importance of medium- and long-term space weather forecasts, Space Weather doi:10.1029/2025SW004619
[5] D. H. Hathaway (2015) The solar cycle, Living Rev. Solar Phys. 12, 4 doi:10.1007/lrsp-2015-4
[6] S. C. Chapman, T. Dudok de Wit (2024) A solar cycle clock for extreme space weather. Scientific Reports doi:10.1038/s41598-024-58960-5
How to cite: Chapman, S.: Sunspot number solar cycle clock based prediction of cycle 26 maximum, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2810, https://doi.org/10.5194/egusphere-egu26-2810, 2026.
Forecast systems and predictions of hazardous Solar Energetic Particle (SEP) events are needed to support space missions, as they can have a major impact on technology and humans. Especially in view of future plans for human exploration of Mars, a radiation protection strategy needs to be implemented with the goal of reliably providing advance warning of sudden radiation hazards.
The Relativistic Electron Alert System for Exploration (REleASE; Posner, 2007) utilises the close correlation between near-relativistic electrons and the slower, but more hazardous, protons to provide, on average, one hour of advance warning of particle events at the location where the measurements are taken. Originally, REleASE used real-time data from SOHO/EPHIN and later ACE/EPAM (HESPERIA/REleASE) to issue short-term warnings before a significant flux increase of ~20-50 MeV protons near Earth at the L1 point. More recently, the method was adapted to work with the HET and SEPT instruments onboard STEREO-A, and an operational STEREO/REleASE system was created.
With two REleASE systems now operational, we have the possibility to directly compare forecasts from different points in the heliosphere. Human explorers following Hohmann trajectories to and from Mars will be up to 22° away in longitudinal magnetic connection distance from the alert system. We used the 2022-2025 passage of STEREO-A by Earth to test whether remote REleASE forecasts can provide timely and sufficiently accurate information for the location of another spacecraft.
How to cite: Dröge, H., Heber, B., Malandraki, O., Karavolos, M., and Tsipis, L.: The accuracy of REleASE forecasts for different heliographic longitude distances, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8207, https://doi.org/10.5194/egusphere-egu26-8207, 2026.
Solar energetic particle (SEP) events pose severe risks to manned spaceflight and most space infrastructure, such as satellites, impacting the broader modern technology-based society. Accurate and timely prediction of SEP events is therefore essential. However, SEP propagation to near-Earth involves multiple complex physical processes, while observational constraints remain limited. Consequently, no physical model has yet been established that can reproduce the full chain of processes accurately and efficiently. We aim to provide physically interpretable reproduction and prediction of SEP events from pre-flare solar observations to near-Earth particle fluxes by improving and connecting models for each process. This presentation focuses on optimizing free parameters in the SEP acceleration and transport model. We coupled a CME propagation model (SUSANOO, SUSANOO-CME; Shiota et al., 2014, 2016) with an acceleration and transport model with the diffusive shock acceleration and the focused transport equation (Minoshima et al., in review), and applied it to the SEP event on 9 October 2021. We attempted simultaneous reproduction of proton fluxes across five spacecraft. We introduced spatial refinement by treating key parameters (injection efficiency ε, acceleration efficiency ξ, and transport mean free path λ) independently for each magnetic field line or heliolongitude, enabling a detailed representation of spatial structure. Furthermore, we implemented black-box optimization using an evolution strategy to robustly and efficiently explore a high-dimensional parameter space. As a result, our framework achieved a lower mean absolute error (MAE) than grid search. Parameter importance analysis revealed that injection efficiency (ε) exerts the strongest influence on proton flux, consistent with physical understanding. This framework achieves accuracy and computational efficiency, representing a significant step toward generalizing initial condition settings in SEP prediction models. Future work will apply this approach to multiple events to establish a model suitable for operational forecasting.
How to cite: Ishikawa, H. T., Fujita, N., Kato, Y., Kurihara, M., Minoshima, T., Shiota, D., Iwai, K., Kusano, K., and Mitsuda, C.: Parameter Optimization of SEP Acceleration and Transport Models Towards Forecasting: Application to Multi-Spacecraft Observations of the 9 October 2021 Event, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6021, https://doi.org/10.5194/egusphere-egu26-6021, 2026.
Field-Alligned Currents (FACs) play a critical role in the coupled Magnetosphere - Ionosphere - Thermosphere (MIT) system, facilitating the transfer of energy and momentum from the solar wind into near-Earth space. Since 2019, the next generation of Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE Next) satellites have produced global maps of ten-minute-averaged FACs in both the Northern and Southern Hemispheres. This volume of new data provides an opportunity to learn more about the influence of the solar wind on the coupled MIT system.
This study presents a probabilistic Machine Learning (ML) approach for forecasting Northern Hemisphere FAC distributions using upstream solar wind and interplanetary magnetic field measurements. The model is designed to capture the structure of FACs on a 1-degree Magnetic Latitude and 1-hour Magnetic Local Time resolution grid, while explicitly representing predictive uncertainty and identifying solar wind drivers. We describe the model architecture and training method, and present preliminary validation results, including performance during geomagnetic storm events selected from the ML-based Geospace Environment Modeling (MLGEM) resource group at the Geospace Environment Modeling (GEM) workshop. Finally, we outline plans for integration of this work into the Artificial Intelligence Modeling Framework for Advancing Heliophysics Research (AIMFAHR) project.
How to cite: Coughlan, M., Connor, H., Valluri, G., and Bard, C.: Probabilistic Machine Learning Techniques for Field Aligned Current Predictions Using AMPERE NEXT and Connections to a Data-Driven Magnetosphere Model., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14362, https://doi.org/10.5194/egusphere-egu26-14362, 2026.
Green and digital transition policies that increasingly rely on satellites and the utilization of the near-Earth space contain an overlooked contradiction between sustainability and resilience: although satellite services increase sustainability on Earth by accelerating green and digital transition, the use of space renders the green and digital infrastructures vulnerable to space weather events. We show that an extreme near-Earth space event may significantly disturb the global sustainability transition. The resilience of green and digital infrastructures on Earth is threatened because of their tight operational coupling with satellite technologies and the contingencies of near-Earth space dynamics. To safeguard the emerging infrastructures with sufficient prediction capabilities, we recommend measures to enhance sociotechnical resilience and new space physics missions to improve our understanding of critical near-Earth space dynamics.
This abstract presents the article that the authors published in Ecology and Society (https://doi.org/10.5751/ES-16056-300206). This is a paper that considers how the field of space physics is aligned and contributes to the terrestrial sustainability, and gives a new and wider definition for the sustainable use of space, which is in line with the decades of discourse in social sciences.
How to cite: Palmroth, M. and Hukkinen, J.: Expanding use of space is an opportunity for sustainability but a threat to resilience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1747, https://doi.org/10.5194/egusphere-egu26-1747, 2026.
In the past, space weather researchers have worked to predict geomagnetic disturbances, sometimes providing advanced warnings of up to several days. Rather than prediction, this presentation provides a proposed model for protection. A model is proposed where the magnetosphere can be temporarily modified through active mass-loading to mitigate and reduce the impact of solar wind structures on Earth’s magnetosphere and ionosphere. Global numerical simulations will be presented demonstrating this process and quantifying the required resources to fortify against strong space weather events. The results demonstrate that with modern, or near-future technology, the intensity of a major geomagnetic storm could be actively reduced by 50% or more, protecting technology and human life.
How to cite: Walsh, B. and Welling, D.: Artificial mass-loading for protection from major space weather events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4018, https://doi.org/10.5194/egusphere-egu26-4018, 2026.
Radionuclides, like 14C and 10Be, are produced by interactions of the Earth's atmosphere with high energetic particles from space. The discovery of large peaks in 14C and 10Be concentration has been linked to severe solar particle events (SPEs), that occured in the past millenia. Besides solar activity, the production rates of radionuclides also depend on the Earth's magnetic field, which shields the planet against cosmic radiation. To infer the strength of the SPE, the amount of shielding has to be known. Here we investigate how uncertainties in the reconstruction of the global geomagnetic field propagate to 10Be production rates. We make use of recent ensemble models for the Holocene geomagnetic field, combined with particle tracing codes, to provide locally resolved cutoff rigidities and 10Be production rates, together with the associated uncertainties. These can be used in combination with deposition models, to estimate 10Be depositional flux. The estimates can be compared to measurements, in order to determine upper and lower bounds for the SPE strength.
How to cite: Schanner, M. A., Panovska, S., Adolphi, F., and Spiegl, T.: Uncertainty propagation in global radionuclide production rate estimates to constrain solar particle event intensity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5081, https://doi.org/10.5194/egusphere-egu26-5081, 2026.
This study aims to investigate the large-scale ionospheric scintillation events that occurred during the magnetic storm on December 1, 2023. Using GNSS network data and ionospheric scintillation data over China, the spatial-temporal evolution of ionospheric irregularities and scintillation are provided, and the impact of these scintillations on GNSS signal and positioning accuracy are studied further, Results show that during magnetic storms, large-scale ionospheric irregularities appear in the China sector, which extend from low to mid-latitudes. When these irregularities structures appear over the GNSS stations, the occurrence of the loss of lock of GNSS signals significantly increases, and their positioning accuracy decreases. The spatiotemporal distribution of loss of lock and the decrease of positioning accuracy shows good consistency, but there are noticeable differences compared to the spatiotemporal distribution of the irregularities. In the mid-latitudes, the irregularities almost do not cause signal loss or decrease in positioning accuracy.
How to cite: Zhang, D. and Zeng, Y.: The space weather effect of the December 1, 2023 geomagnetic storm on GNSS PPP accuracy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4240, https://doi.org/10.5194/egusphere-egu26-4240, 2026.
The daily solar flux at 10.7cm, the F10.7 index, is commonly used as an input in ionospheric models. Typically studies have focused on either global averages or geographically local values of Total Electron Content (TEC), and how these vary with F10.7. Daily F10.7; F10.7A, which is the 81-day average; and F10.7p, which is a combination of these, are all considered. We study how the daily maximum TEC correlates with daily F10.7 [1]. We find that for F10.7 ≳ 78 − 85 SFU, the daily maximum TEC saturates to a seasonally dependent value between 83 − 128 TECU. This saturation of TEC with F10.7 is not generally seen in global averaged TEC or F10.7A/F10.7p. Using 15-minute Global Ionospheric Maps (GIMs) from the Jet Propulsion Laboratory (JPL) between 2003-2024, we apply linear/non-linear least squares fitting on how the daily global maximum TEC varies with daily F10.7 and assess the quality of each fit and how the parameters vary in season for solar cycle 24. We examine the distribution of the residuals as a function of F10.7 and find that a tanh function out- performs a linear function for F10.7≥ 150 SFU. These results are sensitive to different hemispheres, as a result of the construction of JPL-GIMs. Finally, we find that the daily F10.7 clearly resolves the saturation of daily maximum TEC, while F10.7 based on the average does not. Reproducibility of the observed climate of TEC maxima, that is, how daily maximum TEC correlates with daily F10.7, provides a benchmark for ionospheric models forecasting the space weather response of TEC. This is vital for the integrity of position, navigation and timing systems and for the planning of Low Earth Orbit satellite operations.
[1] Cafolla, M.A., Chapman, S.C., Watkins, N.W., & Verkhoglyadova, O.P. (2026). The non-linear dependence of daily maximum ionospheric total electron content on F10.7. Space Weather, 24, e2025SW004745. https://doi.org/10.1029/2025SW004745
How to cite: Cafolla, M., Chapman, S., Watkins, N., and Verkhoglyadova, O.: Daily Maximum Total Electron Content Saturation with Daily F10.7: Seasonal and Hemispheric Effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3152, https://doi.org/10.5194/egusphere-egu26-3152, 2026.
The ionosphere's Total Electron Content (TEC) is a critical parameter for Global Navigation Satellite System (GNSS) positioning, particularly Precise Point Positioning (PPP), satellite communications, and space weather monitoring. While the International GNSS Service (IGS) provides a baseline for global ionospheric maps (GIMs) errors, these products are generated post-facto and lack the temporal resolution needed for real-time forecasting during rapidly evolving solar events. Accurate short-term TEC prediction remains challenging due to the complex, nonlinear coupling between solar extreme ultraviolet (EUV) radiation and ionospheric dynamics.
Here, we present a multi-modal deep learning framework that integrates full-disk solar imagery from NASA's Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) with historical TEC observations to generate global TEC forecasts 15 minutes ahead. The model employs a U-Net architecture with Feature-wise Linear Modulation (FiLM), enabling solar EUV intensities across three wavelength channels (94 Å, 131 Å, 171 Å) to dynamically condition ionospheric feature extraction. By predicting TEC residuals with the standard IGS grid (2.5° × 5° geographic resolution), the framework directly learns solar-driven perturbations while preserving spatial coherence through geometry-aware inputs, encoding solar zenith angle and local solar time. The training dataset spans between 2010-2018 and comprises approximately 770 solar flare events (C, M, and X-class). Stratified sampling across flare classes ensures robust model performance under diverse space weather conditions. We implement comprehensive data preprocessing, including exposure normalization, disk masking, and logarithmic intensity scaling.
The operational concept leverages SDO's continuous, near-real-time AIA data availability. The model ingests the current TEC state, combined with the latest solar EUV imagery, to predict TEC at t+15 minutes. These predictions can then serve as input for the subsequent forecast step, creating an autoregressive chain where each iteration combines new AIA observations (available with ~ 15-minute latency) with the previously predicted TEC state. This sliding window approach enables continuous TEC nowcasting without reliance on ground-based GNSS processing delays.
How to cite: Mauda, N., Reuveni, Y., and Landa, V.: Real-Time GPS ionospheric TEC Mapping using Multi-Modal Deep Learning: Bridging Solar Imagery and Ionospheric Physics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7845, https://doi.org/10.5194/egusphere-egu26-7845, 2026.
Equatorial plasma bubbles (EPBs) are localized ionospheric plasma density irregularities that can strongly disturb Global Navigation Satellite Systems (GNSS) signal propagation, especially after sunset in equatorial regions. Although EPBs have been widely studied, their complex spatial structure and rapid evolution make it difficult to reliably quantify their impact on GNSS-derived total electron content (TEC).
To address this challenge, a simulation framework is employed in which the background ionosphere is generated using the Neustrelitz Electron Density Model (NEDM), and equatorial plasma bubbles are embedded as localized electron density depletions, with their spatial extent derived from satellite observations. GNSS signal propagation is simulated using satellite ephemeris data to define realistic satellite–receiver geometry, and the total electron content (TEC) is computed along the signal paths. The TECs are analysed as a function of satellite elevation angle to assess the impact of plasma bubble structures on trans-ionospheric signal propagation.
The simulated TEC exhibits pronounced variations when signal paths intersect equatorial plasma bubbles, and the magnitude of these variations strongly dependent on satellite elevation and viewing geometry. Signals propagating at low and oblique elevation angles exhibit the largest TEC perturbations due to extended path lengths through ionospheric irregularities.
By varying the bubble structures in simulation environment, we demonstrated the possibility of determining ionospheric bubble structures by analysing their impact on ionospheric TEC data.
How to cite: Shaukat, S., Hoque, M. M., and Schuh, H.: Modelling equatorial plasma bubbles and their impact on GNSS signal propagation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10278, https://doi.org/10.5194/egusphere-egu26-10278, 2026.
Over the past 50-60 years, a decline in the density of the thermosphere has been observed of about 2% per decade at 400 km altitude. This is largely attributed to the increase in atmospheric CO2 concentration, causing cooling and contraction across the stratosphere, mesosphere, and thermosphere. The reduction in thermospheric density reduces drag on active satellites and space debris, affecting orbital characteristics and increasing debris lifetimes. To manage the risk of the growing space debris population and ensure the long-term sustainability of the Low Earth Orbit (LEO) environment, we need to understand the impacts of likely future density changes. Here we used a long transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) 2.0 to define future density scenarios used as input for simulations with the Realisations of the Engineered and Natural Evolution of the Global Atmosphere and Debris Environment (RENEGADE) model. The WACCM-X simulation followed Shared Socio-economic Pathway 2–4.5 and included realistic assumptions on main magnetic field changes and variations in solar activity, which also affect the climate of the upper atmosphere. RENEGADE simulations under a "best-case" scenario for debris generation showed that the projected long-term density trend would lead to ∼8% more objects in LEO by 2070 and a significantly enhanced average collision rate, from 0.22±0.01 to 0.25±0.01 per year. The largest enhancements in debris spatial density, of around 30-35% by 2070, were found at ∼400 km altitude. The thermospheric density trend will therefore have a disproportionally large impact on infrastructure operating around this altitude.
How to cite: Cnossen, I. and Lewis, H.: Impacts of projected climate change in the thermosphere on the future space debris environment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7470, https://doi.org/10.5194/egusphere-egu26-7470, 2026.
Accurate estimation of thermospheric neutral density is vital for atmospheric drag compensation. Actual measurements of thermospheric neutral density are rare, and often limited to specific altitude ranges. Numerical models are often used as a substitute, sometimes in conjunction with data assimilation schemes.
During geomagnetic storms, having an accurate representation of the thermosphere-ionosphere (TI) is vital, since climatological models cannot accurately reproduce the system response. Recently, the physics-based Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model has been shown to provide accurate global estimates of neutral density when used in conjunction with the Thermosphere Ionosphere Data Assimilation scheme (TIDA).
This approach adds the model inputs to the state vector and better accounts for the strongly forced nature of the TI. In this study, we expand on previous work by demonstrating the use of TIDA-CTIPe for neutral density estimation over a much broader time interval, covering multiple geomagnetic events.
We demonstrate the capability to improve global estimates of neutral density by assimilating measurements in a narrow altitude range, from the CHAMP, GRACE and SWARM missions. Additionally, we demonstrate TIDA's capability to improve the thermospheric neutral density by assimilating different data types, such as COSMIC-2 derived TEC. Finally, we discuss the need for near-real-time data for potential forecasting applications.
How to cite: Negrea, C., Codrescu, M., Codrescu, S., Echim, M., and Dumitru, D.: Providing global neutral density estimates using the CTIPe model and data assimilation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16711, https://doi.org/10.5194/egusphere-egu26-16711, 2026.
The Hunga Tonga-Hunga Ha'apai volcanic eruption (hereafter Tonga eruption) occurred on January 15, 2022, was the largest eruption since 1991, also the largest underwater explosion ever recorded. The intensity of Tonga eruption as well as its unique feature of massive water vapor emission makes it a rare and representative case to study the coupling of the whole atmosphere within a short period of time, due to its intense and fast-propagating forcing that is easily recognized when compared to other extreme phenomena. Previous studies have examined the impacts of Tonga eruption on the energy deposition in the neutral atmosphere and the associated wave signatures observed in the ionosphere, among others. This study aims to combine the disturbances observed in different altitude regions of the whole atmosphere in reponse to the Tonga eruption, in order to investigate the vertical coupling between the neutral atmosphere and the ionosphere and understand the underlined physics of ion-neutral interactions.
We approach this goal by utilizing the state-of-the-art whole atmosphere model WACCM-X. Our work includes two runs with solar quiet condition: (1) a free-run WACCM-X simulation with an initial pressure perturbation to simulate the Tonga eruption following Liu et al (2023) to be used as our reference, and (2) a specified dynamics regime configured, namely the SD-WACCM-X simulation with its lower atmosphere nudged with the reanalysis data as a more realistic representation. Our results show Lamb wave features consistent with Liu et al. (2023), and gravity wave signatures due to the strong overshoot of water vapor. Gravity wave momentum flux is calculated to show the vertical energy variation, which is then correlated to the intensity of the observed travelling ionospheric disturbances as a preliminary demonstration of the ion-neutral couplings. Among the neutral atmospheric drivers, we focus on the contribution of neutral winds in the ionosphere by studying its impacts on the ion-neutral collisions and the ion drift velocities. Modeled simulations are also compared with ERA5 thermal variables in the neutral atmosphere, and Madrigal GNSS TEC measurements in the ionosphere, where differences due to data resolution, measuring technique and the lower atmospheric constraints are noticed.
How to cite: Pagiatakis, S., Wang, Y. (., and Vergados, P.: Understanding the Neutral Atmospheric and Ionospheric Disturbances in Response to Hunga Tonga Volcanic Eruption (2022), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15596, https://doi.org/10.5194/egusphere-egu26-15596, 2026.
The International Sunspot Number (SN) is among the longest continuous records of solar activity, thus its accuracy is of the utmost importance for space climate studies. In that context, resolving the remaining scale changes and epoch-to-epoch inconsistencies requires a complete reconstruction of SN, i.e. SN V3.0. The success of this community wide effort depends first and foremost on a strengthened historical data foundation: locating dispersed sources, digitizing them, and preserving provenance-rich metadata so that calibration uncertainties can be linked to dataset quality, rather than only global statistical adjustments.
Within WDC–SILSO and the FARSuN project, major recovery campaigns have expanded and consolidated the observational base. Wolf’s Journals, the Mittheilungen (1610–1944) have been digitized into machine-readable form and integrated with ongoing metadata harmonization and cross-checks. The Zürich observation tables (1945–1979)—the backbone of modern daily production—are being completed through systematic digitization and observer metadata encoding. Complementary early-19th-century sources critical to the 1810s–1840s interval (e.g., Gruithuisen manuscripts, C. H. Adams drawings, and the Stark material) are being collected and extracted using dual-mode transcription (HTR/OCR plus manual verification) with quality control (alias reconciliation, calendar handling, NG/NS consistency tests, and two-person checks for fragile series).
By enlarging overlaps among observers and standardizing heterogeneous formats into a sustainable FARSuN historical sunspot database, these data-gathering efforts enable robust scale-transfer analyses and uncertainty-quantified products, providing the essential foundation for a defensible SN V3.0 series.
How to cite: Lefevre, L., Kalugodu, C., Benjamin, M., Christian, R., and Valliapan, P.: Reconstruction of the Sunspot Number Series : Gathering Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17694, https://doi.org/10.5194/egusphere-egu26-17694, 2026.
May 15, 2024. The Earth is still in the violent aftermath of the Mother’s day storm. Operators doing an HF radio exercise between Belgium and Canada can’t get any signal through. What happened? Two types of solar storms raged on at the moment of the exercise and intercepted the radio waves in the ionised top layer of the Earth’s atmosphere.
One of the missions of the STCE, the Belgian Space Weather Centre is to provide info on space weather and space weather impacts such that professionals with no space weather background understand. The STCE offers basic and tailored training courses and acts as a help desk for stakeholders that run space weather impacted operations and services. The STCE focusses in first instance on awareness and secondly addresses the barriers that users encounter while dealing with the question what space weather is, as well as where to find and how to interpret space weather bulletins, alerts from the STCE.
We will elaborate on our client-tailored methodology.
The STCE, the Solar-Terrestrial Centre of Excellence is the place for research, data & services and education about Sun-Space-Earth and their interactions. The institute can rely on a rich history and expertise in solar and terrestrial observations & measurements, both on ground and from space. The STCE incorporates a Space Weather Service Centre, issuing daily space weather bulletins and warnings in case of space storms. The STCE also runs a Space Weather Education Centre which builds on this firm academic and service experience and has qualified teachers and communicators.
How to cite: Vanlomel, P., D'Huys, E., Dom, E., Janssens, J., Van der Linden, R., and Andries, J.: Space Weather: a natural hazardGoing beyond academic discussions , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19625, https://doi.org/10.5194/egusphere-egu26-19625, 2026.
Posters virtual: Mon, 4 May, 14:00–18:00 | vPoster spot 4
EGU26-3064 | ECS | Posters virtual | VPS27
Storm-Time Strip-Like Plasma Density Bulges at Middle Latitudes Shaped by Meridional Wind GradientsMon, 04 May, 14:54–14:57 (CEST) vPoster spot 4
Prior studies identified a fine structure in the middle latitude ionosphere known as the strip-like plasma density bulge. These bulges emerge during geomagnetic storms, exhibiting a broad longitudinal span of over 150° and a narrow latitudinal extent of 1°~5°. The observations from the DMSP and ICON satellites reveal stronger equatorward ion drifts and neutral winds on the poleward side of bulges compared to the equatorward side. Using the Sami2 is Another Model of the Ionosphere (SAMI2), the bulge feature was reproduced for the storm of 4~6 November 2021 by amplifying the default meridional winds. Numerical simulations indicate that global wind disturbances establish a sharp meridional wind gradient within the lower mid-latitude region. This gradient, in turn, drives a divergence in ion transport parallel and perpendicular to the magnetic field lines, which ultimately results in the localized accumulation of plasma. The phenomenon is most pronounced in the vicinity of ±30° quasi-dipole latitude. This region is characterized by a magnetic inclination angle of approximately 45°, a configuration where the meridional wind component acts most efficiently to elevate ions vertically.
How to cite: Du, W., Zhong, J., and Wan, X.: Storm-Time Strip-Like Plasma Density Bulges at Middle Latitudes Shaped by Meridional Wind Gradients, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3064, https://doi.org/10.5194/egusphere-egu26-3064, 2026.
