This session focuses on the current state of space weather products and explores new ideas and developments that can improve our understanding of space weather and space climate and their impact on critical infrastructure. We invite contributions on topics including, but not limited to: forecasting and nowcasting tools and services; satellite observations and data assimilation techniques; numerical model development, validation, and verification; machine learning applications in space weather prediction; generation and refinement of solar, geomagnetic, and ionospheric indices. We particularly welcome interdisciplinary and collaborative approaches that bridge research and operational communities. Contributions that address the drivers and the real-world impacts of space weather on systems such as aviation, pipelines, power distribution, human spaceflight, and auroral tourism are strongly encouraged.
The UK Met Office Space Weather Operations Centre (MOSWOC) provides continuous monitoring, nowcasting, and forecasting of space weather to support critical infrastructure and national resilience. Operating 24/7, MOSWOC integrates real-time observations from ground- and space-based assets with advanced models and expert analysis to deliver guidance for sectors including satellite operations, aviation, and power distribution.
This presentation will describe the current operational capabilities of MOSWOC and will share lessons learnt from recent space weather events. It will also highlight recent advances in developing a collaborative framework that bridges research and the operational communities. This framework enables the UK research community to implement space weather models on Met Office systems, facilitating the transition from research to real-time service delivery. Finally, the talk will outline the Met Office space weather research strategy, emphasising the role of rigorous verification, data assimilation, model coupling and impact forecasting to further improve MOSWOC services.
How to cite: Bingham, S., Bocquet, F.-X., Jackson, D., and Gonzi, S.: Nowcasting, forecasting and operational monitoring of space weather at the UK Met Office, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1844, https://doi.org/10.5194/egusphere-egu26-1844, 2026.
We present ongoing and forthcoming developements for building an integrated model capable of propagating solar storms from the Sun to Earth, together with high-energy particle emissions from the solar corona by coupling different models. The resulting global model will be based on several world-renowned solar wind, CME and SEP models, some of which are already available to users 24/7 via the STORMS weather forecasting service (storms-service.irap.omp.eu) accredited by the CNRS and maintained by Infor'Marty and IRAP/University of Toulouse.
The PARASOL project will introduce new coupling and data-driving methodologies in order to obtain continuous simulations of the complex interactions between solar storms and the solar wind, as well as the acceleration and propagation of high-energy particles between the Sun and the Earth. Solar imagery and in-situ data obtained in real time is use to not only to initialise the models, but also to constraint them continuously. We will discuss the layout of the new operational systems, together with the strategies for validation of each individual component and of the full chain.
The end goal of the project is to lay out a complete operational space weather forecasting framework ready to be exploited by end-users noth in the public and private sectors.
We acknowledge funding by ANR/AID (grant ANR-25-ASTR-0025, PARASOL).
How to cite: Pinto, R., Rouillard, A., Indurain, M., Alexandre, M., and Dalmasse, K.: PARASOL: development of an operational solar storm and high-energy particle forecasting system, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9792, https://doi.org/10.5194/egusphere-egu26-9792, 2026.
Since November 2019, ICAO Space Weather Centres have issued operational advisories to support civil aviation decision making for HF communications, GNSS, and radiation. We present a consolidated analysis of the ICAO advisory record from November 2019 to September 2025, using the advisories as an operational “space weather climate” dataset to identify where current products perform well, where they are biased, and which post event lessons translate into concrete service improvements.
Across the period, we identify 2,350 advisories grouped into 867 advisory series, dominated by GNSS (1,472) and HF communications (872). Moderate advisories prevail (1,592) over Severe (758). Advisory occurrence scales with Solar Cycle 25 activity and exhibits both strong storm driven clustering (notably May and October 2024) and a clear equinox season enhancement. Geographic footprints are distinct: HF advisories concentrate in the auroral oval and polar cap, while GNSS advisories preferentially populate a low latitude belt with pronounced activity in the South Atlantic sector.
We use these results, supported by targeted event case studies and an impact oriented illustration from HF quality reporting, to propose operational priorities: harmonised cross centre event definitions and closure criteria, better constrained model to observation chains (especially for SEP driven absorption and GNSS impacts), and routine post event analysis with outcome based logging that links advisories to observed operational effects. This bridges research and operations by turning long term advisory statistics into actionable requirements for next generation nowcasting and forecasting services.
How to cite: de Patoul, J., Shukhobodskaia, D., Verhulst, T. G. W., and Maneva, Y.: Operational space weather for aviation under ICAO: Lessons for improved nowcasting and forecasting from 6 years of service, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21892, https://doi.org/10.5194/egusphere-egu26-21892, 2026.
To fully understand and predict the behaviour of the near-Earth space environment in changing solar wind conditions, physics-based modelling is an extremely powerful tool. This can come at considerable computational expense, often making it unsuitable in operational contexts. Recent efforts in transforming research to operations (R2O), however, have produced several 3D magnetohydrodynamic (MHD) magnetosphere models optimised to run using only modest computational resource. One such model is GorgonOps, developed at Imperial College London. With real time solar wind measurements at L1 as inputs, the model simulates the behaviour of Earth’s magnetosphere in faster than real time, making it extremely valuable for space weather forecasting. GorgonOps is currently undergoing integration at the UK Met Office and will soon be deployed as part of the Bergen-Imperial Global Geospace (BIGG) project.
BIGG is a collaborative effort with the University of Bergen, funded under the ESA Space Safety Programme, to provide new forecasting products to the ESA Space Weather Service Network. It combines GorgonOps with another MHD model, the Space Weather Modelling Framework (SWMF). The two run simultaneously, creating forecasting products relevant for sectors such as LEO satellites and power infrastructure, including thermospheric Joule heating, Kp, and dB/dt at a range of synthetic ground stations. In this presentation, we will demonstrate the newly developed BIGG system and associated model developments. This includes an interactive visualisation dashboard as well as an API service, allowing users to retrieve the latest forecasts instantly. The multi-model federated approach is such that it can be expanded to incorporate new models, further increasing forecast diversity and redundancy to ensure reliable service provision to Europe and beyond.
How to cite: LaMoury, A., Heyns, M., Eastwood, J., Kwagala, N., and Engevik, J.: GorgonOps and the BIGG project: Physics-based magnetosphere modelling for operational space weather forecasting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19326, https://doi.org/10.5194/egusphere-egu26-19326, 2026.
We present a fully automated end-to-end pipeline for operational short-term forecasting of the in situ magnetic structure of coronal mass ejections (CMEs) at Earth. Triggered by new events in the NASA/CCMC DONKI catalog, the system couples ensemble arrival time predictions using ELEvo with deep-learning-based in situ detection of magnetic obstacles (ARCANE), and iterative flux rope reconstruction using the semi-empirical 3DCORE model. As more real-time L1 solar wind data becomes available, the pipeline continuously updates forecasts of the remaining CME magnetic field profile. Using archived real-time data, we evaluate the pipeline under operational constraints and analyze how reconstruction quality evolves as a function of available data, providing insight into capabilities and limitations of fully automated real-time CME magnetic field reconstruction for space weather forecasting.
How to cite: Rüdisser, H. T., Davies, E. E., Amerstorfer, U. V., Weiler, E., Weiss, A. J., Reiss, M. A., Le Louëdec, J., Nguyen, G., and Möstl, C.: Towards a fully automated end-to-end pipeline for short-term CME magnetic field forecasting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11539, https://doi.org/10.5194/egusphere-egu26-11539, 2026.
Since we are highly reliant on space-based technology, running human explorations in near-Earth space and planning for human missions to our neighbouring planet, e.g., Mars, building nowcasting and forecasting frameworks with the potential to reduce the risk posed by major solar transients, e.g. Coronal mass ejections (CMEs), has become one of the prime interests. We investigated approximately 20 magnetic and plasma parameters including magnetic and kinetic energy, helicity, plasma beta, proton velocity, density, magnetic field intensity, temperature, and their fluctuations, ratio of alpha to proton number density, observed to expected proton temperature, Alfvén speed, Mach number, total pressure, and entropy to characterize solar wind plasma within magnetic ejecta (MEs), sheaths (SHs) of interplanetary (I) CMEs, and nonICMEs. We rank the features based on their importance in characterizing these solar wind structures and use the best 15 parameters to train a supervised machine learning model to auto-identify these structures in the solar wind stream. The f1-scores in classifying MEs, SHs, and nonICMEs are found as 0.92, 0.88, and 0.86, respectively, with macro accuracy of ~90%. Furthermore, we quantify the uncertainty in classifying the plasma parcels. Finally, we develop a pipeline and web-based tool using the model that takes input of streaming solar wind plasma at 1 au and auto-classifies them in MEs, SHs, and nonICMEs. This tool enables real-time space weather alerts by automatically detecting the presence of ICMEs, including MEs and SHs in the solar wind.
How to cite: Pal, S., Bhardwaj, S., Layh, R., and Nieves-Chinchilla, T.: Towards Operational Space Weather Nowcasting via Solar Transients and Their Substructure Auto-identifications , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16292, https://doi.org/10.5194/egusphere-egu26-16292, 2026.
Since 2019, the SaRIF webpages on the ESA space weather portal have been used as a tool to visualise current conditions in the electron radiation belt and forecasts up to 24 hours ahead. SaRIF collects a variety of real-time data from satellites and geomagnetic indices and uses this information to determine current risk factors for satellites operating within the radiation belts around earth. Timely and accurate warnings of space weather events are crucial for satellite operators to minimise risk to fundamental services such as navigation, communications and science operations.
Over the lifetime of this tool, satellites have been used to provide data for the modelling systems used in SaRIF. In particular, the GOES satellites have provided electron flux data for the British Antarctic Survey Radiation Belt Model (BAS-RBM) that produces the SaRIF forecasts. As of April 2025, however, GOES-16 has been decommissioned and is no longer providing real-time data. We have analysed its successors, GOES 18 & 19, to determine which is a more suitable replacement for use in the SaRIF forecasting system. This includes an investigation into data quality, availability across the different energy channels and long-term data trends. We show that GOES-18 is the optimal choice, due to higher availability at the highest energy channels, crucial for calculation of the BAS-RBM boundary conditions, as well as its location closest to the equator, therefore measuring fluxes with a pitch angle closest to 90°.
Additionally, we have explored improved methods for calculating boundary conditions for the BAS-RBM thus enhancing the accuracy of the modelling underpinning our forecasting system. To determine the outer L* boundary conditions, we fit a kappa-type distribution to the electron flux data from GOES, allowing the flux to be calculated at any energy value, and then convert to phase-space density for providing the final boundary conditions. Finally, we present a new approach to providing the low energy boundary conditions for the RBM, using Van Allen Probes data to determine the average profile along the low energy boundary for different levels of activity. Using a continuous data period of ³6 months, we demonstrate that using these activity dependent profiles improve our simulation results.
How to cite: Hudson, R., Glauert, S., Hendry, A., and Kirsch, P.: The evolution of the SaRIF space weather forecasting system using new satellite data and improved methods for defining boundary conditions., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21468, https://doi.org/10.5194/egusphere-egu26-21468, 2026.
The solar radio flux at 10.7 cm (F10.7) is a key proxy used in thermospheric density and atmospheric drag models and is therefore critical for low Earth orbit prediction. Forecasting F10.7 remains challenging due to its strong day-to-day persistence and the difficulty of anticipating rapid increases associated with enhanced solar activity. In this study, we formulate F10.7 forecasting as a multi-horizon regression problem, incorporating time-derivative information and solar-rotation weighting to capture short- and medium-term variability. Forecasts at 1-, 3-, and 7-day lead times are generated using a regularised multi-output Elastic Net model, chosen to stabilise multi-horizon regression in the presence of strongly correlated lagged, derivative, and rotation-weighted predictors. The model is trained on rolling windows and refitted as new observations become available. Performance is evaluated over the period 2020–2025, showing that during low solar activity conditions the model achieves RMSE values as low as ~5 SFU, increasing to approximately 10–12 SFU during higher activity periods. Across rolling test issue dates, the proposed approach consistently outperforms persistence, reducing RMSE by about 15–20%, with the largest improvements occurring at longer lead times.
How to cite: Anil, A., Tzamali, M., Glover, A., and Luntama, J.-P.: Short- and Multi-Horizon F10.7 Forecasting Using Elastic Net Regression, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22342, https://doi.org/10.5194/egusphere-egu26-22342, 2026.
We report on the real‐time implementation of a local solar proton event forecasting system at the Solar Terrestrial Relations Observatory-Ahead (STEREO-A) spacecraft, namely STEREO REleASE+. The forecasting uses the finding that relativistic electrons provide the “earliest indication” that a solar particle event has started. They arrive at near‐Earth distance earlier than protons at ∼30% of the speed of light. In addition to relativistic electrons, we use a requirement of a radio burst of type III to be observed before issuing a proton alert. A similar system, HESPERIA REleASE+, has already been implemented using electrons observed by SOHO and ACE near Earth, which creates local forecasts for the Earth‐moon system. The radio observations from STEREO‐A are used in both systems, given that radio bursts in parts of their emission spectrum can be observed from all around the Sun. Usefulness of adding a radio burst requirement to an electron‐based forecasting system lies in the potential for suppression of known sources of false alarms, adding robustness. While this work describes the establishment of the real‐time system, we have also started investigating the two local and robust forecasts to test how far away from the spacecraft the validity and usefulness of the local forecasts extend (Droege et al., submitted Abstract EGU26-8207, this conference). Moreover, the STEREO REleASE+ system, currently located between Earth and Earth‐Sun L4, adds an additional safeguard for exploration of the moon, in particular from solar particle events originating behind the western limb of the Sun.
How to cite: Malandraki, O., Karavolos, M., Droege, H., Heber, B., Kuehl, P., and Tsipis, L.: STEREO REleASE+: Adding Robustness to Solar Proton Event Forecasting in the Heliosphere by Means of Automated Recognition of Type‐III Radio Bursts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14339, https://doi.org/10.5194/egusphere-egu26-14339, 2026.
The Vigil mission will be ESAs first operational space-weather mission positioned at the Sun–Earth L5 Lagrange point. From this unique vantage point, Vigil will continuously monitor solar activity and observe regions that will rotate into the Sun–Earth line several days later. This perspective significantly enhances near–real-time space-weather nowcasting and forecasting while also enabling long-term scientific investigations. This presentation will provide an overview of the mission’s objectives, implementation status, payload, and planned data products.
Vigil’s remote-sensing payload includes the Compact Coronagraph (CCOR; NOAA, NRL, NASA) and Heliospheric Imager (HI) for tracking the formation, evolution, and propagation of coronal mass ejections (CMEs); the Photospheric Magnetic Field Imager (PMI) for magnetic-field mapping and solar-wind modelling and forecasting; and the NASA-contributed EUV Imager (JEDI), which will provide full-disk and extended-coronal observations in multiple EUV passbands out to 6 solar radii. These are complemented by in-situ measurements from the magnetometer (MAG) and plasma analyser (PLA), together delivering a consistent, calibrated, and openly accessible dataset for both operational and scientific users.
Vigil will provide science-quality data at low latency, supporting real-time operational forecasting as well as long-term research. All data products will be fully integrated into the ESA Space Weather Service Network, ensuring broad accessibility, continuity, and interoperability across the space-weather community. Vigil’s deployment represents a major step forward in global space-weather monitoring capabilities, offering high-quality observations from a strategically critical location for the first time.
In this presentation, I will introduce the Vigil mission, the payload, and mission status, highlight how the space-weather and solar-physics communities can make full use of Vigil’s capabilities, and outline opportunities for international collaboration aimed at maximising the mission’s scientific and operational impact.
How to cite: West, M., Mandorlo, G., Dean, M., Palomba, M., De Witte, E., Luntama, J.-P., Glover, A., and Newmark, J.: The ESA Vigil Mission at L5: Operational and Scientific Space Weather Opportunities from a New Perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-698, https://doi.org/10.5194/egusphere-egu26-698, 2026.
We investigate the feasibility and potential forecasting benefits of future sub-L1 missions. Spacecraft positioned sunward of the Sun–Earth L1 point offer a promising opportunity to increase forecast lead times for geoeffective solar-wind structures.
ESA is currently preparing a sub-L1 mission, HENON, scheduled for launch by the end of 2026. HENON is a CubeSat mission on a distant retrograde orbit (DRO) at roughly 0.9 au. A larger follow-on mission, SHIELD, is being studied, consisting of a fleet of spacecraft with an orbit planned at about 0.86 au. Together, these efforts represent the first concrete steps toward operational sub-L1 monitoring. Compared to L1 monitoring, the forecast lead times for CME in situ structures and their geomagnetic impacts are increased by factors of roughly 10 and 14 for HENON and SHIELD, respectively.
In our study, we evaluate key requirements for future sub-L1 missions. To this end, we analyse past observations from spacecraft that have crossed the Sun–Earth line at heliocentric distances of less than 0.95 au, including STEREO-A, Solar Orbiter, and Parker Solar Probe. We assess whether and how these data could be used to reliably reproduce observed geomagnetic storms at Earth. We develop a baseline methodology that continuously time-shifts sub-L1 measurements to Earth and hereafter applies the Temerin and Li solar wind-to-Dst model, enabling a direct comparison between predicted and observed geomagnetic indices.
Exploiting the Sun–Earth line passage of STEREO-A from November 2022 to June 2024, we find that a radial separation to Earth of up to 0.05 au sometimes results in negative lead times, with structures being observed at L1 before STEREO-A. This implies that future sub-L1 monitors must be positioned closer to the Sun than 0.95 au. We also find that stronger geomagnetic events are reproduced best, with 82% of all intense storms being successfully modelled using sub-L1 data. Furthermore, we identify a possible east–west asymmetry in forecast lead time, with higher lead times eastward of the Sun-Earth line than westward. This could, however, be a trajectory effect of STEREO-A and should be systematically investigated by HENON.
Using Solar Orbiter and Parker Solar Probe measurements at even smaller heliocentric distances, we aim to statistically determine an ideal trade-off between increased lead time and forecast accuracy.
How to cite: Weiler, E., Davies, E., Möstl, C., Lugaz, N., Bailey, R., Veronig, A., and Reiss, M.: Potential benefits of future sub-L1 missions (HENON, SHIELD) for space weather forecasting, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9450, https://doi.org/10.5194/egusphere-egu26-9450, 2026.
The HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) mission is being developed in the framework of the ESA General Support Technology Program (GSTP) Fly Element and funded by the Italian Space Agency. Currently it is in the middle of implementation stage (Phase D), expected to be launched as a companion of the ESA Plato spacecraft in January 2027. In several months using its own innovative solar-electric propulsion, the 12U cubesat will transfer to a Distant Retrograde Orbit (DRO) of the Sun-Earth system. The one-year lasting orbit allows for about three months to stay ~ 0.1 AU in front of the Earth. Such a unique vantage point enables the quasi real time monitoring of the particle radiation environment in deep space and the generation of alerts for geoeffective solar wind structures several hours before they can reach the Earth. During the rest of the orbit the HENON cubesat will make scientific observations of large solar wind structures and study the fundamental processes of space plasma physics including the particle acceleration and turbulence. The mission payload consists of the high-resolution radiation monitor (REPE), magnetometer (MAGIC), and the Faraday cup based solar wind monitor (FCA), provided by the Italian, Finnish, UK, and Czech consortium members.
We report on a development progress of latter sensor – the Faraday Cup Analyzer (FCA), devised at Charles University as a simple and robust sensor for long-term monitoring of the basic solar wind parameters – density, velocity and temperature. The FCA flight unit currently undergoes environmental and functional testing. As the HENON mission is greatly constrained with limited spacecraft telemetry, we also discuss the data strategy and on-board data processing allowing maximum scientific income and satisfying the mission requirements. The instrument operation modes and telemetry data products are described.
How to cite: Prech, L., Nemecek, Z., Safrankova, J., Cermak, I., Chlupaty, V., Durovcova, T., Marccuci, M. F., Laurenza, M., and Calgano, D.: Solar wind monitor for space weather forecasting and science at 0.9 AU – HENON mission, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7572, https://doi.org/10.5194/egusphere-egu26-7572, 2026.
HENON (Heliospheric pioneer for solar and interplanetary threats defence) is a new European CubeSat technology demonstration mission conceived to address the widely recognized space weather need for longer lead-time measurements of the solar wind upstream of the Earth. To do this, HENON will occupy a distant retrograde orbit in the Sun-Earth system, ‘orbiting’ the Earth once per year and spending a significant period of time upstream of the Earth at 0.1 AU distance, x10 that of the L1 point. Planned for launch in early 2027, HENON will carry a miniaturised space weather payload as a pathfinder to demonstrate increased warning times for space weather conditions at Earth. This payload includes a radiation monitor, a solar wind instrument, and a magnetometer, MAGIC.
In this contribution we present the MAGIC instrument that is being developed for HENON. MAGIC is highly miniaturised and based on magneto-resistive technology, making it a suitable instrument solution given the limited resource envelope on HENON. MAGIC’s flight heritage includes the CINEMA and RadCube CubeSats in low-Earth orbit, with a further version now delivered for flight as part of the ERSA payload planned for the Lunar Gateway. Here we describe the instrument concept and design, as well as the main technical developments arising from the implementation of MAGIC on HENON, most specifically in efforts to improve radiation hardness assurance.
Although HENON is conceived in the context of space weather monitoring, by measuring the solar wind magnetic field HENON-MAGIC will help advance our understanding of the solar wind and heliophysics more generally. We review key outstanding scientific questions relating to the solar wind that HENON will provide insight into, and summarise some previous observations that help inform the HENON science goals.
How to cite: Eastwood, J., Brown, P., Oddy, T., Baughen, R., Greenaway, C., Yu, X., LaMoury, A., Lewis, H., Aldrian, T., Florescu, P., Ganeshan, H., Hodges, H., and Tzartzi, P.: Solar wind magnetic field measurements from the sub-L1 point on the HENON CubeSat, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8210, https://doi.org/10.5194/egusphere-egu26-8210, 2026.
The ionospheric electric currents are a principal source of geomagnetic variations and geomagnetically-induced currents (GICs) in the polar region. It is therefore essential to model the polar ionospheric electric currents to discuss the geomagnetic phenomena at high latitudes. Recently, we have developed a data assimilation system based on an emulator of a global magnetohydrodynamic (MHD) model of the magnetosphere. In this system, line-of-sight velocity data by the SuperDARN radars are incorporated into the emulator using a data assimilation method based on the ensemble transform Kalman filter, and it estimates the electric potential distribution in the polar ionosphere by exploiting both physical knowledge and observational information. In this study, we derived the spatial distributions of the ionospheric currents and field-aligned currents (FACs) from the potential distribution obtained from the data assimilation system. The results well reproduced typical features of the ionospheric currents such as DP2 two-cell patterns and those of the FACs such as the Region-1 and Region-2 systems. This framework is promising for analyzing various phenomena in the polar ionosphere.
How to cite: Nakano, S., Kataoka, R., Fujita, S., Nilam, B., Reddy, S., Nakamizo, A., and Yukimatu, A.: Reproducing the electric current system in the polar ionosphere by emulator-based data assimilation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7102, https://doi.org/10.5194/egusphere-egu26-7102, 2026.
The Earth’s radiation belts are a complex system that endangers satellites instruments and especially electronics onboard spacecraft. Its dynamic may quickly change over several orders of magnitude. Forecasting and reanalyzing this environment is of prime importance for Space Weather and Space Climate assets. Salammbô is a model of the radiation belts dynamics that has been developed at ONERA. In order to correct Salammbô uncertainties, satellite observations coming from ONERA large database of in-situ measurements (IPODE, Ionising Particle Onera DatabasE) are assimilated using an Ensemble Kalman Filter (EnKF). For the EnKF to be optimal, it is important to quantify model and observation errors. As part of the Radiation Belt Forecast and Nowcast activity (RBFAN), this data assimilation tool is used as a prototype of Space Weather service and is available on the ESA SWE Network Portal since July 2023.
This study focuses on the estimation of observations pre-processing errors and their impact on data assimilation, which is a topic not currently covered in our field of research. One of the major sources of uncertainty is related to observation’s locations. Indeed, it is necessary to rely on magnetic field models to convert geographic locations to magnetic coordinates which are used in typical radiation belts codes. In IPODE database, the computation of observation’s magnetic coordinates is done using the Olson-Pfitzer Quiet magnetospheric model (OPQUIET), following recommendations from COSPAR/PRBEM guidelines. OPQUIET has the advantage to be fast to compute. However, it is a static model that does not consider the magnetospheric dynamic. Therefore, OPQUIET makes an error on the coordinates computation which then impacts Salammbô results. This contribution focuses on (1) the observations representation error induced by the use of OPQUIET in comparing its L* computations with the ones computed with the dynamical magnetic field model Tsyganenko 89 model (T89) along 15 years of THEMIS spacecraft orbit, (2) a simple and analytical model allowing to consider this error in the data assimilation scheme, and (3) the impact of this error on Salammbô-EnKF code. We conclude that this error can reach three orders of magnitude and consequently has to be carefully taken into account in the assimilative process.
How to cite: Vanche, Z., Maget, V., and Pannekoucke, O.: Accounting for representation uncertainties in data assimilation of Earth radiation belts satellite observations to improve Space Weather forecast, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3413, https://doi.org/10.5194/egusphere-egu26-3413, 2026.
Field‐aligned currents (FACs) mediate magnetosphere-ionosphere coupling and can strongly enhance the electromagnetic energy input into the upper atmosphere during space‐weather disturbances. Space-based magnetometers in low-Earth orbit (LEO) have been used for decades to infer local FACs. However, the magnetic field perturbations they measure often contain additional contributions from magnetospheric, ionospheric, and ground-induced currents. Isolating these contributions using single or dual spacecraft remains challenging, instead requiring local spacecraft constellations (e.g., Swarm or the GDC mission concept) and motivating physics-based tools to disentangle their signatures.
Global magnetohydrodynamic (MHD) simulations of the coupled magnetosphere-ionosphere system offer a potential framework for assessing the different current-system’s contributions and for enabling direct comparisons with in-situ data. However, numerical constraints introduce a several-Earth-radii “gap region” between the ionosphere and inner magnetosphere, preventing direct prediction of magnetic fields at LEO.
We extend existing methods traditionally used to compute ground magnetic perturbations so that they operate at LEO and use them as a benchmark to evaluate alternative approaches that are more efficient and stable than traditional full three-dimensional Biot-Savart integration. We validate the methods by implementing them in the Gorgon global MHD model.
We present results on the magnetic field contributions from the different current systems at LEO and discuss implications for current and future low-orbit missions (TRACERS, AMPERE, and emerging megaconstellations), as well as for advancing next-generation space-weather forecasting capabilities to LEO.
How to cite: Burne, S., Archer, M., Heyns, M., LaMoury, A., Southwood, D., Chittenden, J., and Eastwood, J.: Filling in the global MHD model gap region: Enabling predictions of magnetic field perturbations at Low-Earth Orbit, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20504, https://doi.org/10.5194/egusphere-egu26-20504, 2026.
We present our work at the Royal Observatory of Belgium to develop a novel, data-driven approach to generate global near real-time VTEC maps using multi-constellation GNSS data, extending the capabilities of the established ROB-IONO software (Bergeot et al., 2014). Our method employs a multi-step downsampling and data reduction algorithm, combined with median polish kriging, to produce global VTEC maps. This purely data-driven approach, which does not rely on ionospheric models or prior time steps as input, enables near real-time mapping and robust analysis of large-scale ionospheric and plasmaspheric trends.
These maps are particularly valuable for studying the ionosphere-plasmasphere system during geomagnetic storms and other disturbed conditions, such as the May 2024 geomagnetic storm. By integrating complementary datasets (e.g., COSMIC-2, ionosondes), we can disentangle ionospheric and plasmaspheric contributions to VTEC, offering new insights into their dynamic behavior and changes in distribution during space weather events. The downsampling and median polishing techniques also enable future analysis of long-term GNSS datasets, facilitating studies of decadal-scale trends in the ionosphere-plasmasphere system, which are critical for understanding changes in the climatology of the upper atmosphere and the impacts of solar cycle variations. This global VTEC mapping capability not only enhances space weather monitoring but also provides a powerful tool for investigating long-term ionospheric variability, with uses for both scientific research and operational applications.
How to cite: Dreyer, J., Chevalier, J.-M., and Bergeot, N.: Development of Global VTEC Maps at the Royal Observatory of Belgium: Applications for Space Weather and Long-Term Ionospheric Trends, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20933, https://doi.org/10.5194/egusphere-egu26-20933, 2026.
Accurate satellite orbit prediction in low-Earth orbit (LEO) has become increasingly important as satellite congestion grows in this region of the atmosphere, increasing the risk of collisions with other spacecraft and space debris. Atmospheric drag is the dominant source of uncertainty at LEO altitudes, with it being the largest non-conservative force in this region. This makes accurate estimation of thermospheric parameters essential for reliable orbit propagation, as the LEO drag force is a function of neutral thermospheric parameters.
Orbit prediction relies on estimating thermospheric properties such as density, temperature, and winds, where currently empirical or numerical models are used to generate these values. Although widely used in space operations, these models struggle to capture the thermosphere’s dynamic behaviour, which leads to significant errors in drag estimation and orbital predictions. A major event occurred in February 2022, when SpaceX launched 49 Starlink satellites during a minor geomagnetic storm. This unexpectedly increased satellite drag, causing 38 satellites to deorbit, where they were ultimately lost as a result of atmospheric reentry. This loss for SpaceX shed light on the need for more accurate thermospheric models, as satellite operators rely heavily on these models for orbit planning.
As collision risk increases, satellite operators require higher-fidelity modelling approaches. While machine learning methods have shown promise in improving thermospheric state prediction, they are not yet widely adopted. Graph Neural Networks (GNNs) have demonstrated strong performance in spatiotemporal modelling of complex geophysical systems. Notably, Google DeepMind’s GraphCast model demonstrated predictive skill comparable to that of the ECMWF operational forecasting system, setting a new benchmark for medium-range tropospheric weather prediction.
This research develops a GNN-based framework to model the spatiotemporal dynamics of the thermosphere, enabling improved estimation of neutral atmospheric parameters and supporting more accurate orbit prediction in the near-Earth environment.
How to cite: Dable, E., Aruliah, A., and Bhattarai, S.: A Graph Neural Network Approach for High-Fidelity Thermospheric State Estimation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5649, https://doi.org/10.5194/egusphere-egu26-5649, 2026.
Data assimilation has been applied to study the radiation belts for many years, and more recently, to the ring current and the plasmasphere. While data assimilation shows significant potential as an efficient tool for nowcasting and post-event analysis, validating data-assimilative simulations of particles in the inner magnetosphere remains a significant challenge due to the scarcity of scientific data.
In this work, we utilize data from both Arase and Van Allen Probes to validate data-assimilative simulations of the plasmasphere, ring current, and radiation belts. All simulations are performed by using a variant of the VERB (Versatile near-Earth environment of Radiation Belts and ring current) code tailored to each particle population, combined with an extended Kalman Filter. By assimilating measurements from the Van Allen Probes and comparing the results with independent Arase measurements, we aim to evaluate the performance of our data assimilation model.
Before assimilating the data, both data sets are processed and harmonized using the newly open-sourced processing framework: ELaborative Particle Analysis from Satellite Observations (EL PASO, available on GitHub). EL PASO allows the user to download, process, and harmonize space physics data, producing the output in a standardized format, to support practical multi-mission studies. In addition, metadata saved alongside the data ensures that the output follows the FAIR principles.
In this study, we show that data assimilation helps to reproduce the dynamics of all three particle populations: plasmasphere, ring current, and radiation belts. Even when the measurements are assimilated only in a limited magnetic local time sector, the accuracy of the predictions is improved in a global manner. Therefore, data assimilation proves to be an invaluable tool for nowcasting and post-event analysis, especially in cases when measurements are sparse.
How to cite: Haas, B., Shprits, Y., Garcia Penaranda, M., Drozdov, A., Wang, D., Lyu, X., and Jhawar, S.: Validation of Data-assimilative Plasmasphere, Ring Current, and Radiation Belts Simulations Powered by the Open-Source Data Processing Framework EL-PASO, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6291, https://doi.org/10.5194/egusphere-egu26-6291, 2026.
We investigate storm-time ionospheric plasma density peak structures at middle latitudes using multi-instrument observations and a statistical analysis. Case studies of the April 2023 geomagnetic storm and the May 2024 superstorm reveal distinct types of plasma enhancements over the Asian–Australian sector during the recovery phase. The April 2023 event exhibits a narrow mid-latitude peak with clear equatorward motion and slight westward drift, characterized by strong O⁺ dominance. Its formation is closely associated with equatorward thermospheric winds and F-layer uplift, while the sharp boundaries of the structure are linked to storm-time O/N₂ depletion and subauroral polarization stream (SAPS) flows.
In contrast, the May 2024 superstorm produces plasma density peaks along ±40° MLAT accompanied by low-latitude enhancements. These structures display pronounced westward evolution and are primarily formed through the stretching and transport of high-density plasma remnants from the storm-enhanced density (SED) base region within a SAPS channel. Plasma composition and ion drift observations confirm their ionospheric origin. The subsequent reshaping of the overall structure and the asymmetric behavior of low-latitude enhancements highlight the role of polarization electric fields associated with equatorial plasma bubbles.
To assess the generality of these phenomena, we perform a statistical analysis of 92 geomagnetic storms (Dst < −50 nT) from 2020 to 2024. Fifty-five events exhibit similar mid-latitude peak structures over East Asia, with most occurring during the recovery phase. These results demonstrate that storm-time mid-latitude plasma density peaks are common but can arise from different physical pathways. We propose that their formation and evolution are governed by varying combinations of thermospheric winds, composition changes, SAPS-driven transport, and electrodynamic processes during geomagnetic storm recovery.
How to cite: Yang, Y.: Storm-Time Plasma Density Peaks at Middle Latitudes: Observations, Statistics, and Mechanisms During Recovery Phases, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9151, https://doi.org/10.5194/egusphere-egu26-9151, 2026.
Geomagnetically induced currents (GIC) are electrical currents caused by variations of the geomagnetic field due to space weather phenomena. These currents can affect numerous infrastructures, such as pipelines and power grids, becoming particularly hazardous during magnetic storms.
This study investigates the Storm Sudden Commencement of the October 2024 magnetic storm by analyzing solar wind data from WIND, ARTEMIS, and GOES satellites, alongside ground-based magnetometer data from the European quasi-Meridional Magnetometer Array (EMMA) network. We reconstructed the interplanetary shock’s normal and the Earth’s magnetosphere state thanks to the TS04 and Shue et al. model. Magnetospheric-ionospheric currents were evaluated and the geoelectric surface field was estimated to compute GIC magnitudes using the MAIGIC model (Piersanti et al., 2019).
This research contributes to understanding how GIC are coupled with interplanetary shocks and when such phenomena can pose significant risks to modern technology.
How to cite: Zurzolo, S., Piersanti, M., and Oliveira, D.: Geomagnetically induced currents during the SSC of the October 2024 geomagnetic storm in Europe., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18392, https://doi.org/10.5194/egusphere-egu26-18392, 2026.
Neutral density measurements are difficult to make, limited in number and coverage, and
often suffer from large and poorly specified uncertainties. This makes the option to im-
prove neutral density specification using thermosphere/ionosphere measurements very
attractive for satellite collision avoidance applications. Better neutral density specification
and forecast can reduce the uncertainty in satellite and debris positioning, lower satellite
fuel consumption, and help prevent the Kessler Syndrome. Using the Thermosphere Iono-
sphere Data Assimilation (TIDA) package, we investigate whether it is possible to improve
global thermosphere neutral density results by assimilating a variety of measurements
taken within the thermosphere/ionosphere system.
How to cite: Codrescu, M., Catalin, C., and Codrescu, S.: Data Assimilation for better global neutral density specification and forecast, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17574, https://doi.org/10.5194/egusphere-egu26-17574, 2026.
Space weather affects a wide range of commercial and critical infrastructure systems, yet the availability, suitability, and usability of space-weather data products vary significantly across application domains. The focus of this work is to perform a structured assessment and mapping of existing and emerging space-weather datasets and services, to technical requirements derived from user needs identified through stakeholder engagement. This project is part of the Space Weather Infrastructure Impact Forecasting Tool (SWiiFT) project, a feasibility study funded by the European Space Agency. SWiiFT aims to improve the resilience of businesses to the physical, systemic, and financial impacts of space-weather events. Engagement with key stakeholders from organisations operating in the insurance, GNSS-dependent services, and power-grid sectors is used to identify specific customer needs for real-time alerting, historical analysis, and short- and long-range forecasting. Relevant technical requirements are derived from these needs, and the data pathways required to deliver them are mapped. This mapping considers multiple data layers and types, from solar activity observations, through to alerting and forecasting data services. By identifying strengths, limitations, and integration challenges across these data pathways, this work provides necessary inputs to risk-modelling service concepts tailored to stakeholder-defined needs. These service concepts intend to provide a foundation for improving the practical application of space-weather data in commercial risk contexts, with the goal of enhancing preparedness and situational awareness across commercial applications.
How to cite: Aplin, K., Higgins, J., Pinto Jayawardena, T., Berthoud, L., Adams, H., Iwanoczko, A., Jackman, S., and Pine, S.: Assessment and Mapping of Space-Weather Data Products for Risk Modelling Applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19508, https://doi.org/10.5194/egusphere-egu26-19508, 2026.
