Orals: Wed, 30 Apr | Room 0.94/95
The geomagnetic field is among the earliest indicators of space weather activity. However, advancements in monitoring and forecasting geomagnetic disturbances have remained relatively stagnant while other areas of space weather made significant progress. These advancements have often relied on outdated global geomagnetic indices, overlooking the importance of local assessments.
LDi-GMap is a novel product designed to address several critical needs in space weather. It generates global maps of local geomagnetic disturbances for low and mid-latitudes, regions where most end-users conduct their activities. The maps operate in real-time, providing disturbance levels in an accessible discrete colour scale (0 to ±9) like the familiar Kp index, well assimilated by the space weather community. With a temporal resolution of one minute (could be lowered depending on input data), these maps leverage data from INTERMAGNET observatories which are processed using the Local Disturbance index (LDi)—a methodology developed at the University of Alcalá to quantify geomagnetic disturbances effectively.
This product demonstrates clear advantages over traditional operational and post-event approaches that use time series of geomagnetic indices. GMap captures both negative and positive local geomagnetic disturbances that might otherwise go unnoticed. By enhancing global awareness and understanding of local geomagnetic activity, this tool addresses a significant gap in space weather.
How to cite: Guerrero, A.: World map of geomagnetic disturbances for Mid and Low latitudes (LDi-GMap), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18707, https://doi.org/10.5194/egusphere-egu25-18707, 2025.
Radial diffusion, generated by ultra-low frequency (ULF) waves, is an important process for the transport of electrons in the outer radiation belt. Ground magnetometers give us constant observations of such ULF waves but their usefulness is limited by the models used to transform ground measurements into their progenitor fields in space. A typical assumption is that of a dipole field, and so measurements can only be reliably performed during the day. We have chosen a series of magnetometer stations at different sets of geomagnetic latitudes, with stations in each set separated by several hours in longitude, and compared their Pc5 ULF power measurements, and the resulting calculated radial diffusion coefficients, from 11 years of their data. By comparing the mismatch of their results when they were in different time sectors, and for different values of Kp, we were able to assess the median deviation of measurements conducted before dawn or after dusk with those on the day side. This will be useful for projects requiring a longitudinally limited array of magnetometers or for parts of the world where such coverage is limited, such as FARBES (Forecast of Actionable Radiation Belt Scenarios).
How to cite: Dimitrakoudis, S., Balasis, G., Boutsi, A. Z., Daglis, I. A., Papadimitriou, C., Katsavrias, C., Georgiou, M., and Lichtenberger, J.: Empirical parameterisations of ULF power and drift orbit averaged radial diffusion coefficients from ground magnetometers separated in MLT, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19294, https://doi.org/10.5194/egusphere-egu25-19294, 2025.
Using auroral boundaries determined from far ultraviolet images of the aurora (Chisham et al., 2022), we have examined auroral occurrence with respect to magnetic latitude, local time and the Kp index. Our results show that auroral occurrence is highly correlated (R2>90%) with Kp between values of 0o and 5o. We use linear fits between occurrence and Kp to build a probabilistic Auroral Location Forecast (ALF) which gives the likelihood of the aurora occuring at a given magnetic latitude and local time for any level of Kp. The model includes both correlated relationships between Kp and occurrence at low latitudes and anti-correlated relationships between Kp and occurrence at high latitudes, enabling the model to replicate behaviour expected within the expanding-contracting polar cap paradigm. The model also shows higher variability in the location of the auroral boundary close to the interface between the upward Region 2 currents and downward Region 1 currents. Validation of the model returns high Brier Skill Scores for both the range of Kp used in the model creation (Kp=0 – 5, Brier Skill Score = 0.569) and the range unseen by the model (Kp=6 – 9, Brier Skill Score = 0.532) indicating that the model is skillful in predicting the location of the aurora. The results of our analysis and outputs of ALF may be of interest to space weather professionals and ‘aurora chasers’ in determining the likelihood of aurora being present, particularly when coupled with forecasts of the Kp index.
How to cite: Forsyth, C., Mooney, M., Chisham, G., Smith, A., Lao, C., and Paxton, L.: ALF - A Probabilistic Auroral Location Forecast derived from Far-Ultraviolet Auroral Boundaries and Geomagnetic Activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10990, https://doi.org/10.5194/egusphere-egu25-10990, 2025.
Reliable forecasts with sufficient advance warning of Solar Energetic Particle (SEP) events (with energies ranging from tens of keV to a few GeV and lasting for a few hours to several days), are vital for swift mitigation of threats to modern technology, spacecraft, avionics and under extreme circumstances commercial aircraft. Moreover, such forecasts are imperative for minimizing radiation hazards to astronauts especially on future Lunar or Mars missions. To this end, the HESPERIA Relativistic Electron Alert System for Exploration (REleASE) forecasting tools provide real-time predictions of the proton flux (30-50 MeV) at L1 based on relativistic and near-relativistic electron measurements by the SOHO/EPHIN and ACE/EPAM experiments using relevant proton forecasting matrices created from historical electron and proton data. Likewise, the recently developed STEREO REleASE forecasting scheme provides real-time predictions of proton flux (21-40 MeV) at the current location of STEREO-A, relying on electron measurements by the Solar Electron Proton Telescope (SEPT) and the High Energy Telescope (HET) onboard the spacecraft and relevant forecasting matrices that were derived from an analysis of 15-years of historical SEPT/HET electron and HET proton data. We, hereby, report on two novel implementations, namely HESPERIA REleASE+ and STEREO REleASE+, that combine for the first time real-time Type III solar radio burst observations by the STEREO S/WAVES instrument, as clear evidence of particle escape from the Sun, within the HESPERIA and STEREO REleASE systems respectively, aiming to substantially improve their accuracy and reduce false alarms. The identification of Type III radio bursts and their qualification as a precondition for intense SEP events occurring either at Earth or STEREO location is provided by a robust automated algorithm that recently resulted from an international collaboration between partners with complementary expertise on particles and radio data. These real-time and highly accurate forecasting schemes, which are currently operational and accessible through the Space Weather Operational Unit of the National Observatory of Athens (http://www.hesperia.astro.noa.gr), have attracted attention from various space organizations (e.g., NASA/CCMC, SRAG) and some of them are now integrated and provided through the ESA Space Weather (SWE) Service Network (https://swe.ssa.esa.int/noahesperia-federated) under the Space Radiation Expert Service Center (R-ESC).
How to cite: Malandraki, O., Tziotziou, K., Karavolos, M., Droege, H., Heber, B., Kuehl, P., Barzilla, J., Semones, E., Whitman, K., Mays, M. L., Didigu, C., J. Stubenrauch, C., Laurenza, M., Maksimovic, M., Krupar, V., and Milas, N.: Using Type III radio bursts as evidence of particle escape from the Sun for enhancing solar proton forecasting capabilities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18393, https://doi.org/10.5194/egusphere-egu25-18393, 2025.
Solar flare forecasting is an essential component in space environment forecasting. Most of the deep learning flare forecasting models constructed are based on the magnetograms of active regions. Affected by the projection effect, these models can only forecast the active region in the center of the Sun. It is difficult to meet the need of operational flare forecasting of the solar full disk. Based on the traditional solar activity parameters, in this study, the relationships between the magnetic type of the active region, area of the active region, the history of the flare outburst, the 10 cm radio flux and flares from January 1996 to December 2022 were statistically analyzed. By using the fully connected neural network, an operational flare forecasting model for solar full disk active regions was constructed. This model can forecast the eruption of the M-class or above flares of the full solar disk active regions in the next 48 h. The F1 score of the model is 0.4304, the TSS is 0.3689, and the HSS is 0.3906. The model is compared with the deep learning flare forecasting model constructed in the previous work, and the results show that the operational forecasting model constructed in this paper has a better forecasting performance. Meanwhile, in order to explore the influence of the projection effect, the solar full disk active regions flare forecasting model constructed was tested for test data within 30 degrees from the center of the solar disk, within the interval from 30 degrees to 60 degrees, and over 60 degrees, respectively. The results show that the projection effect has little influence on the flare forecast model constructed in this study. The model can be used to forecast flares in the active region of the full solar disk, and provide an effective tool for operational solar flare forecasting.
How to cite: Li, M.: Machine Learning Solar Full Disk Flare Operational Forecasting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8513, https://doi.org/10.5194/egusphere-egu25-8513, 2025.
The non-linear dynamics of the solar wind cover multiple decades of scales. These scales are not independent and are linked by turbulent processes. For instance, the energy will cascade from the largest scales determined by the dynamic and structure of the corona, to the smallest where kinetic dissipation and heating of the plasma occur. Mesoscale structures of size superior to the minute can be induced or affected by the turbulent cascade of energy or can generate a cascade. They have the right size to interact quasi-stationarily with the magnetosphere. However, are they well reproduced in space weather forecasts? We question the scale-by-scale accuracy of solar wind forecasts using turbulent-state diagnostics. These forecasts are obtained from the ensemble-analogue methodology applied to L1 measurements. We will discuss the implications of our results for space weather forecasting.
How to cite: A. Simon, P., H. K. Chen, C., and J. Owens, M.: Turbulence diagnostics of scale-by-scale accuracy of solar wind forecasts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11986, https://doi.org/10.5194/egusphere-egu25-11986, 2025.
Coronal mass ejections (CMEs) are the main drivers of severe space weather at Earth which can cause significant disruption to both satellite and ground systems, necessitating accurate predictions for timely mitigation. The complicated nature of the processes affecting CMEs as they propagate makes understanding and predicting their physical properties and global structure a challenging task, from both a fundamental and practical space weather perspective. Current challenges lie in forecasting CME arrival time and magnetic structure prior to Earth arrival, closely related to our ability to directly measure their magnetic field configuration between the Sun and 1 AU, which is critical for assessing their geo-effectiveness.
Recent opportunities provided by Solar Orbiter crossing the Sun-Earth line have allowed us to monitor upstream solar wind conditions in real-time. On 23 March 2024, Solar Orbiter observed a fast CME whilst located upstream of Earth at 0.39 AU. It provided observations of the CME magnetic field vector in real time, with a lead time of over one day before Earth impact. We present the analysis performed that led to the first real-time prediction of the geomagnetic magnitude of a severe geomagnetic storm (minimum Dst -130 nT) with sufficient accuracy and lead time. Our results demonstrate the necessity of future real-time upstream solar wind monitors towards providing accurate and timely predictions of space weather effects.
How to cite: Davies, E., Möstl, C., Weiler, E., Rüdisser, H., Amerstorfer, U., Horbury, T., O’Brien, H., Morris, J., Crabtree, A., and Fauchon-Jones, E.: Prediction of coronal mass ejection geo-effectiveness using Solar Orbiter as a far upstream monitor in real-time, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16359, https://doi.org/10.5194/egusphere-egu25-16359, 2025.
Interplanetary Coronal Mass Ejections (ICMEs) are the primary drivers of space weather disturbances, necessitating accurate and timely detection to mitigate their impact. However, traditional identification methods often rely on post-event analysis, which limits their application in real-time forecasting scenarios.
We introduce ARCANE, an operational, modular framework for the automatic, real-time detection of ICMEs in solar wind in situ data. ARCANE combines machine learning models with physics-based approaches, leveraging data from multiple spacecraft to enable early detection and enhance forecasting capabilities. The first prototype of the framework, trained on OMNI data, has been evaluated on real-time solar wind datasets, demonstrating its potential for operational use.
This presentation outlines the methodology underlying ARCANE, highlights the challenges of adapting machine learning models for streaming data, and discusses the framework’s operational implementation at the Austrian Space Weather Office. Future development directions include enhancing real-time performance, integrating early predictions of key ICME parameters, and extending ARCANE's applicability to multi-spacecraft data for improved global space weather forecasting.
How to cite: Rüdisser, H. T., Nguyen, G., Le Louëdec, J., and Möstl, C.: ARCANE: An Operational Framework for Automatic Realtime ICME Detection in Solar Wind In Situ Data , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3560, https://doi.org/10.5194/egusphere-egu25-3560, 2025.
We present the new 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, for viewing the ensemble of community-contributed models, and for comparing the performance of these models during extreme space weather events. Our overarching objective is to identify 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., Huang, Z., Baratashvili, T., Petrenko, M., Kubaryk, A., and Henley, E.: The Solar Wind Scoreboard hosted by NASA’s CCMC, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20309, https://doi.org/10.5194/egusphere-egu25-20309, 2025.
The enhanced variation of the magnetic field during severe to extreme geomagnetic storms induces a large geoelectric field in the subsurface. Grounded infrastructure can be susceptible to geomagnetically induced currents (GICs) during these events. Modelling the effect in real time and forecasting the magnitude of GICs are important for allowing operators of critical infrastructure to make informed decisions on potential impacts. As part of the UK-funded SWIMMR programme, we implemented nine research-level models into operational codes capable of running consistently and robustly to produce estimates of GICs in the Great Britain high voltage power transmission network, the high pressure pipeline network and the railway network. To improve magnetic coverage and geoelectric field modelling accuracy, three new variometer sites were installed in the UK and a three year campaign of magnetotelluric measurements at 53 sites was undertaken. The models rely on real time ground observatory data and solar wind data from satellites at the L1 Lagrange point. A mixture of empirical machine learning and numerical magnetohydrodynamic models are used for forecasting. In addition to nowcast capabilities, contextual information on the likelihood of substorms, sudden commencements and large rates of magnetic field change were developed. The final nowcast and forecast codes were implemented in a cloud-based environment using modern software tools and practices. We describe the process to move from research to operations (R2O) and give examples from the largest storms in 2024.
How to cite: Beggan, C.: Research to Operations: Implementing cloud-based real-time operational magnetic, geoelectric and GIC models for the UK, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2804, https://doi.org/10.5194/egusphere-egu25-2804, 2025.
A key space weather hazard is the generation of Geomagnetically Induced Currents (GICs) in grounded, conducting infrastructure (e.g., power networks). These GICs are driven by the changing magnetic field at the surface of the Earth and in extreme cases can cause disruption or even damage to power systems. Due to a sparsity of GIC measurements around the globe, the rate of change of the magnetic field (e.g., H’) is often used as a proxy, under the assumption that larger rates of change of the geomagnetic field will be related to larger GICs. While a range of magnetospheric processes can result in large GICs, in this work we focus on one: Sudden Commencements (SCs). SCs are rapid, coherent changes in the geomagnetic field caused by the impact of a large increase in solar wind dynamic pressure (e.g., an interplanetary shock). Globally, in one-minute cadence ground magnetic field data SCs appear relatively homogenous, lasting only a few data points. However, it has previously been found that in New Zealand SCs on the dayside have been linked to 30% larger measured GICs for a given H’. We investigate a deceptively simple question: why?
In this work we examine the sub-minute structure of SCs in New Zealand and their impact on the resulting GICs. We introduce an analytical model that describes the key features of the magnetic field signature, allowing us to fully describe the key features of an SC. The use of parameters (e.g., maximum H’) from the fitted analytical model strengthens the correlation between maximum H’ and GIC during SCs, but leaves remnant dependencies which are yet to be explained. We conduct synthetic experiments with our analytical SC model and a high resolution magnetotelluric-derived map of the southern part of New Zealand to examine which properties of an SC make it more-likely to cause disproportionately large GIC.
How to cite: Smith, A. W., Rodger, C., Pratscher, K., MacManus, D., Rae, J., Ratliff, D., Clilverd, M., Lawrence, E., Beggan, C., Richardson, G., Fogg, A., Oliveira, D., Petersen, T., and Dalzell, M.: Why do Some Sudden Commencements Generate “Disproportionate” Geomagnetically Induced Currents?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9258, https://doi.org/10.5194/egusphere-egu25-9258, 2025.
Severe geomagnetic storms can induce geomagnetically induced currents (GICs) in infrastructures like power grids, leading to transformer overheating, voltage instability, and power outages. With the rapid expansion and large-scale deployment of these systems worldwide, space weather effects have become an increasing concern. To address the urgent need to assess the impacts of space weather, a systematic modelling framework is essential. However, the absence of complete grid data has hindered the development of a GICs model during geomagnetic storms. This study proposes a systematic GICs modeling methodology that involves reconstructing power grid topology using open-source geographic data, calculating induced electric fields from magnetic disturbances, and analyzing GICs at substation nodes and transmission lines. Firstly, we accurately reconstruct the UK power grid. The high-resolution reconstructed grid model establishes a solid foundation for calculating the electromagnetic properties of key nodes and transmission lines. Next, we use geomagnetic field data from observatories during geomagnetic storms to perform geomagnetic field interpolation and induced electric field modeling, followed by the computation of GICs at substations within the grid. The model is further applied to simulate the geoelectric fields in Japan, demonstrating high accuracy. Additionally, GIC analysis during magnetic storms is conducted for a specific region in China, revealing that even low-latitude areas of China's power grid can be significantly affected by strong magnetic storms. This study establishes a systematic model that takes geomagnetic field data as input and outputs GICs at substation nodes, providing a new tool for GICs modelling induced by geomagnetic storms. It holds significant implications for assessing and managing the operational security of power grids during geomagnetic storms.
How to cite: Chen, W., Yuan, D., Zhu, Y., and Yin, T.: National-scale power grid modelling and space weather application with open-source data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3034, https://doi.org/10.5194/egusphere-egu25-3034, 2025.
This talk applies artificial intelligence (AI) to predict the whole chain of events associated with the May 2024 superstorm, including solar flares from NOAA active region (AR) 13644, Earth-directed CMEs, and a violent geomagnetic storm. Specifically, we will show that, using magnetogram cut-outs, a Vision Transformer was able to classify the evolution of the AR morphology and a video-based deep learning could have predicted the occurrence of solar flares; further, using remote sensing and in-situ observations, we will show that physics-driven models were able to improve the accuracy of CME travel time prediction and provide timely alert of its geomagnetic impact. The results showed unprecedented accuracy in predicting both solar flares and geomagnetic disturbance occurrences, as well as CME arrival, with uncertainty as low as one minute.
How to cite: Legnaro, E., Guastavino, S., Massone, A. M., and Piana, M.: AI could have predicted the whole chain of events associated with the may 2024 space weather superstorm, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19525, https://doi.org/10.5194/egusphere-egu25-19525, 2025.
On 8 May 2024, the solar active region AR13664 started releasing a series of intense solar flares. Those of class X released between 9 and 11 May 2024 gave rise to a chain of fast Coronal Mass Ejections (CMEs) that proved to be geoeffective. The Storm Sudden Commencement (SSC) of the resulting geomagnetic storm was registered on 10 May 2024 and it is, to date, the strongest event since November 2003. The May 2024 storm, named hereafter Mother’s Day storm, peaked with a Dst of -412 nT and exhibited almost no substorm signatures in the recovery phase.
This study deals with the Space Weather effects that the Mother’s Day storm had on the Mediterranean sector, with a special focus on Italy. Istituto Nazionale di Geofisica e Vulcanologia (INGV) operational manages and monitors a dense network of GNSS receivers (including scintillation receivers), ionosondes and magnetometers in the Mediterranean area, which facilitated a detailed characterization of the storm effects.
Geomagnetic observatories located in Italy recorded a SSC with a rise time of only 3 minutes and a maximum variation of around 600 nT. The most notable ionospheric effect following the arrival of the disturbance was a significant decrease in plasma density on 11 May, resulting in a pronounced negative ionospheric storm registered on both foF2 and Total Electron Content (TEC). These negative ionospheric phases were ascribed to neutral composition changes and, specifically, to a decrease of the [O]/[N2] ratio. The IRI UP IONORING data-assimilation procedure, recently developed to nowcast the critical F2-layer frequency (foF2) over Italy, proved to be quite reliable during this extreme event. Relevant outcomes of the work relate to the Rate of TEC change Index (ROTI), which showed unusually high spatially distributed values on the nights of 10 and 11 May. The ROTI enhancements on 10 May might be linked to Stable Auroral Red (SAR) arcs and an equatorward displacement of the ionospheric trough. Differently, the ROTI enhancements on 11 May might be triggered by a joint action of low-latitude plasma pushed poleward by the pre-reversal enhancement (PRE) in the post-sunset hours and wave-like perturbations propagating from the north.
The storm attracted also the general public’s attention to Space Weather effects, including mid-latitude visible phenomena like SAR arcs. This presentation outlines also the monitoring report of the Space Weather Monitoring Group (SWMG) of the INGV Environment Department and its effort to timely disseminate information about this exceptional event.
How to cite: Pignalberi, A. and the Space Weather Monitoring Group (SWMG) of the INGV Environment Department: The geomagnetic and ionospheric effects of the May 2024 Mother’s Day superstorm over the Mediterranean sector, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4340, https://doi.org/10.5194/egusphere-egu25-4340, 2025.
In this study, we present the results of a comprehensive assessment of thermosphere models under geomagnetic storm conditions, defined by a geomagnetic index ap ≥ 80. This work builds upon Bruinsma et al. (2024, DOI: 10.1051/swsc/2024027), which evaluated the performance of empirical and physics-based thermosphere models during storm periods. Utilizing models hosted at NASA's Community Coordinated Modeling Center (CCMC), we conduct an unbiased evaluation of their performance. Model simulations are analyzed across four storm phases—pre-storm, onset, recovery, and post-storm—relative to the time of peak ap. After applying a debiasing procedure based on the pre-storm phase, we compare the modeled neutral density data to high-fidelity observational datasets from TU Delft, derived from CHAMP, GOCE, GRACE, GRACE-FO, and SWARM-A satellites.
Key performance metrics, including mean density ratios, standard deviations, and correlation coefficients, are used to construct thermosphere model scorecards. These scorecards provide a valuable resource for users to identify the most suitable model for specific applications. The ultimate objective of this study is to establish a near-real-time scorecard for thermosphere model assessment at NASA/CCMC, employing consistent and standardized metrics.
How to cite: Wang, J., Yue, J., Bruinsma, S., Sypal, J., Kuznetsova, M., Mullinix, R., Wiegand, C., Siemes, C., Laurens, S., Dimarzio, P., Chou, M.-Y., and Petrenko, M.: Comprehensive Assessment of Thermospheric Models During Geomagnetic Storms at NASA/CCMC, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1673, https://doi.org/10.5194/egusphere-egu25-1673, 2025.
The Earth’s thermosphere plays a critical role in the Earth’s response to space weather and satellite drag in particular. The relationship between thermospheric variability and satellite drag is relatively straightforward: A hotter thermosphere results in higher densities at all altitudes, directly increasing satellite drag. Despite its crucial role in space weather, there are presently no operational direct measurements of the thermospheric state. Instead, today, the thermospheric state can only be estimated by driving numerical models with known space weather drivers, or by assimilating spatiotemporally averaged satellite drag data into such models.
The NOAA GOES satellites include a suite of measurements for space weather operations including magnetic field, energetic particle flux, solar soft x-ray and EUV irradiance and solar corona imagery, but historically have not provided measurements of the upper atmosphere. This may soon change. Recent NASA and NOAA funded projects have derived upper atmospheric densities from GOES solar measurements during solar occultations, which include measurements of exospheric hydrogen density from ~1000 km to 40,000 km using the GOES EXIS instrument and thermospheric O and N2 density from ~180 km to 400 km using the GOES SUVI instrument. In this presentation, we review the new datasets, discuss their capabilities and limitations, and provide examples of both longer-term (solar cycle) and transient (geomagnetic storm) variability. Additionally, we discuss what improvements could be made for future sensors intended for thermospheric measurements.
How to cite: Thiemann, E., Machol, J., Sewell, R., Bhattacharyya, D., and Bethge, C.: Exosphere and thermosphere density measurements from GOES for space weather operations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13196, https://doi.org/10.5194/egusphere-egu25-13196, 2025.
The mission of NOAA’s Space Weather Prediction Center (SWPC) is to provide space weather products and services to stakeholders by issuing alerts, watches, and warnings. For the satellite and GNSS users, different thermosphere and ionospheric products have been developed. These ionosphere-thermosphere products are based on first-principle and data-assimilative models. To operate stable 24/7, the products have gone through long cycles of development, verification, and validation. Once in operation, products need to be continuously evaluated to assess their performance in the operational environment and identify areas of improvement. The validation was named, among others, as a need in the recently released NOAA Space Weather Advisory Group (SWAG) report. Results of validations can guide improvements which can be addressed with the help of the research community. In addition, SWPC continuously interacts with customers to identify their needs and ensure that developed products and tools are useful and meet the requirements. In this presentation, we will describe the ionospheric and thermospheric data products provided by SWPC and the validation efforts. We will discuss plans to improve the data products / tools and expand the evaluation effort.
How to cite: Maute, A., Fang, T.-W., Fuller-Rowell, T., Kubaryk, A., Li, Z., Fuller-Rowell, D., Durgonics, T., Fedrizzi, M., Karol, S., Millward, G., and Curtis, B.: NOAA SPWC’s ionospheric and thermospheric data products – status and plans, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7325, https://doi.org/10.5194/egusphere-egu25-7325, 2025.
For the past three decades, ionospheric drift velocity measurements from the Super Dual Auroral Radar Network (SuperDARN) have been combined at a nominal time resolution of two minutes to produce horizontal patterns of the high-latitude convective flow. Recently, SuperDARN radars operated by the University of Saskatchewan (codenamed Borealis), which overlook much of the northern hemisphere polar cap, have been upgraded to enable a form of scanning which can be carried out every 3.7 seconds without compromising on the large field-of-views of the radars. When data from all Borealis radars are combined, a 32-fold temporal resolution improvement over traditional SuperDARN convection maps is achieved. We call this new data product the Fast Borealis Ionosphere (FBI).
The SuperDARN FBI allows for the study of highly transient and quickly evolving ionospheric phenomena (or the order of seconds) that span several thousands of kilometres, such as transient flow bursts, polar cap patches, substorm-related enhancements, and more. In this presentation, we show FBI results for events highlighting its capabilities in capturing transient ionospheric dynamics, along with several conjunction studies with satellites and other ground-based instruments (such as all-sky cameras).
How to cite: Billett, D., Rohel, R., Martin, C., McWilliams, K., and Laundal, K.: The Fast Borealis Ionosphere: New observations and insights from mapping the polar ionosphere every four seconds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1313, https://doi.org/10.5194/egusphere-egu25-1313, 2025.
The radiation environment en route to and on Mars is dominated by sporadic Solar Energetic Particle (SEP) events and omnipresent Galactic Cosmic Rays (GCRs). Both pose significant health risks for future crewed Mars missions due to high radiation exposure, increasing the long-term cancer risk. In extreme cases, acute radiation syndromes (ARS) may occur during intense SEP events, particularly if astronauts are exposed to high-dose rates during extravehicular activities.
Forecasting the occurrence and intensity of SEP events using tools such as ESPERTA, UMASEP, or REleASE is therefore crucial to provide astronauts with sufficient time to seek shelter. However, this task remains highly challenging due to the variability of SEP events, the diverse heliospheric configurations, limited data and instrumentation, as well as the complexity of prediction models. Moreover, these systems are specifically designed for the Earth or Earth-Moon system, making their applicability to Mars missions uncertain.
To adress this, we present a nowcasting system for SEP events in deep space and on the Martian surface, which serves as a reliable last backup in cases where forecasts fail. Our system is developed based on dose rate measurements from the Radiation Assessment Detector (RAD) onboard the Mars Science Laboratory (MSL) during its 7-month cruise to Mars and over 12 years of operation on the Martian surface. We demonstrate that our nowcasting system provides astronauts with sufficient time to avoid both the peak radiation exposure and the majority of the cumulative dose from SEP
events. Additionally, astronauts are informed when it is safe to leave the shelter, with total shelter durations varying from a few hours to several days depending on the specific event. Our system is easy feasible, implementable in real-life scenarios, and achieves a near-zero false alarm rate both in
deep space and on the Martian surface, as verified using data from MSL/RAD.
How to cite: Löwe, J. L., Wimmer-Schweingruber, R., Khaksarighiri, S., Hassler, D., Guo, J., Ehresmann, B., Zeitlin, C., Matthiä, D., Berger, T., Reitz, G., and Löffler, S.: Nowcasting Solar Energetic Particle Events for Mars Missions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11043, https://doi.org/10.5194/egusphere-egu25-11043, 2025.
The Radiation Assessment Detector (RAD) on the Mars Rover Curiosity has been effectively serving as a space weather monitor on the surface of Mars since Curiosity landed on the red planet in 2012. RAD has measured the impact of more than a dozen solar storms, with the frequency of events increasing as the Sun approaches solar maximum. Two relatively large events (Sept. 10, 2017 and Oct. 28, 2021) were observed as Ground Level Events (GLEs) at both Earth and Mars, separated by 180 degrees in longitude. Most recently, RAD observed its largest event to date as part of the May 2024 solar storms that impacted both Earth and Mars. We will discuss these events and their implications for space weather predictions, as well as the need for heliosphere-wide space weather monitoring to support future human exploration to Mars and beyond.
How to cite: Hassler, D. M., Wimmer-Schweingruber, R. F., Ehresmann, B., Zeitlin, C., Loewe, J. L., Khaksari, S., and Loeffler, S.: Lessons Learned from a Solar Cycle of Space Radiation Measurements on the Surface of Mars with RAD, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13647, https://doi.org/10.5194/egusphere-egu25-13647, 2025.
Space radiation is a major concern for the safety of robotic and human exploration both in the near-Earth environment and towards deep space and other planetary bodies such as the Moon. It is therefore important to characterize and predict the fluxes of the major sources of energetic particle radiation in the heliosphere including solar energetic particles (SEPs) and Galactic cosmic rays (GCRs). This involves a good understanding of the GCR modulation process and the SEP/GCR transport mechanisms as well as their interaction with the Lunar surface environment. In this talk, we will present our recent porgress in assessing the Lunar radiation environment, both during solar-quiet periods and during solar eruptions. In particular, we developed empirical functions to rapidly assess SEP-induced effective dose on the Moon under different shielding scenarios.
How to cite: Guo, J., Dobynde, M., Liu, B., and Wang, Y.: The lunar radiation environment and its contraint for crewed missions to the Moon, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1968, https://doi.org/10.5194/egusphere-egu25-1968, 2025.
As part of the Horizon Europe FARBES (Forecast of Actionable Radiation Belt Scenarios) project, we have developed a method to automatically identify past radiation belt electron enhancement events using a ground-based geomagnetic index [Bernoux et al., 2025, accepted for publication in AGU ESS]. This method has enabled the production and publication of a list of over 150 years of past radiation belt electron enhancement events. By cross-referencing with catalogues of interplanetary events (SIRs, ICMEs), we have been able to assign a possible interplanetary cause to each post-1995 radiation belt event. In this presentation, we will first present the methodology used to derive the list of events and discuss how it can become a valuable asset to the community for both space weather and space climate studies. In particular, we will demonstrate its application to the analysis of extreme events and also highlight its potential for forecasting purposes, using a simple but effective analogue ensemble-based methodology that allows us to provide forecasts of the Kp index as physically credible scenarios. By using this historical context, we can provide more robust forecasting capabilities, ultimately improving the resilience of critical infrastructure to space weather impacts.
How to cite: Bernoux, G., Nguyen, G., Gibaru, Q., and Maget, V.: A 150-Year Record of Past Radiation Belt Electron Enhancement Events: Development and Application to Space Weather Forecasting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10708, https://doi.org/10.5194/egusphere-egu25-10708, 2025.
The INTEGRAL Radiation Environment Monitor (IREM) conducts permanent observations of energetic protons and electrons along the orbit of the ESA INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL). IREM was powered on shortly after its launch on 17 October 2002 and since then it operates continuously for more than two decades. The instrument was developed in partnership between ESA, PSI and Contraves Space AG (Now Thales Alenia Switzerland) and belongs to the family of Standard Radiation Environment Monitors (SREMs). Ten identical SREMs were manufactured and are characterized by low weight, small dimensions and low power consumption. They were optimized for detection of particles with energies and fluxes typical to the Earth radiation environment. IREM onboard of INTEGRAL supports large science instruments by permanent measurements of charge particle background along the orbit. Its telemetry is instantaneously used by the spacecraft data handler enabling generation of alerts broadcasted to the rest of the payload. In parallel, IREM permanently measures the Earth radiation environment for the space weather program. These science data include regular radiation belt scans, large number of Solar Energetic Particles detections as well as numerous Forbush decreases. Observations spanned over three solar maxima provide long records on radiation belt dynamics and Cosmic Rays modulation including its spectral variations at low energies. (IREM could also detect rare, explosive events e.g., from the Soft Gamma Repeaters - magnetars.) Extensive database populated with 23 years of observations is open and available for space research community. It was recently upgraded with a new quick-look inspection utility and Python based data analysis tools.
How to cite: Hajdas, W., Buehler, P., Galli, A., Xiao, H., Nieminen, P., Evans, H., Santin, G., Grzanka, L., Bednorz, S., Peczek, K., and Swakon, J.: Two decades of space radiation environment observations with IREM monitor on INTEGRAL, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15258, https://doi.org/10.5194/egusphere-egu25-15258, 2025.
Surface charging, the process of charge deposition on covering insulating surfaces of satellites is directly linked to the space environment at a time scale of a few tens of seconds. Accurate specification of the space environment at different orbits is of a key importance. We present the operational model for low energy (< 200 keV) electrons in the inner magnetosphere, called Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM). This model in its various versions has been operating online since March 2013 (imptam.fmi.fi and imptam.engin.umich.edu) and it is driven by the real time solar wind (solar wind number density, dynamic pressure and velocity) and Interplanetary Magnetic Field (Y and Z components and total magnitude) parameters and by the real time Dst and Kp indices. The model provides the low energy electron (and proton) flux at all L-shells and at all satellite orbits, when necessary. We present several products, such as (1) 3D distributions of 1-200 keV electron fluxes (dependent on L, MLT, pitch angle and energy) inside 10 Re, (2) electron fluxes along any given satellite orbit for any given energy, (3) electron spectra at any location inside 10 Re as input to software computing potentials at satellite surfaces.
How to cite: Ganushkina, N.: Operational Inner Magnetosphere Transport and Acceleration Model (IMPTAM) for specification of radiation environment for surface charging, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10686, https://doi.org/10.5194/egusphere-egu25-10686, 2025.
Abstract
PINE (Plasma density in the Inner magnetosphere Neural network-based Empirical model) [4] is
a previously developed neural network model that uses RBSP [3] data and geomagnetic indices to
capture the global dynamics of cold plasma density in the plasmasphere. In this study, we enhance
PINE by incorporating additional data from the ERG (Exploration of Energization and Radiation
in Geospace) ARASE mission [1, 2], alongside the existing RBSP dataset. The updated model
is rigorously validated using a withheld test set and further evaluated through comparison with
global hydrogen ion distribution images obtained by the IMAGE (Imager for Magnetopause-to-
Aurora Global Exploration) mission. Model performance is analyzed under varying geomagnetic
conditions, including quiet periods, disturbed intervals, and extreme space weather events. Inte-
grating Arase data improves modeling of the inner magnetosphere, extending PINE’s applicability
to lower altitudes in the ionosphere by covering low L-shell regions and enhancing predictions of
the plasmapause configuration.
References
[1] Atsushi, K., Fuminori, T., Hirotsugu, K., Shoya, M., Ayako, M., Mariko, T., Masafumi, S., Satoko, N., Masahiro, K., Yoshizumi, M., et al., 2021. Exploration of energization and radiation in geospace (erg) plasma wave experiment (pwe) high frequency analyzer (hfa) level-3 electron density data. DOI: 10.34515/DATA.ERG-10001.
[2] Kasahara, Y., Kumamoto, A., Tsuchiya, F., Kojima, H., Matsuda, S., Matsuoka, A., Teramoto, M., Shoji, M., Nakamura, S., Kitahara, M., et al., 2021. The pwe/hfa instrument level-3 electron density data of exploration of energization and radiation in geospace (erg) arase satellite. ERG Sci. Cent. DOI: 10.34515/DATA.ERG-10001 1.
[3] Mauk, B., Fox, N.J., Kanekal, S., Kessel, R., Sibeck, D., Ukhorskiy, a.A., 2014. Science objectives and rationale for the radiation belt storm probes mission. The van Allen probes mission, 3–27. DOI: 10.1007/978-1-4899-7433-4_2.
[4] Zhelavskaya, I.S., Shprits, Y.Y., Spasojevi´c, M., 2017. Empirical modeling of the plasmasphere dynamics using neural networks. Journal of Geophysical Research: Space Physics 122, 11–227. DOI: 10.1002/2017JA024406
How to cite: Shahsavani, S., Shprits, Y. Y., Bianco, S., Haas, B., Smirnov, A., Kasahara, Y., Tsuchiya, F., Kumamoto, A., Shinbori, A., Matsuoka, A., Teramoto, M., Yamamoto, K., Shinohara, I., and Miyoshi, Y.: Enhancing PINE Model Performance through Database Extension, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17180, https://doi.org/10.5194/egusphere-egu25-17180, 2025.
The COSPAR International Space Weather Action Team (ISWAT) facilitates global
collaboration to address challenges across the field of space weather. The G3-04 team, “Internal
Charging Effects and the Relevant Space Environment”, aims to systematically assess and
improve model performance under different conditions. In response to the team's first bench-
marking challenge (long-term simulation), this study validates the Versatile Electron Radiation
Belt (VERB) code by performing simulations for the entire year of 2017 and validating the
simulation results against observations from NASA’s Van Allen Probes. No measurements from
Van Allen Probes are used in the model setups, including both initial and boundary conditions.
The only data input employed in our simulations is obtained from the Geostationary
Operational Environmental Satellites (GOES) to define the outer boundary condition. Then,
the validation is conducted by comparing simulated differential electron fluxes at 0.9 MeV and
57.27 degrees pitch angle with observations from the Van Allen Probes. Overall, our simulation
results show good agreement with observations. Model performance is evaluated by calculating
several different metrics such as root mean square error, prediction efficiency, median
symmetric accuracy, and normalized difference. Similar approach is extended to multi-year
simulations, validated against satellite data for both long-term trends and specific geomagnetic
storm events, providing a comprehensive assessment of model accuracy.
How to cite: Lyu, X., Wang, D., Shprits, Y., Teng, S., Drozdov, A., and Castillo, A.: Validation of Model Results in Response to the COSPAR ISWAT Challenge, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18472, https://doi.org/10.5194/egusphere-egu25-18472, 2025.
IonoNet is a project of a cooperative radar network of multistatic Pseudo Random Code (PRC) ionosondes for oblique ionospheric soundings placed in different points of the Italian national territory; in this way it will be possible to compare the ionospheric characteristics relative to points separated by about a few hundred km. The project activities concern the design, construction, and installation of PRC ionosondes for oblique soundings. The oblique PRC ionosondes are made up of two parts, a transmitting and a receiving one placed in various places. The project includes the installation of three transmitting ionosondes located in the north (La Spezia), center (Montelibretti (Rome) and south (Gibilmanna) of Italy and five receiving ionosondes in Castello Tesino (TN), Rocca di Papa (RM), Preturo (AQ), Duronia (CB) and Lampedusa (AG). The instrumentation will be complemented by communication and data analysis systems, including the transformation of oblique ionograms into vertical ones, to enable better comparison with the ionograms from the Italian observatories. Autoscala software will be used for the real-time generation of electron density profiles and the calculation of all propagation parameters; based on the Autoscala output, ionospheric warnings will be generated, in case of disturbed conditions. The soundings will allow to map the ionosphere over large regions for the verification of models of the global. The local disturbed ionospheric conditions will be investigated to study possible ionosphere-lithosphere coupling phenomena. The project was funded within the framework of the “National Recovery and Resilience Plan” PNRR of the INGV “Meet” within activity 9.5.
How to cite: Zirizzotti, A., Sciacca, U., Zuccheretti, E., Scotto, C., and Baskaradas, J. A.: IonoNet: An Italian network of Oblique Ionosondes , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10913, https://doi.org/10.5194/egusphere-egu25-10913, 2025.
We present newly established possible applications of HF Continuous Doppler Sounding Systems (CDSS).
Ionospheric hindcasts for purposes of LOw Frequency ARray (LOFAR) telescope are applicable for selecting only suitable LOFAR core measurements for processing. CDSS-based measurements in Belgium, specifically Spread-F intensity and actual Doppler shifts, are evaluated for this purpose.
We demonstrate also statistical relations between GNSS positioning deviations obtained using state-of-the-art Septentrio receivers as well as low-cost U-Blox receivers with wide range of ionospheric condition parameters available for Central Europe, including indicators of Travelling Ionospheric Disturbances developed within the TechTIDE project. The applicable finding is that the ionospheric F-layer Doppler frequency-shift (dF) obtained by CDSS correlates the best from among the analyzed parameters, having positive dF during positive altitude deviations (and vice-versa). We are currently extending the CDSS network, operational in Czechia, Slovakia, Germany and Belgium, as well as in Argentina, South Africa and Taiwan, to other locations of interest. The CDSS can also identify the 3-D parameters of the Medium Scale Travelling Ionospheric Disturbances and infrasound propagating in the ionosphere.
How to cite: Urbar, J., Chum, J., Verhulst, T., and Wood, A.: HF Doppler ionospheric monitoring applications: Indications of GNSS positioning accuracy degradation and for LOFAR operations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20056, https://doi.org/10.5194/egusphere-egu25-20056, 2025.
During magnetic storm, the ionpsheric plasma vertical distribution would show some variations such as in foF2, h'F, hmF2, et al., and the disturbances may deveop into irregularities as Spread-F in ionogram.
We have made a high-definition prediction of ionograms at Hainan, focusing on Spread-F forecasting, using a neural network with a GAN architecture.This is a short-term ionogram prediction model, providing well predictions for both the F trace and Spread-F features. In this study, we product ionospheric response forecasting and analysis during magnetic storm.
We chose 3 magnetic storm events in 2022, compared whether the model estimate the F trace variation, and estimate the Spread-F occur referred to real ionograms at the same time. In the results, the estimated F trace curves have a high correlation with real ones, and the model also obtain enough Spread-F features to judge their types for each event.During a storm event, the ionosphere could produce two/three different types of Spread-F, which are corresponding to different space plasma structures.
How to cite: Zheng, W., Jinhui, C., Pengdong, G., Guojun, W., and Jiankui, S.: Ionospheric response forecasting and analysis during magnetic storm by a short-term ionogram prediction model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4627, https://doi.org/10.5194/egusphere-egu25-4627, 2025.
The ionosphere is a critical factor for the performance of a wide range of communication and navigation systems. Sudden significant changes in its electron density can cause degradations in the performance of these technical systems. The variability of the ionosphere is mainly driven by solar EUV radiation, but solar wind can also modify the ionosphere significantly for periods of geomagnetic storms. The modelling of the solar wind driven variability of the ionospheric electron density is still an open challenge because of the very complex nature of the ionosphere response to the solar wind input. This study presents an attempt to reproduce the variability of the Total Electron Content (TEC) during one of the most recent extreme geomagnetic storms, which occurred on 10 May 2024.
18 years of TEC maps (2005-2023) provided by the International GNSS Service (IGS) are analysed for potential correlations with the popular geomagnetic index Kp. The analysis differentiates local and UT dependencies. The correlation results show a clear latitudinal dependence and hemispheric asymmetry. A linear regression model is generated for those conditions, where a significant correlation is detected. This statistical model is used to reproduce the storm in May 2024. The results are compared with the actual IGS TEC maps observed during the storm.
How to cite: Borries, C.: Reproducing TEC variations during May 2024 storm based on statistics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15733, https://doi.org/10.5194/egusphere-egu25-15733, 2025.
One of the main objectives of the HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) mission is the provision of alerts for potential harmful Space Weather events, such as Solar Energetic Particle (SEP) events and geomagnetic storms. Therefore, we have developed several types of methods and have evaluated their performance. In particular, we have implemented a machine learning model, based on the Random Forest Regressor algorithm, to forecast SEP events at the Earth by using HENON observations of only energetic electrons which will be made by the REPE detector. The model can provide a reliable prediction of the >10 MeV proton flux expected at the Earth with an advance of 1 hour (i.e., before an increase of the proton flux is directly measured) by taking as input: the electron flux in four differential channels between 0.25 and 10.40 MeV; their derivatives; the proton derivative in the integral channel between 7-8 and 53 MeV; these nine physical observables multiplied by the two statistical measures (mean and standard deviation). For forecasting geomagnetic storms, we have developed two methods which will exploit data of the solar wind velocity velocity V from the FCA instrument and the magnetic field (IMF) from the MAGIC instrument. The first method uses both V and the IMF southward component Bz. It provides an alert if both the VBz parameter and the Bz component have values that are above the chosen thresholds (4 mV/m and -6 nT for the VBz and the Bz) for at least 3 hours. The second method is an Artificial Neural Network (ANN) for making a real-time regression of SYM-H index. We adapted the EDDA (Empirical Dst Data Algorithm) algorithm, developed by Pallocchia et al. (2016), using only magnetic field data, to predict the Sym-H index 1 hour ahead every 20 minutes. We remark that HENON observations will allow us to compute alerts of geoeffective storms with a 10 time improvement in the lead times with respect to current predictions.
How to cite: Laurenza, M. and the HENON team: Space Weather forecasting methods for the HENON mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19588, https://doi.org/10.5194/egusphere-egu25-19588, 2025.
Space missions play a key role in predicting natural hazards like Coronal Mass Ejections (CMEs) and high fluxes of solar energetic particles that hit the Earth. In this work we carry out a preparatory study for the interpretation of the data that will be collected by a new space mission under development by the Italian ASI. The name of the space mission is HEliospheric pioNeer for solar and interplanetary threats defeNce (HENON) and its aim is to improve the forecasting capabilities of the Space Weather hazards such as SEPs/CMEs events and geoffective interplanetary disturbances. We use the 3D-MHD numerical code EUHFORIA. We insert the possible trajectories of the Henon spacecraft in EUHFORIA and we simulate the evolution of CMEs varying the initial parameters of the code. We determine from the simulation the VBz parameter that allow us to understand if a specific event can be dangerous for the environemnt around the Earth or not. Here, V is the solar wind speed, Bz is the southward component of the interplanetary magnetic field, and VBz is the motional electric field which couples with the Earth's magnetosphere and pumps energy into it. In order to have a comparison with real data, we study the event of 03/11/2021 seen by ACE and SolO. ACE and SolO were at the same position in latitude and longitude in this date, with a radial separation of about 22 million km. We make a comparison between numerical simulation and results at ACE and SolO. In this way we make a forecasting analysis in order to understand what are the events potentially dangerous for space weather. On going simulations will be used to benchmark the forecasting capabilities of EUHFORIA, too.
How to cite: Prete, G., Niemela, A. E., Poedts, S., Zimbardo, G., Chiappetta, F., Perri, S., Lepreti, F., Carbone, V., Cicalò, S., Marcucci, M. F., Pecora, F., Greco, A., Laurenza, M., Stumpo, M., and Landi, S.: A VBz parameter study of the CME propagation with EUHFORIA: a perspective from the HENON mission., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12727, https://doi.org/10.5194/egusphere-egu25-12727, 2025.
This study presents the development of five linear regression models to predict proton intensities within the energy range of 92.2 to 159.7 keV for different regions in the magnetosphere. These models are based on 14 years of data from the Cluster RAPID experiment and NASA’s OMNI database. Designed to support the operations of the Solar wind-Magnetosphere-Ionosphere Link Explorer (SMILE), the models are user-friendly and offer broad applicability for satellite mission planning and risk assessment. Analysis across four spatial regions showed that proton intensities in outer regions (YGSE > 6,Re) depend mainly on radial distance and solar wind speed, while in inner regions (YGSE < 6, Re), they are well correlated with the Z-coordinate and magnetic field topology. Spearman correlations of 0.57 to 0.72 demonstrate good predictive performance, emphasizing the potential of region-specific approaches in space weather prediction.
How to cite: Mischel, S., Kronberg, E., and Escoubet, C. P.: Evaluating Proton Intensities for the SMILE Mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-811, https://doi.org/10.5194/egusphere-egu25-811, 2025.
CLS has been providing solar radio fluxes forecasts at 10.7 and 30 cm in a daily operational routine since 2016. A posteriori forecasts were also generated since 1992, simulating the real time conditions. The forecasts are computed up to 30 days in advance using a one-hidden layer Artificial Neural Network. In the framework of ESA/S2P SWESNET project, CLS has developed a web page to provide a graphical interface to the users, as well as a data archive of the nowcast and forecast products. It is available since October 2023. In the present work, we describe the last evolutions of the service. We also show the CLS forecast performances, in comparison to those from external operational centers (SWPC, SIDC, BGS, USAF). Moreover, recent studies performed at CLS and using state-of-the-art machine learning techniques to improve the forecast are also presented.
How to cite: Yaya, P. and Souissi, R.: Status of the F10.7 and F30 solar indices forecast service at CLS: last evolutions, comparison to other centers and foreseen improvements using machine learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19179, https://doi.org/10.5194/egusphere-egu25-19179, 2025.
Gradual solar energetic particle (SEP) events are attributed to particle acceleration in shock waves driven by coronal mass ejections (CMEs). These events have significant space-weather effects, prompting ongoing efforts to develop models capable of forecasting their characteristics. Here we present a new such model, PARASOL. PARASOL is an extension of the PArticle Radiation Asset Directed at Interplanetary Space Exploration (PARADISE) test-particle simulation model of SEP transport. Its key feature is a semi-analytical description of the inner foreshock region (near the shock), constructed using simulations from the SOLar Particle Acceleration in Coronal Shocks (SOLPACS) model, which simulates proton acceleration self-consistently coupled with Alfvén wave generation upstream of the shock. PARASOL requires magnetohydrodynamic (MHD) parameters of the solar wind and the shock as inputs. To evaluate the PARASOL performance, we simulated the 12 July 2012 SEP event using the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) MHD simulation of the solar wind and CME for this event. The PARASOL simulation successfully reproduced the observed energetic storm particle (ESP) event near the shock, achieving an intensity within one order of magnitude of the observations.
How to cite: Afanasiev, A., Wijsen, N., and Vainio, R.: PARASOL: A novel simulation model for forecasting solar energetic particle events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6492, https://doi.org/10.5194/egusphere-egu25-6492, 2025.
The polarity inversion line (PIL) in active regions (AR) is considered being closely associated with solar flare eruptions. In this study, we rigorously constructed standardized datasets based on time series of different lengths using the SHARP parameters along the PIL. We compared the actual performance of the traditional logistic regression model (non-sequential) and time-series models in solar flare prediction tasks, as well as the predictive performance differences between time series models of different lengths within the CNN-BiLSTM-AT framework. The following conclusions are drawn: 1. It is verified that the prediction performance of the new SHARP parameters determined along the PIL is better. 2. In the actual prediction task, the time-series model is better than the non-sequential model, and the F1 score is almost doubled, reaching 0.59. 3. The most suitable hyperparameters of the model are estimated and the importance of the input parameters is evaluated based on the experimental results. This study provides further references and suggestions for data/model selection for flare prediction.
How to cite: Liu, S.: Flare Prediction Modeling based on the Time Series of SHARP Parameters along the Polarity Inversion Line of Active Regions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9267, https://doi.org/10.5194/egusphere-egu25-9267, 2025.
The solar wind is a continuous, magnetised outflow of plasma from the Sun's surface that shapes the heliosphere and interacts with Earth's magnetic field, driving space weather phenomena. Variability in the photospheric and solar coronal magnetic field, which continually evolves, introduces changes in the formation and propagation of the solar wind. This variability leads to the development of large-scale structures, such as High-Speed Streams (HSS) and Stream Interaction Regions (SIRs), which can trigger geoeffective events.
In this study, we present results from a 2.5D magnetohydrodynamic (MHD) simulation of the heliosphere in the equatorial plane to assess the importance of incorporating the time-dependent nature of solar conditions through boundary conditions. Such boundary conditions are imperative to capture the variable behaviour of the solar magnetic field and coronal plasma. Thus, the MHD simulation is driven using six-hourly updated photospheric magnetograms to feed the Wang-Sheeley-Arge (WSA) coronal model over a 10-day period. These evolving WSA maps serve as the inner boundary conditions at 0.1 AU for the MHD simulation. The solar wind is modelled by solving the ideal MHD equations with an adiabatic equation of state, incorporating heating through a reflection-driven turbulent heating mechanism. The resulting simulation can capture time-dependant effects in the heliosphere that are absent when performing steady-state simulations using a single WSA map. The simulation outputs are validated against spacecraft data from 1 AU.
Previous studies have demonstrated that the time-dependent evolution of WSA maps captures large-scale heliospheric features with greater fidelity. An alternative approach, utilising time-dependent coronal simulations instead of WSA maps, has been shown to reproduce evolutionary features in solar wind stream structures that steady-state simulations fail to resolve. More recently, time-dependent boundary conditions driving a hydrodynamic wind model have highlighted their importance for improved forecasting at 1 AU, particularly for longer lead times, by accounting for evolving solar wind features.
The present study builds on these efforts by developing a robust and efficient simulation tool for the community, focusing on the equatorial plane which is a main region of interest for predicting space weather. It extends the impact of boundary-driven solar wind modelling from hydrodynamic approaches to an MHD framework, while also analysing forecast lead times at 1 AU. This work aims to facilitate further research into the role of time-dependent boundary conditions in modelling space weather and coronal mass ejection (CME) propagation.
How to cite: Sishtla, C., Chen, C. H. K., Pomoell, J., and Barnard, L.: Forecasting solar wind parameters at 1 AU using time-dependant magnetohydrodynamic simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6047, https://doi.org/10.5194/egusphere-egu25-6047, 2025.
Predicting the geomagnetic effects of coronal mass ejections (CMEs) remains a significant challenge in space weather forecasting. Spacecraft positioned upstream of L1, referred to as sub-L1 monitors, present a promising observational approach to addressing this problem. Such monitors have the potential to enhance both the lead-time and accuracy of geomagnetic storm forecasts.
In a hindcast analysis, we demonstrate that the geomagnetic impact of the May 2024 superstorm—a complex event involving at least five interacting CMEs that led to the strongest geomagnetic storm since 2003—was reasonably well reproduced using real-time data from the STEREO-A spacecraft. This spacecraft, positioned at 0.956 AU and 12.6° west of Earth, acted as a sub-L1 monitor during this event and observed the associated interplanetary shock 2.57 hours prior to its detection at L1.
Between November 2022 and June 2024, STEREO-A passed 0.05 AU ahead of the Wind spacecraft at ±15° heliospheric longitude, corresponding to the longitudinal separation for which monitoring below L1 is considered feasible. During this time interval, ten severe geomagnetic storms (Dst < -100 nT) and several moderate storms (Dst < -50 nT) were observed. This favourable spacecraft configuration enables a first robust statistical analysis of the utility of sub-L1 monitoring for space weather forecasting.
To refine our methodology and address unresolved questions from the May 2024 analysis, we apply solar wind-to-Dst models to both STEREO-A and L1 solar wind data. By comparing model outputs to observed geomagnetic indices, we quantify the predictive performance and disentangle contributions from observational and modelling uncertainties. Furthermore, we examine the influence of longitudinal separation between the spacecraft on prediction accuracy.
With this statistical analysis we aim to establish a critical benchmark for the development of future missions that leverage upstream monitoring to advance space weather forecasting capabilities.
How to cite: Weiler, E., Möstl, C., Davies, E., Amerstorfer, T., Lugaz, N., Amerstorfer, U., Veronig, A., and Haberle, V.: Advancing Space Weather Forecasting with Sub-L1 Monitors: A Statistical Analysis , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10611, https://doi.org/10.5194/egusphere-egu25-10611, 2025.
