ST4.4 | Nowcasting, forecasting, operational monitoring and post-event analysis of the space weather and space climate in the Sun-Earth system
EDI
Nowcasting, forecasting, operational monitoring and post-event analysis of the space weather and space climate in the Sun-Earth system
Convener: Guram Kervalishvili | Co-conveners: Maike Bauer, Yulia Bogdanova, Therese Moretto Jorgensen, Claudia Borries, Dario Del Moro, Evangelos Paouris
Orals
| Thu, 18 Apr, 08:30–12:30 (CEST)
 
Room 0.51
Posters on site
| Attendance Fri, 19 Apr, 10:45–12:30 (CEST) | Display Fri, 19 Apr, 08:30–12:30
 
Hall X3
Posters virtual
| Attendance Fri, 19 Apr, 14:00–15:45 (CEST) | Display Fri, 19 Apr, 08:30–18:00
 
vHall X3
Orals |
Thu, 08:30
Fri, 10:45
Fri, 14:00
This session focuses on the intricate dynamics of space weather and space climate, investigating the Sun-Earth system's interactions across various timescales in the heliosphere, magnetosphere, ionosphere, thermosphere and lower atmosphere. It addresses the collective impact of phenomena such as coronal mass ejections, interplanetary shocks, co-rotating interaction regions, and solar energetic particles. Understanding and predicting these events is crucial for mitigating their effects on critical infrastructure, space-based technologies, and terrestrial systems.

The discussion encompasses the current state of space weather products, featuring forecast and nowcast services, satellite observations, the use of data assimilation for enhancing predictions, as well as the production of geomagnetic and ionospheric indices. Contributions employing a cross-disciplinary approach to advance our understanding of space weather and space climate are encouraged, particularly those addressing the impact of space weather on applications such as aviation, power grids, and space flights.

The session also highlights the significant progress in predictive capabilities over the past decade. This includes advancements in observational and modeling techniques, with a specific emphasis on challenges such as acquiring real-time, observation-based data, tracking solar wind transients, and evaluating predictive models. Presentations will showcase ongoing observational and modeling work, offering insights into the current landscape of space weather forecasting and potential future opportunities. By providing a comprehensive overview, the session aims to guide future scientific efforts and inform strategic planning for space missions in the dynamic field of space weather.

Orals: Thu, 18 Apr | Room 0.51

Chairpersons: Guram Kervalishvili, Maike Bauer, Yulia Bogdanova
08:30–08:35
08:35–08:55
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EGU24-18152
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solicited
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Highlight
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Virtual presentation
Anja Stromme

The Near Earth Space Environment is a complex and interconnected system of systems, and the home of a multitude of physical processes all contributing to space weather and space climate effects, and hence collaboration across traditional boundaries is essential in order to progress in our understanding of and our capability to predict Space Weather.  

The ESA Swarm Earth Explorer mission, launched 22. September 2013 has completed almost a solar cycle in orbit and is in its nature a true system science mission in its endeavor to unravel our planets invisible shield on a magnetic journey from the Earth’s core to the magnetosphere and nearly everything in-between.

In this presentation we will highlight both the direct contributions the Swarm mission has had and continues to have for the space weather community through constantly evolving products and services, but also how it has acted as a catalyst to help utilize other data sources in order to enhance our understanding of space weather processes.

How to cite: Stromme, A.: How the ESA Swarm mission can contribute to Space Weather and Space Climate , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18152, https://doi.org/10.5194/egusphere-egu24-18152, 2024.

08:55–09:05
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EGU24-17944
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On-site presentation
Roberta Forte, Enkelejda Qamili, Nicola Comparetti, Lars Tøffner-Clausen, Stephan Buchert, Johnathan Burchill, Christian Siemes, Alessandro Maltese, Anna Mizerska, María José Brazal Aragón, Lorenzo Trenchi, Elisabetta Iorfida, Irene Cerro Herrero, Berta Hoyos Ortega, Giuseppe Albini, Antonio De la Fuente, and Anja Stromme

On 22nd November 2023 Swarm ESA’s Earth Explorer mission celebrated 10 years in Space, characterizing Earth’s geomagnetic, ionospheric and electric fields, for a better understanding of our planet’s interior and its environment. After a decade in orbit, the mission is still in excellent shape and continues to contribute to a wide range of scientific studies, from the core of our planet, via the mantle and the lithosphere, to the ionosphere and interactions with Solar wind, opening the door for many innovating applications largely beyond its original scope.

Moreover, the processing algorithms have been continuously improved since the beginning of the mission, to cope with the evolving needs of the scientific community, to keep providing excellent quality data and to maintain good instruments performances.

In April 2023 a “Fast” processing chain has been transferred to operations, providing Swarm L1B products with a minimum delay respect to the acquisition. This Fast data production adds significant value to Swarm mission’s scientific purposes and applications, making it eligible for monitoring Space Weather phenomena, modelling and nowcasting the evolution of several geomagnetic and ionospheric events.

This work provides an overview of the Swarm enhanced data processing chain, instruments performances, Fast chain applications and upcoming evolutions, together with other innovative Swarm-based data products and services.

How to cite: Forte, R., Qamili, E., Comparetti, N., Tøffner-Clausen, L., Buchert, S., Burchill, J., Siemes, C., Maltese, A., Mizerska, A., Brazal Aragón, M. J., Trenchi, L., Iorfida, E., Cerro Herrero, I., Hoyos Ortega, B., Albini, G., De la Fuente, A., and Stromme, A.: ESA Swarm mission after 10 years in Space: new opportunities through enhanced processors and data quality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17944, https://doi.org/10.5194/egusphere-egu24-17944, 2024.

09:05–09:15
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EGU24-6683
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Highlight
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On-site presentation
Astrid Maute, Tzu-Wei Fang, Timothy Fuller-Rowell, Adam Kubaryk, Zhuxiao Li, George Millward, and Brian Curtis

The coupled Whole Atmosphere Model - Ionosphere Plasmasphere Model (WAM-IPE) has been transitioned into operations at the NOAA Space Weather Prediction Center (SWPC) in 2021. WAM is an extension of the NOAA National Weather Service (NWS) operational model and calculates Earth’s global three-dimensional, time-dependent, neutral atmosphere from the surface up to the thermosphere at 10^-7 hPa (400-600 km). WAM is coupled to the global ionosphere-plasmasphere electrodynamics (IPE) model which extends to several Earth radii. The model is providing a forecast of the neutral and plasma environment that impacts the GNSS positioning, global communications, and collision avoidance for space traffic management.

In this presentation, we describe the different Concept of Operations (CONOPS) which provide nowcast and forecast with WAM-IPE and the validation efforts. We discuss several developments based on the operational version of WAM, which includes the data-assimilation system for WAM and the high-resolution WAM-IPE. A recent testbed exercise targeted satellite operator and solicited feedback from operators and service providers which informs future developments.  We will conclude with the future plans to update WAM to the Finite-Volume Cubed-Sphere Dynamical Core (FV3) version.

How to cite: Maute, A., Fang, T.-W., Fuller-Rowell, T., Kubaryk, A., Li, Z., Millward, G., and Curtis, B.: Operation and developments of the Whole-Atmosphere-Model at NOAA Space Weather Prediction Center, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6683, https://doi.org/10.5194/egusphere-egu24-6683, 2024.

09:15–09:25
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EGU24-7575
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Highlight
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On-site presentation
Sean Bruinsma, Sophie Laurens, Jack Wang, Jia Yue, and Maria Kuznetsova

Appropriate metrics to track the progress over time of thermosphere models, both first principle and semi-empirical, were developed. Secondly, the high quality and high-spatial resolution neutral density data sets of TU Delft covering long intervals of time (i.e. the complete CHAMP, GRACE, GRACE-FO and GOCE mission datasets) were selected. The neutral density observations can then be used to verify model accuracy with respect to latitude-longitude-local time variations, and solar and geomagnetic activity levels and seasonal variations, respectively. The density data and metrics together allow benchmarking of the models, and improvement from one release to the next can be quantified. An assessment tool was implemented at CCMC specifically for storm-time assessment, while global assessment capacity is currently also under development.

In this study, we present the results of comparisons with storms from 2001-2022 for the DTM2020, NRLMSISE-00 and JB2008 models. Secondly, the CCMC CAMEL model assessment tool will be shown and the model score cards that it can generate. These score cards allow easy and objective comparison of the performance of thermosphere models.

How to cite: Bruinsma, S., Laurens, S., Wang, J., Yue, J., and Kuznetsova, M.: Thermosphere model assessment and implementation at NASA/CCMC, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7575, https://doi.org/10.5194/egusphere-egu24-7575, 2024.

09:25–09:35
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EGU24-4913
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ECS
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On-site presentation
Chih Ting Hsu and Nicholas Pedatella

Ensemble Data assimilation is a state-of-the-art method that can combine the observation information into a numerical model and further improve the performance of numerical weather prediction of the thermosphere and ionosphere.  The thermospheric and ionospheric weather are highly sensitive to the variation of forcings from above, including the solar irradiance and the magnetospheric forcings, and forcings from below, including waves and tides from the lower atmosphere. However, these forcings are hard to quantify. Building up the connection between the uncertainty of the forcings and the variability of a numerical model of the thermosphere and ionosphere that is used in a data assimilation system is a critical issue in thermospheric and ionospheric weather prediction.

This study aims to advance our understanding of how solar irradiance variability and tide and wave variability drive the variability of Earth's thermosphere and ionosphere and improve our capability to represent this driver-response relationship in physics-based models using ensemble data assimilation. This study focuses on the National Center for Atmospheric Research’s (NCAR’s) Whole Atmosphere Community Climate Model – eXtended (WACCM-X). In the WACCM-X, the solar irradiance is determined by an empirical model, such as EUVAC, or by a real data set, and the waves and tides are generated self-consistently from the lower atmosphere in the model.

We first try to quantify the solar irradiance variability in different wavelengths based on real data, including data from the Extreme Ultraviolet Variability Experiment (EVE) on Solar Dynamics Observatory (SDO) and the X-ray Photometer System (XPS)and the Solar Stellar Irradiance Comparison Experiment (SOLSTICE) on Solar Radiation and Climate Experiment (SORCE). Then, we quantify and qualify the response of the thermosphere and ionosphere in the WACCM-X to both the variation of solar irradiance and waves and tides by launching a set of ensemble simulation experiences. This will help prove the predictability of the thermospheric and ionospheric weather. 

How to cite: Hsu, C. T. and Pedatella, N.: Effects of Forcing Uncertainties on the Thermospheric and Ionospheric Ensemble-based data assimilation., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4913, https://doi.org/10.5194/egusphere-egu24-4913, 2024.

09:35–09:45
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EGU24-9309
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ECS
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On-site presentation
Daniel Billett, Remington Rohel, Kathryn McWilliams, Carley Martin, Karl Laundal, and Jone Reistad

Over the last few years, the five SuperDARN HF ionospheric radars operated by the University of Saskatchewan have been upgraded to digital systems that utilise the flexibility and reliability of software defined radios (SDRs). SDRs allow for a vastly greater control of radar transmit and receive operations, bringing with them new capabilities for scientific experiments that were previously not feasible on analogue hardware. This next generation of SuperDARN radar is named Borealis. 

 

One new radar operating mode implemented at the Borealis radars has been full field-of-view imaging. On traditional SuperDARN radars, one full scan of an entire field-of-view (an area encompassing thousands of kilometres at F-region ionospheric altitudes) takes approximately 1 minute as each of the 16 beam directions is sequentially integrated over. With Borealis, every beam direction can be probed (or “imaged”) simultaneously, providing a 16-fold improvement in scan temporal resolution to 3.5 seconds.

 

We present a new ionospheric data product derived from Borealis imaging mode data: high time resolution mapping of polar E x B drifts. In contrast to traditional SuperDARN ionospheric convection patterns which are nominally derived every two minutes on a coarse global grid, Borealis convection patterns are derived locally over the Canadian polar cap every few seconds. This not only provides the opportunity to study mesoscale ionospheric phenomena like polar cap patches, flow channels, and substorms, but also allows for doing so at a temporal resolution not previously possible without compromising spatial coverage.

How to cite: Billett, D., Rohel, R., McWilliams, K., Martin, C., Laundal, K., and Reistad, J.: High time resolution mapping of polar ionospheric flows with the SuperDARN Borealis systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9309, https://doi.org/10.5194/egusphere-egu24-9309, 2024.

09:45–09:55
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EGU24-1512
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ECS
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Highlight
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On-site presentation
Erik Schmölter and Jens Berdermann

Safe and efficient management of the constantly growing air traffic is an important task. For that reason, the international civil aviation organization (ICAO) approved Automatic Dependent Surveillance (ADS) system is used to share information (e.g. position, altitude and speed) between aircraft and air traffic control units. This improves the situational awareness and visibility of aircraft but also the environmental impact and air space capacity. Both applications of ADS, Broadcast (B) and Contract (C), rely on satellite-based communication and navigation services, which can be significantly disturbed by space weather impacts (e.g. loss of the signal and position errors). Therefore, related impacts are also observed for ADS records especially during extreme space weather events. We will present such impacts for both, ADS-B and ADS-C, with first results from an analysis covering periods with solar flares and geomagnetic storms. We will also discuss the challenge of differentiating space weather impacts from other influences. Finally, we will give an outlook how monitoring these impacts could contribute to space weather services.

How to cite: Schmölter, E. and Berdermann, J.: Significance of space weather impacts on Automatic Dependent Surveillance (ADS) data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1512, https://doi.org/10.5194/egusphere-egu24-1512, 2024.

09:55–10:05
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EGU24-17954
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On-site presentation
Philippe Yaya, Roiya Souissi, Marie Cherrier, and Ali Naouri

The International Civil Aviation Organization (ICAO) has set up a space weather service for monitoring and raising alerts in case of moderate or severe potential impact on aviation, and covering three domains: GNSS, Radiation and HF Communications. This service is operational since November 2019 and is working in a bi-weekly rotation of four global centers: SWPC (US Space Weather Prediction Center), PECASUS (consortium of 9 European States), CRC (China-Russia Consortium) and ACFJ (Australia-Canada-France-Japan). CLS (Collecte Localisation Satellites), a member of ACFJ, is a subsidiary of the French Space Agency and responsible for delivering near real-time ionospheric scintillation maps. The input data is based on a worldwide network of GNSS receivers, composed of various regional and global networks. The work presented here summarizes the adopted algorithms and pre-processing tasks leading to generate the nowcast maps. The results of a validation work are shown (comparison of indices from geodetic receivers and scintillation monitors) as well as a focus on severe events and their effect on aviation. Finally, taking advantage of a 4-years long data base, the status of a forecasting scintillation model is presented, taking care of separating the EPBs (Equatorial Plasma Bubbles) and geomagnetic storms origins.

How to cite: Yaya, P., Souissi, R., Cherrier, M., and Naouri, A.: Ionospheric Scintillation Nowcasting and Forecasting for Civil Aviation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17954, https://doi.org/10.5194/egusphere-egu24-17954, 2024.

10:05–10:15
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EGU24-11055
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Highlight
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Virtual presentation
Ciaran Beggan, Ellen Clarke, Ewelina Lawrence, Eliot Eaton, John Williamson, Keitaro Matsumoto, and Hisashi Hayakawa

Dedicated scientific measurements of the strength and direction of the Earth's magnetic field began at Greenwich and Kew observatories in London, UK, in the middle of the 19th century. Using advanced techniques for the time, collimated light was focussed onto mirrors mounted on free-swinging magnetized needles which reflected onto photographic paper, allowing continuous analogue magnetograms to be recorded. By good fortune, both observatories were in full operation during the so-called Carrington storm in early September 1859 and its precursor storm in late August 1859. Based on digital images of the magnetograms and information from the observatory yearbooks and scientific papers, it is possible to scale the measurements to SI units and extract quasi-minute cadence spot values. However, due to the magnitude of the storms, the periods of the greatest magnetic field variation were lost as the traces moved off-page. We present the most complete digitized magnetic records to date of the ten-day period from 25th August to 5th September 1859 encompassing the Carrington storm and its lesser recognised precursor on the 28th August. We demonstrate the good correlation between observatories and estimate the instantaneous rate of change of the magnetic field.

How to cite: Beggan, C., Clarke, E., Lawrence, E., Eaton, E., Williamson, J., Matsumoto, K., and Hayakawa, H.: Digitized continuous magnetic recordings for the August/September 1859 storms from London, UK, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11055, https://doi.org/10.5194/egusphere-egu24-11055, 2024.

Coffee break
Chairpersons: Maike Bauer, Guram Kervalishvili, Yulia Bogdanova
10:45–10:50
10:50–11:10
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EGU24-7852
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solicited
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Highlight
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On-site presentation
Eleanna Asvestari

Due to their socioeconomic impact, the forecasting of coronal mass ejections (CMEs) is of paramount importance. This has led to decades of model development based on the knowledge we have gained from observations and our understanding of the physical processes that take place and could explain these observations. Currently we have empirical and magnetohydrodynamic (MHD) models that show promising results in CME forecasting. However, these are observationally driven and strongly dependent on the quality and quantity of observations we have at our disposal. The vast majority of our CME observations are made on the ecliptic plane. And in situ observations are collected by a few spacecraft scattered in the same plane. In the case of MHD models, we are also limited by numerical implementation issues and our understanding of the CME plasma and magnetic structure, as well as the physical processes CMEs undergo during their journey in the heliosphere.

EUHFORIA (EUropean Heliospheric FORecasting Information Asset), is a state-of-the-art 3-dimensional MHD model that can simulate CMEs in the inner heliosphere, either as hydrodynamic pulses (cone model) or magnetised flux ropes (spheromak, FRiED-3D, torus). Throughout this presentation we will explore the observable parameters the CME implementations in EUHHFORIA depend on and how they are impacted by observational limitations. We will also discuss the performance of the spheromak CME and how we can track it with a novel tool. Last but not least, we will discuss the physical processes manifested in spheromak CME simulations and how they can shed light on the evolution of 3D flux ropes in the interplanetary space depending on the ambient medium (solar wind and interplanetary magnetic field) they are embedded in.

How to cite: Asvestari, E.: Lessons learned from modelling flux ropes with EUHFORIA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7852, https://doi.org/10.5194/egusphere-egu24-7852, 2024.

11:10–11:20
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EGU24-4076
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On-site presentation
Christina Kay and Erika Palmerio

Predicting the impacts of coronal mass ejections (CMEs) is a major focus of current space weather forecasting efforts. Typically, CME properties are reconstructed from stereoscopic coronal images and then used to forward model a CME's interplanetary evolution. Knowing the uncertainty in the coronal reconstructions is then a critical factor in determining the uncertainty of any predictions. A growing number of catalogs of coronal CME reconstructions exist, but no extensive comparison between these catalogs has yet been performed. Here we develop a Living List of Attributes Measured in Any Coronal Reconstruction (LLAMACoRe), an online collection of individual catalogs, which we intend to continually update. In this first version, we use results from 24 different catalogs with 3D reconstructions using STEREO observations between 2007-2014. We have collated the individual catalogs, determining which reconstructions correspond to the same events. LLAMACoRe contains 2954 reconstructions for 1862 CMEs. Of these, 511 CMEs contain multiple reconstructions from different catalogs. Using the best-constrained values for each CME, we find that the combined catalog reproduces the generally known solar cycle trends. We determine the typical difference we would expect between two independent reconstructions of the same event and find values of 4.0 deg in the latitude, 8.0 deg in the longitude, 24.0 deg in the tilt, 9.3 deg in the angular width, 0.1 in the shape parameter kappa, 115 km/s in the velocity, and 2.5e15 g in the mass. These remain the most probable values over the solar cycle, though we find more extreme outliers in the deviation toward solar maximum.

How to cite: Kay, C. and Palmerio, E.: Collection, Collation, and Comparison of 3D Coronal CME Reconstructions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4076, https://doi.org/10.5194/egusphere-egu24-4076, 2024.

11:20–11:30
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EGU24-8210
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ECS
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On-site presentation
Sabrina Guastavino, Michele Piana, Anna Maria Massone, Francesco Marchetti, Federico Benvenuto, Alessandro Bemporad, Roberto Susino, and Daniele Telloni

The study of space weather impacts of coronal mass ejections (CMEs) requires the formulation, implementation and validation of predictive approaches to address issues such as the arrival of CMEs to Earth and, if so, its arrival time and speed. The problem of predicting the CMEs’ travel times has been addressed by means of empirical models, physics-based models, and artificial intelligence techniques. In this talk, we propose a physics-driven artificial intelligence (AI) method, in which we encode physical information into the process of neural network training. Specifically we include the drag-based model in the definition of the loss functions to minimize during the training process of a cascade of two neural networks fed with both remote sensing and in situ data. We show that including physical information in the AI architecture improves its predictive capabilities and the proposed physics-driven AI method leads to more accurate and robust results for the CMEs’ travel time prediction with respect to the purely-data driven AI approach.

How to cite: Guastavino, S., Piana, M., Massone, A. M., Marchetti, F., Benvenuto, F., Bemporad, A., Susino, R., and Telloni, D.: Encoding the drag-based model in the artificial intelligence training process to predict CMEs’ travel times, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8210, https://doi.org/10.5194/egusphere-egu24-8210, 2024.

11:30–11:40
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EGU24-13486
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Virtual presentation
Noé Lugaz, Florian Regnault, Sahanaj Banu, Nada Al-Haddad, Bin Zhuang, Christina Lee, Charles J. Farrugia, Christian Möstl, Reka M. Winslow, Emma Davies, Camilla Scolini, Wenyuan Yu, and Toni Galvin

In-situ measurements from the Sun-Earth Lagrangian L1 point typically provide a 20-minute to 1-hour advanced warning of incoming interplanetary (IP) shocks, magnetic clouds before impact at the nose of Earth's magnetopause. Sub-L1 monitors may provide measurements sunward of the L1 point to improve the lead times for such transients to several hours, and various mission architecture have been proposed for more than 25 years. Because CMEs and shocks do not propagate exactly radially, the location of such a monitor with respect to the Sun-Earth line is a key parameter to take into account when designing such missions. Here, we highlight some recent results and measurements of CMEs that show that small angular separations may result in drastic differences in the CME properties measured by two spacecraft, and examples showing that CME evolution over a few hours may differ significantly from the average evolution as obtained from statistical studies over several decades. We highlight how a pathfinder mission is required to better understand the variation of properties within CMEs on moderate scales and the evolution of CMEs over a few hours. Such an improved knowledge will then allow for a dedicated fleet of operational monitors that will improve the lead time of space weather forecasting without a loss of accuracy

How to cite: Lugaz, N., Regnault, F., Banu, S., Al-Haddad, N., Zhuang, B., Lee, C., Farrugia, C. J., Möstl, C., Winslow, R. M., Davies, E., Scolini, C., Yu, W., and Galvin, T.: The Space Weather Research on Coronal Mass Ejections Required Before Operational Sub-L1 Monitors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13486, https://doi.org/10.5194/egusphere-egu24-13486, 2024.

11:40–11:50
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EGU24-5109
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ECS
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Highlight
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On-site presentation
Tinatin Baratashvili, Michaela Brchnelova, Jin Han Guo, Andrea Lani, and Stefaan Poedts

Space weather events can affect Earth. In order to mitigate damage, space weather modelling tools have been implemented. In this study, the full MHD chain is presented, starting from the Sun, with a 3D MHD data-driven coronal model COCONUT up to 0.1 AU, where the code is coupled to Icarus, an ideal 3D MHD heliospheric modelling tool.

COCONUT (Perri, Leitner et al. 2022, COolfluid COrona Unstructured) is a data-driven coronal model that was recently developed at the Centre for Mathematical Plasma Astrophysics, KU Leuven. It is a global 3-D MHD model based on the COOLFluiD code (Yalim et al. 2011, Lani et al. 2014). The advantage of the COCONUT model lies in its efficient, optimised implementation. It uses a time-implicit backward Euler scheme and unstructured computational grid, which avoids singularities near the poles and enables using high CFL numbers to rapidly converge to steady state for realistic simulations on modern HPC systems. In order to obtain realistic solar wind conditions at 0.1AU, the source terms have been implemented in the MHD equations, namely, the approximated coronal heating function, radiative losses and the thermal conduction. The output of the COCONUT coronal model is used as input boundary conditions for plasma variables in the heliospheric model Icarus.

Icarus (Verbeke et al. 2022, Baratashvili et al. 2022) is a new heliospheric wind and CME evolution model that is implemented within the framework of MPI-AMRVAC (Xia et al., 2018) and introduces new capabilities for better and faster space weather forecasts. Advanced numerical techniques, such as solution adaptive mesh refinement (AMR) and radial grid stretching, are implemented. These techniques result in optimised computer memory usage and a significant execution speed-up, which is crucial for forecasting purposes.

The modelled 3D data in the solar corona and heliosphere are presented for assessing the model capabilities. The density profiles near the Sun are compared to tomography data. The time-series profiles of different variables at Earth are compared to observational data. As a result, the COCONUT+Icarus model chain represents the full MHD model covering the domain from Sun to Earth, which allows more in depth studies and understanding of different physics phenomena, e.g. shock formation, erosion, and deformation, compared to empirical or semi-empirical models. 

How to cite: Baratashvili, T., Brchnelova, M., Guo, J. H., Lani, A., and Poedts, S.: A novel full MHD forecasting model chain from Sun to Earth: COCONUT+ Icarus, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5109, https://doi.org/10.5194/egusphere-egu24-5109, 2024.

11:50–12:00
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EGU24-10110
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Highlight
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On-site presentation
Yuri Shprits, Stefano Bianco, Dedong Wang, Bernhard Haas, Muhammad Asim Khawaja, Karina Wilgan, Tony Arber, Keith Bennett, Ondrej Santolik, Ivana Kolmasova, Ulrich Taubenschuss, Mike Liemohn, Bart van der Holst, Julien Forest, Arnaud Trouche, and Benoit Tezenas du Montcel

The European Union's Horizon 2020 Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) project was successfully concluded in 2023. This project provides real-time space weather forecast initiated from the solar observations as well as predictions of radiation in space and its effects on satellite infrastructure. Real-time predictions of particle radiation and cold plasma density allow for evaluation of surface charging and deep dielectric charging. The project provides a 1-2-day probabilistic and data assimilative forecast of ring current and radiation belt environments, which allows satellite operators to respond to predictions that present a significant threat. As a backbone of the project, we use the state-of-the-art codes that currently exist and adapt existing codes to perform ensemble simulations and uncertainty quantifications. Within PAGER, a number of innovative tools was obtained, including data assimilation and uncertainty quantification, new models of near-Earth electromagnetic wave environment, ensemble predictions of solar wind parameters at L1, and data-driven forecast of the geomangetic Kp index and plasma density. In this presentation, we show the overview of the outcomes and the products obtained within the project. The developed codes may be used in the future for realistic modelling of extreme space weather events.

How to cite: Shprits, Y., Bianco, S., Wang, D., Haas, B., Khawaja, M. A., Wilgan, K., Arber, T., Bennett, K., Santolik, O., Kolmasova, I., Taubenschuss, U., Liemohn, M., van der Holst, B., Forest, J., Trouche, A., and Tezenas du Montcel, B.: Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) – project conclusion, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10110, https://doi.org/10.5194/egusphere-egu24-10110, 2024.

12:00–12:10
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EGU24-10862
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On-site presentation
Olga E. Malandraki, Arik Posner, Michalis Karavolos, Kostas Tziotziou, Fanis Smanis, Monica Laurenza, Janet Barzilla, Edward Semones, Kathryn Whitman, M. Leila Mays, Chinwe Didigu, Christopher J. Stubenrauch, Bernd Heber, Patrick Kuehl, Milan Maksimovic, Vratislav Krupar, and Nikolas Milas

Providing reliable forecasts of Solar Energetic Particle (SEP) events is mandatory for human spaceflight beyond low-Earth orbit, especially outside the Earth's magnetosphere. High-energy SEPs are tracked because they penetrate deeper into the terrestrial atmosphere and contribute to the radiation dose aboard spacecraft specifically over Canada and the Southern Indian Ocean, due to the tilt of the Earth on its axis. Based on the Relativistic Electron Alert System for Exploration (REleASE) forecasting scheme], the HESPERIA REleASE product was developed by the HESPERIA H2020 project (Project Coordinator: Dr. Olga Malandraki) and generating real-time predictions of the proton flux (30-50 MeV) at L1, making use of relativistic and near-relativistic electron measurements by the SOHO/EPHIN and ACE/EPAM experiments, respectively. The HESPERIA REleASE tools are operational through the Space Weather Operational Unit of the National Observatory of Athens, accessible through the dedicated website (http://www.hesperia.astro.noa.gr). HESPERIA REleASE has attracted attention from various space organizations (e.g., NASA/CCMC, SRAG), due to the real-time, highly accurate and timely performance offered. ESA selected the HESPERIA REleASE products that were integrated and provided through the ESA Space Weather (SWE) Service Network (https://swe.ssa.esa.int/noa-hesperia-federated) under the Space Radiation Expert Service Center (R-ESC). Solar cycle 25 solar radiation storms successfully predicted by HESPERIA REleASE are presented and discussed. Moreover, we present an innovative upgrade implemented, namely HESPERIA REleASE+, that is using the novel approach of combining for the first time real-time type III solar radio burst observations by the STEREO S/WAVES instrument, thus incorporating clear evidence of particle escape from the Sun, within the HESPERIA REleASE system. To this end, a robust automated algorithm has been developed for the real-time identification and classification of Type III radio burst characteristics, related to intense SEP events at Earth’s orbit. This new implementation leads to a substantial step forward in improving the accuracy and reduction of false alarms.

How to cite: Malandraki, O. E., Posner, A., Karavolos, M., Tziotziou, K., Smanis, F., Laurenza, M., Barzilla, J., Semones, E., Whitman, K., Mays, M. L., Didigu, C., Stubenrauch, C. J., Heber, B., Kuehl, P., Maksimovic, M., Krupar, V., and Milas, N.: Improving the REleASE solar proton forecasting capabilities with evidence of particle escape from the Sun: HESPERIA REleASE + , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10862, https://doi.org/10.5194/egusphere-egu24-10862, 2024.

12:10–12:20
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EGU24-13327
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ECS
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On-site presentation
Adrian LaMoury, Mike Heyns, Jonathan Eastwood, Norah Kwagala, and Jon-Thøger Hagen

In order to better safeguard society and infrastructure from space weather hazards, improved forecasting capabilities are required. To maximise the efficiency of mitigation strategies, forecasting products must not only be accurate, but also timely and tailored to end-user needs. For understanding and predicting the behaviour of the near-Earth space environment in changing solar wind conditions, physics-based modelling is extremely powerful, though often comes at considerable computational expense. The Bergen-Imperial Global Geospace (BIGG) project is an ongoing collaborative effort to provide new space weather forecasting capabilities to the ESA space weather service network via the use of two 3D magnetohydrodynamic (MHD) magnetosphere models, GorgonOps and the Space Weather Modelling Framework (SWMF). Solar wind observations as measured in situ at L1 will be continuously and automatically ingested as simulation inputs, with minimal human intervention. Both models have been optimised such that they are able to run in faster than real time, using only modest computational resources, delivering bespoke forecasting products to the end-user community via a web portal and API in a timely fashion. This multi-model approach will provide forecast diversity and redundancy to ensure continuous and reliable service provision to Europe and beyond.

How to cite: LaMoury, A., Heyns, M., Eastwood, J., Kwagala, N., and Hagen, J.-T.: Operational Space Weather Modelling in the Bergen-Imperial Global Geospace (BIGG) Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13327, https://doi.org/10.5194/egusphere-egu24-13327, 2024.

12:20–12:30
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EGU24-9684
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ECS
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On-site presentation
|
Lauren Orr, Sandra Chapman, and Ryan McGranaghan

During geomagnetic storms the electrical power grid is vulnerable to geomagnetically induced currents (GICs) caused by sharp changes in magnetic and geoelectric fields. In the UK the measurement of GIC in the power grid is extremely limited with most GIC estimates coming from a model of the high voltage grid. The US has collected geomagnetic disturbance (GMD) data for 18 geomagnetic storms. Network theory is routinely used to estimate the resilience of the physical power grid, and its robustness to the removal of nodes, when faced with threats ranging from natural hazards to cyber-attacks but is currently not applied to GIC. By applying network theory to both the modelled UK dataset and measured US dataset, we can utilize known parameters to test for vulnerabilities to space weather in the power grid across varying spatial and temporal scales. The network is formed using methods of association between the GIC data at each transformer. The monitors are the nodes of the network and the links are defined as when the wavelet cross-correlation of the GIC is sufficiently high (1). The wavelet transform is used to localise the GIC response to the storm across time scales. Whilst previous network science studies have focused on the physical topology of the power grid, our method focuses on the dynamical response of the grid to GIC. Despite the difference in latitude and local time we see many similarities between the modelled UK and measured US GIC data, particularly during the sudden commencement. Initial results show the same nodes repeatedly appearing as the most highly connected to the network across multiple events. These nodes could be key to providing resilience and/or prediction of forthcoming disturbance of the power grid in the event of a large geomagnetic storm.

(1) Orr, L., Chapman, S. C., Beggan, C. D. (2021). Space Weather, 19, e2021SW002772.

How to cite: Orr, L., Chapman, S., and McGranaghan, R.: Comparison of geomagnetically induced currents in the US and UK power grid using network analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9684, https://doi.org/10.5194/egusphere-egu24-9684, 2024.

Posters on site: Fri, 19 Apr, 10:45–12:30 | Hall X3

Display time: Fri, 19 Apr, 08:30–Fri, 19 Apr, 12:30
Chairpersons: Guram Kervalishvili, Maike Bauer, Yulia Bogdanova
X3.10
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EGU24-11750
Monica Laurenza on behalf of the CAESAR Team

It is well known that Space Weather events can have a profound impact on our technology-dependent society. On September 6, 2017, a powerful Space Weather event originated on the Sun in the active region 12673 located at 9 degrees North latitude and 42 degrees West longitude.  An X9.3 class flare was produced, peaking at 12:02 UT, and was associated with a powerful eruptive coronal mass ejection and the emission of solar energetic particles. Correspondingly, several phenomena were observed in the interplanetary space and Earth’s environment on September 7: a shock passage at 22.58 UT associated with an energetic particle enhancement, followed by magnetospheric compression, plasmasphere density depletion, ionospheric storm and intensification of convection cells, and a Forbush decrease in the cosmic ray intensity. Here we provide a comprehensive understanding of the event, encompassing the whole chain of phenomena occurred from the Sun to the Earth. We explore the causes and evolution the Space Weather event and evaluate effects on technological systems as well as  implications for future space weather research. 

How to cite: Laurenza on behalf of the CAESAR Team, M.: A comprehensive study from the Sun to the Earth of the Space Weather event starting on the 6 September 2017, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11750, https://doi.org/10.5194/egusphere-egu24-11750, 2024.

X3.11
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EGU24-11417
Natalia Buzulukova, Juan Rodriguez, Brian Kress, Mei-Ching Fok, Lauri Holappa, Rob Redmon, and Artem Smirnov

The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model has proved to be an effective tool to understand dynamics of charged particles in the Earth's inner magnetosphere. The CIMI model can predict fluxes of radiation belt electrons, ring current particles, cold plasmaspheric population as a function of solar wind parameters, indices, equatorial radial distance, local time, energy and pitch-angle information (for radiation belts/ring current). For electrons, the CIMI model solves advection-diffusion equation combined with statistical models for chorus wave intensity and tabulated diffusion coefficients to predict radiation belt fluxes. An important part of the CIMI model is calculation of the electric field in the inner magnetosphere that is self-consistent with the ring current pressure distribution. For this study, we use the CIMI model to simulate GOES electron fluxes in the energy range 40-450 keV. Fluxes in this energy range are highly dynamic and their prediction is very important for complete space weather analysis. Additional motivation for understanding the dynamics of this energy range is demonstrated by recent findings that establish the population of electrons with energies of 100–200 keV in GEO orbit as a new class of previously neglected space weather hazards. We simulate CIMI electron fluxes for ~20 CIR-type geomagnetic storms and ~20 CME-type geomagnetic storms, and study both the model response and GOES fluxes as a function of the drivers (storm type, IMF Bz , Vx, dynamic pressure) and the local time sector. Finally, we evaluate the model's performance in terms of statistical metrics and propose ways to improve the model's predictions.

How to cite: Buzulukova, N., Rodriguez, J., Kress, B., Fok, M.-C., Holappa, L., Redmon, R., and Smirnov, A.: Predicting GOES Electron Fluxes With Comprehensive Inner Magnetosphere-Ionosphere (CIMI) Model for Different Types of Geomagnetic Storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11417, https://doi.org/10.5194/egusphere-egu24-11417, 2024.

X3.12
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EGU24-8224
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ECS
Pauline Simon and Christopher Chen

The solar wind is a plasma which is known to be highly turbulent. The subsequent non-linear cascades of, for instance, energy influence the behaviour at a wide range of scales of the observable quantities, such as the magnetic field and velocity. The small-scale behaviour can be seen as an a priori predictable “noise” that could impact space weather forecasts. Such an impact is usually neglected because the resolution of solar wind forecast models is not sufficient, due to computational limitations. As a first step in the turbulent-oriented improvement of space weather forecasts, we have tackled the question of how predictable different aspects of the small-scale turbulence in the solar wind are. We have used the ensemble analogue methodology, which assumes that future events are predictable based on what has happened in the past, and test this on the solar wind turbulence properties. We will discuss our results in terms of their implications for solar wind and space weather forecasting.

How to cite: Simon, P. and Chen, C.: Ensemble analogue methodology for the forecast of turbulent properties in the solar wind , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8224, https://doi.org/10.5194/egusphere-egu24-8224, 2024.

X3.13
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EGU24-17975
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Highlight
Syau-Yun Hsieh, Yongliang Zhang, Robert Schaefer, and Larry Paxton

Particle precipitation in the auroral oval serves as an important connection between the magnetosphere and ionosphere/atmosphere.  It is an important source of energy for the high-latitude upper atmosphere.  Particle precipitation not only creates extra ionization in the high-latitude ionosphere which leads to absorption and disturbances in radio communication, but also enhances the Joule heating by creating the Hall and Pedersen conductivity which alters the thermospheric convection and composition and further causes the global ionospheric disturbances.   To accurately characterize the auroral region energy inputs and conductivity is essential for improving the current capability for nowcasting and forecasting the ionospheric conditions in the high latitude region for space weather. The SSUSI Aurora Forecast Model is an FUV-based aurora forecast model.  It has been used operationally for predicting the global auroral quantities using the input remote-sensing ultraviolet measurements from the DMSP/SSUSI instruments.  The model predicts the equatorward boundary of auroral oval and precipitating the electron energy flux and mean energy estimated based on the empirical GUVI global model for up to 1 day or 15 DMSP orbits in advance.  We present the current implementation, capability and forecast results of this operational forecast model.  We will also discuss the current improvement and future development.

How to cite: Hsieh, S.-Y., Zhang, Y., Schaefer, R., and Paxton, L.: Operational SSUSI Aurora Forecast Model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17975, https://doi.org/10.5194/egusphere-egu24-17975, 2024.

X3.14
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EGU24-8743
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ECS
Veera Juntunen and Timo Asikainen

Earlier studies have shown that geomagnetic activity, used as a proxy for energetic particle precipitation (EPP), can influence the wintertime weather conditions, e.g. temperature and wind speed, on the surface of the Earth. This effect is transmitted via the polar vortex, the westerly wind system circulating the polar area during winter, which can intensify due to increased EPP activity. Stronger vortex tends to cause mild, wet and more windy winter weather in Northern Europe while weaker vortex leads to cold, dry and less windy winter weather. The EPP effect on the vortex is greatly dependent on the phase of the equatorial stratospheric zonal winds, called quasi-biennial oscillation (QBO), and is stronger during easterly QBO winds.

Previously it has been shown that the EPP effect on the polar vortex influences the wintertime electricity consumption in Finland that is greatly dependent on the outdoor temperature.  Since the strength of the polar vortex also affects the wind speed on ground, we now study how energetic particle precipitation would influence the electricity production by wind power.

In general, the electricity production by wind turbines is proportional to the wind speed. Here we find that during easterly QBO winds the geomagnetic aa index (proxy for EPP) correlates significantly with the wintertime wind speed in Finland and Sweden and also with the wintertime electricity production by wind power. This correlation can explain about 30-40% of the inter-annual variations of wintertime wind power production in these countries during QBO-E winters.

How to cite: Juntunen, V. and Asikainen, T.: Energetic particle precipitation (EPP) influencing the electricity production by wind power in Northern Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8743, https://doi.org/10.5194/egusphere-egu24-8743, 2024.

X3.15
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EGU24-10847
Lubomír Přech, Jana Šafránková, Zdeněk Němeček, Ivo Čermák, Tereza Ďurovcová, Maria Federica Marcucci, Monica Laurenza, and Davide Calgano

The HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) mission funded by the Italian Space Agency has recently advanced to implementation (Phase C). The HENON 12U cubesat is expected to reach a Distant Retrograde Orbit (DRO) of the Sun–Earth system before the end of this decade. For several months it will stay about ≈ 0.1 AU in front of the Earth, providing thus a unique vantage point for the in-situ solar wind monitoring and allowing to send space weather alerts several hours before the related causal geoeffective structures can reach the Earth. The payload of the mission 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.

In this contribution we focus to the description of latter sensor — the Faraday Cup Analyzer (FCA), developed at Charles University as a simple and robust sensor for long-term monitoring of the basic solar wind parameters — density, velocity and temperature. We describe the overall instrument design, discuss many important technical aspects of the development including a computer modeling of the most important parts — Faraday cups (FC). We report on results of testing of an FCA development model with newly designed FC sensors, the instrument operation modes and future telemetry data products. 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.

How to cite: Přech, L., Šafránková, J., Němeček, Z., Čermák, I., Ďurovcová, T., Marcucci, M. F., Laurenza, M., and Calgano, D.: Faraday cup instrument for the solar wind monitoring at 0.9 AU — HENON mission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10847, https://doi.org/10.5194/egusphere-egu24-10847, 2024.

X3.16
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EGU24-4766
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ECS
Dakalo Mashao, Tilly Alton, Cory Binnersley, Steve Bradnam, Stephen Croft, Malcolm Joyce, Lee Packer, Tony Turner, Jim Wild, and Michael Aspinall

Space weather events impose a threat on critical infrastructures such as electrical power grids, global navigation satellite systems, satellite operations, aviation technology and radio communication channels at various frequencies. We present an update on a new ground-level neutron monitor (NM-2023) which will be used to monitor space weather events, namely the detection and alert of ground-level enhancement (GLE) events. The NM-2023 will provide data to entities such as the United Kingdom Meteorological Office, the Neutron Monitor Database (NMDB), and the University of Surrey. We also report on a neutron monitoring survey conducted using a pair of subsystems deployed at several UK field sites. The data collected by these subsystems will be compared across the various sites, to data collected using a partial NM-2023 instrument and with data from established NMDB instruments with similar geomagnetic cutoff rigidities.

How to cite: Mashao, D., Alton, T., Binnersley, C., Bradnam, S., Croft, S., Joyce, M., Packer, L., Turner, T., Wild, J., and Aspinall, M.: Ground-level neutron monitoring survey over the United Kingdom, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4766, https://doi.org/10.5194/egusphere-egu24-4766, 2024.

X3.17
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EGU24-4674
Martina Ćorković, Giuliana Verbanac, and Mario Bandić

Geomagnetic disturbances during coronal mass ejections (CMEs), which are powerful plasma ejections from Sun’s corona, pose significant challenges for space weather forecasting. In this study, we propose an improvement to the O’Brien-McPherron model [1] for forecasting the storm-time disturbance index Dst, a key parameter reflecting geomagnetic storm intensity during CMEs, in terms of solar wind parameters. By optimizing the parameters of the O’Brien-McPherron model with respect to the sunspot number, we enhanced the model’s performance for both very low and high solar activity.

We have analysed 48 CME-induced geomagnetic storms from 1996 to 2020 and grouped them in four different solar activity levels based on the mean number of sunspots during each storm. We derived the new optimal values for three model parameters for each activity level by employing a non-linear least squares approach, specifically utilizing the Levenberg-Marquardt algorithm.

By taking into account the number of sunspots during a geomagnetic storm, we successfully mitigated the model’s tendency to consistently overestimate the intensity of very weak geomagnetic storms in the very low solar activity level. While the average difference between the forecasted maximum storm intensity and the observed intensity for the regular O’Brien-McPherron model is 17 nT, the optimized model demonstrates a notably reduced difference of 2 nT. Simultaneously, we expanded the model’s applicability to include hazardous superstorms (Dst < -150 nT) occurring during high solar activity, effectively preventing the substantial underestimation of their intensity. The O’Brien-McPherron model is not suited for superstorms and exhibits deviations of about 100 nT in forecasting their maximum intensity, whereas the optimized model underestimates it on average by only 25 nT.

Geomagnetic superstorms can induce very strong electrical currents in power grids, navigation and communication systems and satellites. Underestimating their impact can lead to insufficient shielding and permanent damage of these systems. Enhancing our ability to forecast these events with greater precision, as demonstrated by the improved performance of the optimized model, is crucial in minimizing disruptions and safeguarding infrastructure and technology.

[1] O'Brien, T. P., and R. L. McPherron (2000), An empirical phase space analysis of ring current dynamics: Solar wind control of injection and decay, J. Geophys. Res., 105(A4), 7707–7719, doi:10.1029/1998JA000437.

How to cite: Ćorković, M., Verbanac, G., and Bandić, M.: Parameter estimation of the geomagnetic activity model by non-linear least squares, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4674, https://doi.org/10.5194/egusphere-egu24-4674, 2024.

X3.18
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EGU24-14525
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ECS
Si Chen, Hong Yuan, and Yong Wei

Measuring the probability of extreme space weather events poses a challenge due to their infrequency. However, these rare events significantly and extensively impact various facilities in modern society. Extreme space weather events from the Sun have the potential to push the magnetosphere into an extreme state, where electromagnetic fields and particle environments behave differently than predicted by conventional theory, potentially causing more severe impacts than anticipated. In this study, we applied Extreme Value Theory to geomagnetic indices (such as the AE index, Aa index) derived from ground-based magnetometer observations spanning various solar cycles. We obtained the return levels of the indices with different return periods and identified an upper bound for the time series. Diligent precautions are necessary to mitigate the consequences of such extreme events, and surpassing the upper limit becomes increasingly challenging over time.

How to cite: Chen, S., Yuan, H., and Wei, Y.: Statistics of the extreme events with extreme value theory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14525, https://doi.org/10.5194/egusphere-egu24-14525, 2024.

X3.19
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EGU24-10799
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ECS
Marie Cherrier and Philippe Yaya

Ionospheric scintillations due to ionosphere irregularities may severely degrade GNSS data in equatorial and high latitudes regions, and consequently the applications that rely on such data. It is thus of high importance for many users in a large variety of applications to have access to global maps of scintillation intensity, for both signal phase and amplitude. Typically, networks of ground based GNSS receivers are used to derive those maps, but it inevitably leads to sparse coverage. 

In order to mitigate this weakness, the current study proposes to add original data points based on the DORIS system. DORIS (Doppler Orbitography by Radiopositioning Integrated by Satellite) is a French orbitography system, developed primarily for altimetric purposes by the Centre National d’Etudes Spatiales (CNES), the Institut National de l’information géographique et forestière (IGN) and the Groupe de Recherche de Géodésie Spatiale (GRGS). It consists of a network of around sixty ground-based beacons emitting a radio-frequency signal at 400 MHz and 2 GHz. The on-board receivers (on 9 civilian satellites as of January 2024) then performs Doppler shift measurements that allow precise orbit determination.  

Despite a lower data rate (0,1 Hz instead of 1 Hz for the GNSS) and a lower number of satellites, DORIS can add valuable information where there is no GNSS receivers, or by taking advantage of its geometry, in particular with polar satellites. In this study, we will explore to what extent it is possible to define scintillation proxies based on DORIS data losses, phase signal degradation, or power signal attenuation, by a comparison to a scintillation data base from GNSS measurements. Eventually, we will discuss whether the challenging near-real time basis delay is achievable. 

How to cite: Cherrier, M. and Yaya, P.: Contribution of DORIS System to Global Ionospheric Scintillation Mapping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10799, https://doi.org/10.5194/egusphere-egu24-10799, 2024.

X3.20
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EGU24-9938
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ECS
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Frédéric Tournier, Vincent Lesur, and Pierdavide Coïsson

When a cloud of plasma from a corona mass ejection hits the Earth's magnetosphere, a rapid perturbation of the magnetopause current systems occurs. It generates a signal that is detected worldwide by ground magnetic observatories in the form of a Sudden Storm Commencement (SSC). This signal has an amplitude of approximatively 20 nT but is similar to signals generated by other phenomena. Existing lists of SSCs had been set by human inspection of magnetic time series. We have implemented and tested a method to automatically detect SSC events using Support Vector Machines (SVM) classifiers within one-second data collected in the network of IPGP magnetic observatories.

How to cite: Tournier, F., Lesur, V., and Coïsson, P.: Sudden Storm Commencement detection with SVM classifiers using ground magnetic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9938, https://doi.org/10.5194/egusphere-egu24-9938, 2024.

X3.21
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EGU24-3363
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ECS
Veronika Haberle, Aurélie Marchaudon, Aude Chambodut, and Pierre-Louis Blelly

As a direct response to the increasing dependency on technological systems, the need for operational now- and forecasting of space weather events has been rising within the past decades.

In order to monitor these events and their impacts, ground magnetic field data has proven to be a long-lasting and powerful source of information. Especially for the determination of the intensity and strength of solar forcing events, the derivation of geomagnetic baselines that extract the solar forcing portion from the rest of the superposing sources within geomagnetic field signals are of importance.

In this work, we present a derivation method for determining the geomagnetic baseline for magnetic field data recorded at mid-latitudes. The contributing sources include the secular variation and the day-to-day variability, enabling the extraction of solar forcing contributions accurately. The derivation method is based on standard algorithms and does not need a-priori information other than the geomagnetic field measurements themselves. This enables the production of the baseline in near-real time and is thus suitable for operational purposes.

The deployment of the introduced baseline allows for the operational identification of solar forcing intensities and may also be used for derivation of magnetic indices that use magnetic field data from mid-latitudinal observatories.

How to cite: Haberle, V., Marchaudon, A., Chambodut, A., and Blelly, P.-L.: An operational geomagnetic baseline derivation for ground magnetometer data located in mid-latitudinal regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3363, https://doi.org/10.5194/egusphere-egu24-3363, 2024.

X3.22
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EGU24-5927
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Highlight
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Guram Kervalishvili, Jürgen Matzka, Yosuke Yamazaki, Jan Rauberg, and Marcos Vinicius da Silva

Geomagnetic indices are commonly used for various purposes, including the characterization of geomagnetic disturbance levels, parametrization of physical and empirical models of the near-Earth space environment, and data (re)analysis. The Kp (and ap) index, which is derived and disseminated by the GFZ German Research Centre for Geosciences, is one of the most extensively used such indices. The Kp index has been available since 1932 and therefore is particularly useful for studying long-term space climate trends. However, the Kp temporal resolution is limited to a three-hourly interval, which means that it cannot correctly capture rapid changes in geomagnetic activity that occur on shorter timescales. Secondly, the Kp index has an upper limit of 9, which means that all events of extremely disturbed conditions are described with one single number, which makes it difficult to differentiate between different levels of extreme geomagnetic activity.

We developed a new family of geomagnetic indices, called Hpo (“H” stands for half-hourly or hourly, “p” for planetary, and “o” for open-ended). This open-ended, high-cadence index family is similar to the Kp index in its representation of planetary geomagnetic activity, but with higher time resolution and without an upper limit. The Hpo index family consists of the half-hourly Hp30 and the hourly Hp60 indices, as well as their linear versions, the ap30 and ap60 indices. The Hpo index family is based on the same 13 geomagnetic observatory data as the Kp index. Previously, the Hpo index values were only available back to 1995. However, we have recently derived Hpo indices for the period from 1985 to 1994. This period includes several strong geomagnetic storms in 1989-1992 that have been analysed using the newly derived Hpo indices. The Hpo index family provides a more comprehensive view of the geomagnetic activity, allowing for better analysis and understanding of space weather.

How to cite: Kervalishvili, G., Matzka, J., Yamazaki, Y., Rauberg, J., and da Silva, M. V.: Extending back in time the Kp-like, open-ended, high-cadence geomagnetic Hp60 and Hp30 indices to cover the period starting from 1985, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5927, https://doi.org/10.5194/egusphere-egu24-5927, 2024.

X3.23
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EGU24-9269
Jan Rauberg, Ingo Michaelis, Martin Rother, Monika Korte, and Guram Kervalishvili

The Swarm mission of the European Space Agency (ESA) consists of three identical satellites named Alpha (A), Bravo (B), and Charlie (C), launched in a near-polar orbit on 22 November 2013. It is the first constellation mission for Earth Observation at Low Earth Orbit (LEO), which achieved the initial constellation on 17 April 2014, with Swarm A and C flying side-by-side at an altitude of about 470 km and Swarm B at an altitude of around 520 km. All of the satellites in the Swarm mission are equipped with six high-precision instruments which are identical and provide high-level data products for the past decade. These instruments include an absolute scalar and vector field magnetometer, a star tracker, an electric field instrument (Langmuir probe and thermal ion imager), a GPS receiver, and an accelerometer.

The Swarm L1b fast-track (FAST) operational chain data are distributed more rapidly and frequently in comparison with the standard product provision (OPER), which is typically available after three days. The concept of FAST data products refers to the reduced time interval between the occurrence of an event and its detection or measurement. This significantly increases the applicability of Swarm data in the field of space weather monitoring and forecasting. We performed a quality check of FAST data against OPER data for L1b products that are required as an input for the GFZ L2 data product processing chain. Here, several GFZ Swarm L2 FAST data products are shown that have been tested and implemented for operational maintenance. The quality check and operational readiness have been analysed for geomagnetically quiet and disturbed periods. Overall, these products are suitable for the FAST operational chain.

How to cite: Rauberg, J., Michaelis, I., Rother, M., Korte, M., and Kervalishvili, G.: Implementing and verifying the algorithm used for generating Swarm L2 Fast-track data products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9269, https://doi.org/10.5194/egusphere-egu24-9269, 2024.

X3.24
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EGU24-10294
Dedong Wang, Yuri Shprits, Angelica Maria Castillo Tibocha, and Alexander Drozdov

The COSPAR International Space Weather Action Team (ISWAT) is a global hub for collaborations addressing challenges across the field of space weather. One of the objectives of the G3-04 team “Internal Charging Effects and the Relevant Space Environment” is model performance assessment and improvement. One of the expected outputs is a more systematic assessment of model performance under different conditions. The G3-04 team proposed performing benchmarking challenge runs. In this study, in response to the first benchmarking challenge (long-term simulation), we perform simulations for the year 2017 to validate the Versatile Electron Radiation Belt (VERB) code. The challenge requires not using any of the measurements from the NASA' s Van Allen Probes for setting up parameters of the code, such as boundary and initial conditions. In our simulations, we use data from the Geostationary Operational Environmental Satellites (GOES) to set up the outer boundary condition, which is the only data input for simulations. We validate our simulation results against measurements from Van Allen Probes. In particular, we ‘fly’ a virtual satellite through our simulation results and compare the simulated differential electron fluxes at 0.9 MeV and 57.27 degrees local pitch-angle with the fluxes measured by the Van Allen Probes. In general, our simulation results show good agreement with observations. We calculated several different matrices to validate our simulation results against satellite observations. Using the similar approach, we extend our simulations to several years long period and validate our simulation results against satellite observations in both long-term and specific geomagnetic storms. Several different validation matrices are calculated for both long-term and specific events.

How to cite: Wang, D., Shprits, Y., Castillo Tibocha, A. M., and Drozdov, A.: Validation of Model Results in Response to the COSPAR ISWAT Challenge, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10294, https://doi.org/10.5194/egusphere-egu24-10294, 2024.

X3.25
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EGU24-7574
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ECS
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Barbara Perri, Martin Reiss, Karin Muglach, Evangelia Samara, Richard Mullinix, and Chiu Wiegand and the ISWAT Ambient Solar Wind Validation Team

To drive innovation in space weather research and prediction, we need to seek out promising strategies for unifying the validation of our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. Our team's mission is to create an open online platform for validating ambient solar wind models at NASA's Community Coordinated Modeling Center. This open platform will allow the community to easily assess the accuracy of state-of-the-art solar wind model solutions in terms of unified metrics, and will thereby provide an unbiased assessment of progress over time. In this presentation, we will introduce the online platform, highlight our progress in developing unified metrics for both historical and near real-time validation, and discuss the current status and future perspectives of this community effort.

How to cite: Perri, B., Reiss, M., Muglach, K., Samara, E., Mullinix, R., and Wiegand, C. and the ISWAT Ambient Solar Wind Validation Team: An Open Platform for Validating Ambient Solar Wind Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7574, https://doi.org/10.5194/egusphere-egu24-7574, 2024.

X3.26
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EGU24-16590
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ECS
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Highlight
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Maike Bauer, Justin LeLouedec, Tanja Amerstorfer, and Jackie Davies

Timely and accurate prediction of coronal mass ejections (CMEs) is vital for mitigating the potential impact of severe space weather events on critical infrastructures. Currently, manual detection and tracking of CMEs as they traverse the heliosphere are the norm. This presentation introduces an innovative approach: the development and implementation of a machine learning algorithm for automatic detection and tracking of CMEs, leveraging data from various heliospheric imager (HI) instruments. The wealth of active spacecraft equipped with HI instruments provides a unique opportunity to train the algorithm using diverse datasets.

This work gains significance in light of the upcoming launch of Vigil, a space weather monitor scheduled for deployment in the early 2030s at the L5 point. Vigil will continuously observe and provide real-time HI observations along the Sun-Earth line. Our presentation showcases preliminary outcomes from an automated CME detection and tracking algorithm, demonstrating its effectiveness with training on STEREO-HI data. We also discuss potential future steps and challenges in the development and testing of this algorithm, emphasizing its role in advancing operational space weather prediction capabilities, especially in anticipation of the Vigil mission.

How to cite: Bauer, M., LeLouedec, J., Amerstorfer, T., and Davies, J.: Automated detection and tracking of CMEs using HI instruments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16590, https://doi.org/10.5194/egusphere-egu24-16590, 2024.

X3.27
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EGU24-5357
Tanja Amerstorfer, Jackie A. Davies, David Barnes, Maike Bauer, Justin LeLouëdec, Eva Weiler, and Christian Möstl

The STEREO mission has paved the way for the forthcoming Vigil mission, set to launch around 2030. Based on the extensive data archives from STEREO's wide-angle cameras, the heliospheric imagers (HI), we aim to assess the suitability of these data for real-time space weather prediction.
This study focuses on modeling the evolution of coronal mass ejections (CMEs) as they progress towards Earth, employing STEREO-A and STEREO-B observations from Vigil's future vantage point, the L5 point of the Sun-Earth system, with the drag-based ensemble model ELEvoHI.
Our investigation aims to determine to what extent incorporating additional HI data (as it would be received in real-time) improves the forecasting accuracy and its impact on the prediction lead time.

How to cite: Amerstorfer, T., Davies, J. A., Barnes, D., Bauer, M., LeLouëdec, J., Weiler, E., and Möstl, C.: Utilising Heliospheric Images for Space Weather Prediction: A Data Assimilation Strategy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5357, https://doi.org/10.5194/egusphere-egu24-5357, 2024.

X3.28
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EGU24-15028
Ute Amerstorfer, Hannah Rüdisser, Andreas Weiss, and Christian Möstl

The 3D coronal rope ejection (3DCORE) method has been used to fit magnetic fields of CME flux ropes to in situ observations. Its assumed Gold-Hoyle-like flux rope has an elliptical cross-section and expands self-similarly, thereby staying always attached to the Sun. An approximate Bayesian computation sequential Monte Carlo algorithm performs the fitting and allows us to get error estimates of the model parameters. 

Extending our previous studies, we investigate the ability of 3DCORE to fit the magnetic field of a flux rope in real time, when only the first hours of an observation are available. Therefore, we use past events mimicking a possible real-time application, but also any real-time events possibly happening. If performing well, this real-time application of 3DCORE can further advance the efforts of space weather prediction.

 

How to cite: Amerstorfer, U., Rüdisser, H., Weiss, A., and Möstl, C.: How well does 3DCORE perform at fitting flux rope signatures in real-time?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15028, https://doi.org/10.5194/egusphere-egu24-15028, 2024.

X3.29
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EGU24-20550
Stefaan Poedts, Senne Doumen, Anwesha Maharana, Peter Wintoft, and Tinatin Baratashvili

The EUropean Heliospheric FORecasting Information Asset (EUHFORIA, Pomoell and Poedts, 2018), a physics-based and data-driven heliospheric and CME propagation model can predict the solar wind plasma and magnetic field conditions at Earth. It contains several flux-rope CME models, such as the simple spheromak models and the more advanced FRi3D and toroidal CME models. This enables the prediction of the sign and strength of the magnetic field components upon the arrival of the CME at Earth and, thus, the geo-effectiveness of the CME impact. EUHFORIA has been coupled to several global magnetosphere models like OpenGGCM, GUMICS-4, and Gorgon-Space. In addition, the synthetic data at L1 (from the EUHFORIA simulation) can be used as input for empirical models and neural networks to predict the geomagnetic indices like Disturbance-storm-time (Dst) or Kp that quantify the impact of the magnetized plasma encounters on Earth’s magnetosphere. Hence, we also coupled EUHFORIA to empirical models (Obrien and McPherron, 2000b, and Newell et al, 2006) and machine learning (NARMAX, and the models from Wintoft et al. (2017 and 2021)) based models to predict the geomagnetic indices. We then compare the results of these models to observational data to evaluate their performance in predicting the geo-effect indices. To quantify these comparisons, we use the advanced dynamic time warping method. Since we use synthetic data from the EUHFORIA simulations, we can obtain the input parameters for running the geomagnetic indices models two to three days in advance, unlike the 60-90 minutes lead time of the real-time measurements. 

We perform ensemble modelling considering the L1 monitor precision in its orbit as well as the uncertainty in the initial CME parameters (longitude and latitude) at launch, for error quantification. This is done by evaluating the geomagnetic index models using synthetic data from the virtual satellites around L1 in EUHFORIA’s simulation domain. In addition, we also investigate the impact of the spatio-temporal resolution of EUHFORIA output in forecasting the geomagnetic indices, exploiting the adaptive mesh refinement feature in ICARUS (Baratashvili et al., 2022). Overall, this study validates various space weather forecasting model chains and checks the best compatibility and predictive capabilities using EUHFORIA data for operational space weather forecasting.  

How to cite: Poedts, S., Doumen, S., Maharana, A., Wintoft, P., and Baratashvili, T.: Predicting geo-effectiveness two days prior to CME impact with EUHFORIA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20550, https://doi.org/10.5194/egusphere-egu24-20550, 2024.

X3.30
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EGU24-20576
Maher Dayeh and Radoslav Bučik

Solar flares, Coronal Mass Ejections (CMEs), and associated Solar Energetic Particles (SEPs) play crucial roles in influencing space weather in the vicinity of Earth and beyond. Forecasting these events requires prior knowledge and understanding of the physical mechanisms driving these phenomena. Although some CMEs and flares are strongly associated with intense SEPs, there are instances where little or no SEP connection is evident. This lack of consistent correlation between observed SEPs at 1 AU and their origins near the Sun is primarily due to the complex interplanetary environment that governs SEP generation, acceleration, and transport. Currently, there is no reliable and consistent method for long-term forecasting (spanning hours to days) of SEP properties, and efforts to develop such forecasting techniques are ongoing. The Space Weather Helioseismic and Magnetic Imager (HMI) Active Region Patches (SHARP) provide information about the magnetic properties (e.g., helicity, strength, and gradient) of solar active regions and pre-flaring activity.  In this work, we examined the connection between the characteristics of 21 large gradual SEP events affecting the Earth environmentand and their associated SHARP parameters. Specifically, we investigated the relationship between SEP peak intensities at ~10 MeV and ~50 MeV, CME speed, X-ray flare, and the SHARP parameters. Our findings reveal consistent and stable correlations, both positive and negative, between average SHARP parameters and each of the analyzed properties within the 24 hours leading up to the flare onset. These results offer evidence that SHARP parameters could significantly enhance the prediction of space weather events.

How to cite: Dayeh, M. and Bučik, R.: Linking pre-flare active region parameters to Flare, CME and SEP properties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20576, https://doi.org/10.5194/egusphere-egu24-20576, 2024.

Posters virtual: Fri, 19 Apr, 14:00–15:45 | vHall X3

Display time: Fri, 19 Apr, 08:30–Fri, 19 Apr, 18:00
Chairpersons: Guram Kervalishvili, Maike Bauer, Yulia Bogdanova
vX3.2
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EGU24-20497
A new geoelectric field model for the UK based on long-period magnetotelluric data to assess and forecast ground-based space weather effects
(withdrawn)
Juliane Huebert, Ciaran Beggan, Gemma Richardson, Eliot Eaton, Lauren Orr, Duygu Kiyan, Colin Hogg, and Ellen Clarke