CD3 – Advancing our Understanding of the Heliospheric and Near-Earth Environments to Enhance Space Weather Forecasting Capabilities
Talks
CD3.1 Mon 4/11 12:00-13:00, room C2B – Sofia
Author(s): Joseph Minow
NASA
Abstract: The relatively low energy component of the charged particle environments beyond the Earth’s radiation belts represents a radiation source with potential impacts to materials used on the exterior surfaces of spacecraft for missions in interplanetary space including the Moon and other airless bodies, the Sun-Earth Lagrange points, and planetary missions in transit to and from Earth. The low energies (less than about an MeV with a peak ion energies of approximately 1 keV and electron energies extending to a few keV) are relatively benign to the bulk structure of materials with little or no threat to spacecraft operations. Surfaces and volumes of thin space exposed materials however may accumulate total ionizing doses generated by electrons, protons, and alpha particles in the megarad to gigarad range over a mission life. Radiation damage of materials due to these large doses may be a concern for current and future spacecraft designs using very thin materials or bulk materials where the surface properties are mission critical. Some examples where radiation dose from low energy particles should be evaluated include radiation degradation of solar sail propulsion systems, changes in thermo-optical properties of thermal control coatings, radiation damage to thin sunshield materials, and modification of surface charging properties for materials used on the exterior surfaces of spacecraft with requirements to be electrostatically clean. We will first discuss the characteristics of ionizing radiation and plasma environments relevant to thin materials including solar wind and low energy contributions from solar particle events in interplanetary space. Next, low energy charged particle damage mechanisms for materials will be summarized including total ionizing dose, hydrogen blistering, changes in thermo-optical properties, and sputter erosion yields. Finally, examples of modeling techniques used to compute the charged particle fluence to material surfaces and volumes of thin materials will be described along with methodologies for estimating total ionizing dose as a function of depth for materials in the low energy environment.
Author(s): Ravindra Desai, Jamie Perrin, Saurav Patel, Nigel Meredith
University of Warwick; University of Warwick; University of Warwick; British Antarctic Survey
Abstract: The Combined Release and Radiation Effects Satellite (CRRES) launched in 1990 into the maximum of solar cycle 22 and provided unprecedented advances in our understanding of radiation belt dynamics. These observations include the radiation belt response to a solar cycle much more active than recent ones, and include the extreme event of 24 March 1991 where a large interplanetary shock rapidly compressed the magnetosphere inside of geosynchronous orbit for an extended period of 6 hours. In this study, we re-examine data from the CRRES High Energy Electron Fluxometer (HEEF) dataset to determine the extent and scale of energetic electron injections into the slot region and inner belt. Upon examining this dataset we find that electron injections deep into the slot region and inner belt occur throughout the mission and under a variety of conditions. We characterise their decay rates according to various geomagnetic indices and discuss how upcoming observations by the Gateway space station will observe electron injections with unprecedented detail.
Author(s): Janet Green, Adam Kellerman, Linda Parker, Alex Boyd, Paul O’Brien
Space Hazards Applications LLC; University of California, Los Angeles; Space Weather Solutions; Aerospace Corporation; Aerospace Corporation
Abstract: Electrons in the magnetosphere create a hazard for satellites in near-Earth orbit which must function continuously even in this charging environment. When the electron flux intensifies, charge may build on satellite surfaces and internal materials resulting in sudden discharges that can damage sensitive components leaving the satellite temporarily or permanently inoperable. With the proliferation of satellites in all orbits, it is necessary to understand how the global electron environment changes in real time and to quantify the impacts and hazards to this growing satellite infrastructure.
Our goal is to provide models and applications that will allow satellite operators to easily monitor the electron environment and its impacts to satellite systems in order to analyze, mitigate, and respond to any on-orbit issues. To do so, we have developed several real time physics based and machine learning electron radiation belt models spanning from low Earth orbit to cislunar space. For example, the SHELLS model provides a global map of electron flux based on a neural network mapping of low altitude measurements and is now available through the NASA Community Coordinated Modeling Center (CCMC). In addition, we are expanding the domain of the Versatile Electron Radiation Belt (VERB) model to predict low energy electron fluxes responsible for surface charging as well as the high energy component that causes internal charging issues. To make this output usable by operators, we are extending the model capabilities to transform the flux into charging potentials expected in different orbital regimes. Here we report on the progress of these modeling efforts and the applications developed for real time monitoring purposes.
Author(s): T.P. OBrien, W.R. Johnston, Piers Jiggens, Yoshizumi Miyoshi
The Aerospace Corporation; Air Force Research Lab; ESA; ISEE / Nagoya University
Abstract: The International Radiation Environment Near Earth Model (IRENE), formerly AE9/AP9/SPM, has provided the global satellite design community with enhanced specification capabilities over legacy models since 2012. Based on feedback from the community we have continued to improve and expand capabilities of the model suite. We have recently released updates to version 1.5 providing more features for capturing statistics such as variable timescale fluences and worst-case quantities. Pending updates will incorporate data sets including Pamela, PROBA-V, EPT, SREM, NASA’s Van Allen Probes (remaining data), and AFRL’s DSX. Version 2.0 will provide a new module-based architecture supporting additional hazard models (e.g., solar protons), new module-specific capabilities (e.g., local time dependence for plasma), and improved stitching between models. We will provide an update on development status and plans for future versions.
Author(s): Geoffrey Reeves, Maria Voskresenskaya, Greg Cunningham
The New Mexico Consortium; The New Mexico Consortium; Los Alamos National Laboratory
Abstract: Here we report on a new R2O2R project to predict the duration and intensity of space weather events using re-analysis of long-term space weather data to develop a computationally inexpensive algorithm fed only by operationally-available, real-time data streams.
Space weather nowcast, forecasts, and scales provide alerts for the probability and severity of current or near-future space weather hazards. In a complementary role, space weather “benchmarks” provide information to enable users to develop plans to prepare for, mitigate, and respond to severe space weather conditions. Both can benefit from rigorous re-analysis of long-term data sets. To date most statistical studies have focused on analyzing and/or predicting simple time-series data such as Dst, radiation belt fluxes, or ionospheric disturbances. However, most statistical methods assume that the input data are all statistically independent – which is not the case for most time-series. Fortunately most space weather conditions of interest occur as discrete “events” of various intensities and durations that are, in fact, statistically independent of one another.
In 2020, Reeves et al. (https://doi.org/10.1029/2020SW002528) introduced a methodology to define and analyze MeV electron events at geosynchronous orbit. The method identifies “events” based on a variable flux threshold. It then uses the probability distribution of events to establish, quantitatively, the thresholds that define an average occurrence rate of, for example, 1 event per year, 1 event per 10 years, 1 event per 30 years, etc. While demonstrated for a single use case the methodology is applicable to any space weather situations that occur as discrete “events”.
We now extend that methodology to predict, in real-time, how long a given space weather event will last and how intense it will be. A key finding of our research is that it is both more feasible and more valuable to predict the duration and intensity of an event in progress than to predict a time series. By their nature time-series predictions, and associated validation metrics, are dominated by the quiet or low-hazard intervals between hazardous events. They are also relatively less accurate at predicting the onset of a hazardous event in advance. In contrast, we demonstrate how real-time data can be used to identify the onset of an event as it occurs and use historical re-analysis to predict how long the event will last and how intense it will be. Initially the algorithm uses the recent “pre-event” time series and ancillary data (e.g. solar wind and geomagnetic conditions) and probability distributions of durations and intensity of similar historical events. But, as the event progresses and data for the event becomes more robust, the forecast continuously updates, becoming more accurate and more event-specific. Importantly, the metrics for this method are accuracy of predicting only duration and intensity, not the accuracy of each future data point.
In this talk we demonstrate the methodology for predicting the duration and intensity of space weather “events” and discuss our plans for transitioning the results to an operational space weather testbed within 3 years.
CD3.2 Thu 7/11 14:15-15:15, room Sofia
Author(s): Yuri Shprits, Stefan Bianco, Dedong Wang, Bernhard Haas, Muhammad Asim Khawaja, Karina Wilgan, Tony Arber, Keith Bennet, Ondrej Santolik, Ivana Kolmasova, Ulrich Taubenschuss, Mike Liemohn, Bart van der Holst, Julien Forest, Arnaud Trouche, Benoit Tezenas du Montcel
GFZ Potsdam, Germany/University of Potsdam/UCLA; GFZ Potsdam, Germany; GFZ Potsdam, Germany; GFZ Potsdam, Germany; GFZ Potsdam, Germany; GFZ Potsdam, Germany; University of Warwick, UK; University of Warwick, UK; Institute of Atmospheric Physics, Prague, Czech Republic; Charles University, Prague, Czech Republic; Institute of Atmospheric Physics, Prague, Czech Republic; University of Michigan, USA; University of Michigan, USA; ARTENUM, Paris, France; ARTENUM, Paris, France; ARTENUM, Paris, France
Abstract: 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 forecasts initiated from 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 the 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, several innovative tools were 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 forecasts of the geomagnetic 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 modeling of extreme space weather events. Similar to the codes used in the PAGER project, we can use the VERB-3D code to evaluate the global precipitation of particles.
Author(s): Vincent Maget, Guillerme Bernoux, Gautier Nguyen, Quentin Gibaru, Nourallah Dahmen, Angélica Sicard
ONERA; ONERA; ONERA; ONERA; ONERA; ONERA
Abstract: The Horizon Europe FARBES (Forecast of Actionable Radiation Belt Scenarios) project aims to develop methods for forecasting the dynamics of radiation belts trapped electron fluxes in an operational context. Our goal is to predict the evolution of an event over several days from its onset, as observed through geomagnetic indices, rather than predicting the occurrence of an event in the radiation belts based on its solar origin or upstream solar wind parameters.
This presentation describes the work carried out to date to develop a method for forecasting, several days in advance, the indices and parameters that drive the Salammbô radiation belts model. Our method is based on the Analog Ensemble technique, which involves identifying past periods that are most similar to the so-called current disturbed state and using their future developments as members of an ensemble forecast several days in advance. Unlike most usual machine learning methods, this method has the advantage of producing physically realistic scenarios, that can be updated as soon as more recent data become available.
We present here how the analog ensemble method can contribute to fine-tune the drivers of the Salammbô code to forecast the ongoing event, using both single and ensemble Salammbô simulations. In particular, this method has the advantage of providing analog and historical time periods from which we can retrieve numerous timeseries such as the location of the magnetopause, observed fluxes along different orbits and in particular, outer boundaries for such a code. This method also allows us to estimate what is the most probable cause (such as ICMEs or SIRs) of the ongoing event. This information can be used to derive wave-particle interaction coefficients with a newly-developed classification method. Finally, we evaluate our model and present avenues for future development.
Author(s): Mario M. Bisi, Biagio Forte, Steve Milan, David Jackson, Richard A. Fallows, Bernard V. Jackson, Dusan Odstrcil, Edmund Henley, David Barnes, Oyuki Chang, Matthew Bracamontes, Siegfried Gonzi, Pauk Kinsler
UKRI STFC RAL Space, UK; University of Bath, UK; University of Leicester, UK; Met Office, UK; UKRI STFC RAL Space, UK; UCSD, USA; GMU/NASA, USA; Met Office, UK; UKRI STFC RAL Space, UK; UKRI STFC RAL Space, UK; UCSD, USA; Met Office, UK; University of Bath, UK
Abstract: The NERC-funded Radio Investigations for Space Environment Research (RISER) project addresses the chain of events through which the Sun creates adverse space-weather conditions at Earth and within the Earth’s space environment. RISER aims to investigate how the LOw Frequency ARray (LOFAR) can be utilised for continuous and accurate tracking of inner-heliospheric and ionospheric plasma structures, combined with magnetospheric modelling, leading to more-precise and advanced forecasts of space-weather conditions and their impacts at Earth. RISER will provide a comprehensive understanding of the Earth’s space-environment through the use of novel radio observations and modelling techniques to investigate coupling between solar-driven inner-heliospheric structures and the Earth.
RISER brings together a unique set of different radio techniques along with various types of modelling and other data sets. It is a five-year project, which commenced on 01 September 2023 with partners in the UK and the USA. RISER will facilitate the upgrading of the LOFAR-UK Rawlings Array at Chilbolton to the new dual-beam, LOFAR For Space Weather (LOFAR4SW) capability, providing the potential for 24/7 space-weather observations towards the end of the five-year project.
Here, we give a reminder of the RISER project and its high-level objectives including the importance and relevance to advancing our understanding of space-weather science and impacts. We will report on progress to date throughout the first year of the project with an outlook on the next steps.
Author(s): Marina García Peñaranda, Yuri Shprits, Alexander Drozdov, Angélica M. Castillo Tibocha, Bernhard Haas, Matyas Mátyás Szabó-Roberts
GFZ German Research Centre for Geosciences; University of Potsdam, Potsdam, Germany; GFZ German Research Centre for Geosciences; University of Potsdam, Potsdam, Germany; University of California, Los Angeles, CA, USA.; University of California, Los Angeles, CA, USA; GFZ German Research Centre for Geosciences; University of Potsdam, Potsdam, Germany; GFZ German Research Centre for Geosciences; University of Potsdam, Potsdam, Germany; GFZ German Research Centre for Geosciences
Abstract: Radiation belt electron dynamics show high variability in space and time during geomagnetically active periods, which could potentially damage the satellites though deep dielectric and surface charging. In the past years, numerous physics-based models have been developed to describe the evolution of phase space density in the radiation belts, however they are subject to uncertainties and errors in the initial and boundary conditions. Data assimilation provides to be a reliable technique for blending satellite data and the output of physics-based models, creating a more reliable reconstruction with all the available information about the environment.
This study presents for the very first time a global validation of the data-assimilative VERB-3D code using two independent datasets: Arase measurements for the assimilation with the VERB-3D code via a split-operator Kalman Filter, and Van Allen Probes observations for validation, which are not used for data assimilation. The results provide very valuable insights into the accuracy and performance of the data assimilative model and its capability to replicate the radiation belt environment, showing the great potential for data assimilation techniques in space weather applications.
Author(s): Bernhard Haas, Yuri Y Shprits, Stefano Bianco
Helmholtz Centre, GFZ German Centre for Geosciences, Potsdam, Germany; Helmholtz Centre, GFZ German Centre for Geosciences, Potsdam, Germany; Helmholtz Centre, GFZ German Centre for Geosciences, Potsdam, Germany
Abstract: One of the major characteristics of a geomagnetic storm is the enhancement of the particle flux in the terrestrial ring current, causing multiple space weather effects.
The electron population from 10 to 50 keV forms a hazardous environment for spacecraft, due to surface charging effects, which can cause satellite anomalies.
Here, we present the most recent global validation efforts of the data-assimilative VERB-4D ring current model.
By assimilating measurements from one satellite and validating the results against another satellite in a different magnetic local time sector, we assess the global response and effectiveness of the data assimilation technique for space weather applications.
Using this method, we found that the simulation accuracy can be drastically improved at times when observations are available while eliminating almost all of the bias previously present in the model.
Furthermore, we show results of ensemble forecasting of VERB-4D when coupled to machine-learning-based Kp ensemble predictions.
Posters
Posters II Display Thu 7/11 – Fri 8/11, room C1A – Aeminium
Authors in attendance: Thu 7/11 10:15–11:30, 15:15-16:15; Fri 8/11 10:15–11:30
Author(s): Leon Golub
Center for Astrophysics; Harvard & Smithsonian
Abstract: The Extreme ultraviolet Coronal mass ejection and Coronal Connectivity Observatory (ECCCO) is an innovative mission designed to explore the middle corona, the region between 1.5–3 Rsun, which is the least explored part of the solar atmosphere. The dynamics of eruptive events leaving the Sun and the conditions that produce the outward streaming solar wind can only be understood through extended and continuous observations of this region. ECCCO builds on a foundation of previous instrumentation that provided tantalizing hints of the complex nature of the middle corona, but no observatory until now has been able to provide consistent, uniform, global measurements of dynamics, morphology, and plasma diagnostics in this crucial part of the atmosphere.
ECCCO addresses its scientific objectives with three instruments: a two-channel widefield extreme ultraviolet (EUV) imager (ECCCO-I) and a pair of nearly identical slitless imaging EUV spectrographs (ECCCO-S). Each of these instruments is dramatically more capable than those previously or currently available. The innovative ECCCO instrument suite, constructed with heritage components, includes: an EUV imager with unprecedented dynamic range and spectral coverage, capable of observing from the solar disk through the middle corona; and two nearly identical spectrographs with complementary passbands to detect both hot and cool coronal plasma.
ECCCO answers fundamental questions about the origins of the mass and energy flow that links the Sun to the outer corona and heliosphere, revealing principal drivers of coronal and heliospheric physics. ECCCO fully characterizes the middle corona to determine the sources, release, dynamics, and acceleration of matter escaping from the Sun, both for particles continually streaming outward with the solar wind and for large amounts of material erupting during coronal mass ejections. The overarching scientific goals of ECCCO are twofold: 1) Understand the sources, release, and acceleration of the solar wind close to the Sun and 2) Understand the symbiotic relationship between eruptive solar events and the large-scale coronal structure.
ECCCO naturally complements the highly successful GOES Solar Ultraviolet Imager instruments, extended their field of view in overlapping passbands. The QuickECCCO SEO provides a path to delivering low-latency ECCCO observations to NOAA’s Space Weather Prediction Center to improve tracking of flares and eruptions and refine forecasts of impact and arrival times for energetic solar events, and tracking shock structures associated with acceleration of solar energetic particle, which currently lack strong forecast constraints.
Author(s): Janna Martens, Bernd Heber, Henrik Dröge, Karl-Ludwig Klein, Jens Berdermann, Volker Wilken, Jan Maik Wissing, Malte Bröse, Daniela Banys
Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany; Christian-Albrechts-University, Kiel, Germany; Christian-Albrechts-University, Kiel, Germany; Christian-Albrechts-University, Kiel, Germany; Observatoire de Paris, Meudon, France; Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany; Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany; Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany; Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany; Institute for Solar-Terrestrial Physics, German Aerospace Center, Neustrelitz, Germany
Abstract: Historically, a range of diagnostics for Solar Energetic Particle (SEP) events based on radio observations from Earth has been developed since the 1960s, which are to some extent utilized in contemporary prediction models. These diagnostics span from the occurrence of long-lasting broadband radio emissions (cm-m waves) to the spectra of microwave bursts (mm-cm waves).
The Relativistic Electron Alert System for Exploration (REleASE) forecasting metric utilizes electron data collected by the Electron Proton Helium Instrument aboard the SOHO spacecraft. We aim to enhance the capabilities of the REleASE system by exploring diagnostics across diverse frequency ranges while the primary focus is on the presence and spectral profile of microwave emissions. We assess especially the quality of whole-Sun measurements of microwave spectra and discuss how they provide a deeper insight into the relationships between particle acceleration in the corona and potential radiation exposure at 1 AU. Initial results of this integration and its impact on the accuracy of SEP event forecasting will be presented.
Author(s): Angelica Maria Castillo Tibocha, Yuri Y. Shprits, Jana de Wiljes, Nikita Aseev, Alexander Drozdov, Sebastian Cervantes, Artem Smirnov, Ingo Michaelis, Dedong Wang, Marina García Peñaranda
German Research Centre for Geosciences – GFZ Potsdam; University of Potsdam, Institute of Physics and Astronomy, Potsdam, Germany; German Research Centre for Geosciences – GFZ Potsdam; University of Potsdam, Institute of Physics and Astronomy, Potsdam, Germany; Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, CA, USA; Technical University of Ilmenau, Institute of Mathematics, Ilmenau, Germany; German Research Centre for Geosciences – GFZ Potsdam; Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, CA, USA; University of Cologne, Institute of Geophysics and Meteorology, Cologne, Germany; German Research Centre for Geosciences – GFZ Potsdam; German Research Centre for Geosciences – GFZ Potsdam; German Research Centre for Geosciences – GFZ Potsdam; German Research Centre for Geosciences – GFZ Potsdam; University of Potsdam, Institute of Physics and Astronomy, Potsdam, Germany
Abstract: The near-Earth radiation environment poses significant risks to satellites and human spaceflight missions. Sparse observational data and uncertainties in physics-based models hinder our understanding and prediction capabilities of the complex plasma dynamics in this region. To overcome these challenges, data assimilation techniques are employed to reconstruct the state of the entire system by blending physics-based models and measurements from multiple instruments. Data assimilative approaches also allow us to issue real-time predictions and aid in identifying missing physical processes. We present successful implementation of two data assimilation methods: the Kalman Filter (KF) and the Ensemble Kalman Filter (EnKF), for studying the electron phase space density in the outer radiation belt. Additionally, we demonstrate how the obtained global reconstruction of the radiation belt system can be utilized to perform efficient intercalibration of satellite observations of electron fluxes in this region. Our data assimilative intercalibration approach is validated by comparing the obtained intercalibration factors with those derived from a traditional conjunction study.
Author(s): A. P. Rasca, H. J. Singer, G. H. Millward, J. G. Luhmann, C. O. Lee, L. Jian, G. Tóth, Z. Huang, A. B. Galvin, L. Ellis, C. T. Russell, X. Liu, P. Schroeder, H. Wei
CU/CIRES; NOAA/SWPC; CU/CIRES; UC Berkeley; UC Berkeley; NASA; University of Michigan; University of Michigan; University of New Hampshire; University of New Hampshire; UCLA; UCLA; UC Berkeley; UCLA
Abstract: On August 12, 2023 the STEREO-A spacecraft made its first close approach with Earth since 2006, passing at a distance of ~8 million km along the Earth-Sun line. Downstream at the L1 Lagrange point (1.5 million km from Earth) lie the ACE and DSCOVR spacecraft, with solar wind plasma and magnetic field measurements used at the inflow boundary for the operational Geospace global magnetosphere model that provides a 30-60 minute lead time for incoming space weather activity. The brief passage of STEREO-A near the Sun-Earth line provides an opportunity to test the performance of the Geospace model using sub-L1 observations that can increase the lead time by several hours. We use data from STEREO-A as input for the Geospace model for three geomagnetic storms in April, August, and September of 2023 and compare predictions with the L1-driven Geosapce model results that use Wind and ACE/DSCOVR measurements.
Author(s): Stefano Bianco, Yuri Shprits
GFZ; GFZ, University of Potsdam, UCLA
Abstract: We will present operational real-time forecasts of the Kp/Hp indices and of the plasma density in the plasmasphere that are currently running and available at spacepager.eu. These forecasts are generated by machine-learning models which have been extensively validated and which have measurements and forecasts of the solar wind at L1 and the Kp index as inputs for the real-time predictions.
Author(s): Alwin Roy, Dedong Wang, Yuri Y. Shprits, Ting Feng, Thea Lepage, Ingo Michaelis, Yoshizumi Miyoshi, Geoffrey D. Reeves, Yoshiya Kasahara, Ondřej Santolik, Atsushi Kumamoto, Shoya Matsuda, Ayako Matsuoka, Tomoaki Hori, Iku Shinohara, Fuminori Tsuchiya
Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany; Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany; Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany, University of Potsdam, Germany, University of California, Los Angeles, USA; Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany, Wuhan University, China; Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany, Luleå University of Technology, Sweden; Helmholtz Centre Potsdam German Research Centre for Geosciences, GFZ, Germany; Nagoya University, Japan; Los Alamos National Laboratory, USA, The New Mexico Consortium, Los Alamos, New Mexico, USA; Kanazawa University, Japan; Czech Academy of Sciences, Prague, Czechia, Charles University, Prague, Czechia; Tohoku University, Japan; Kanazawa University, Japan; ISAS/JAXA, Sagamihara, Japan; Nagoya University, Japan; ISAS/JAXA, Sagamihara, Japan; Tohoku University, Japan
Abstract: Chorus waves play an important role in the dynamic evolution of energetic electrons in the Earth’s radiation belts and ring current. Due to the orbit limitation of Van Allen Probes, our previous chorus wave model developed using Van Allen Probe data is limited to low latitude. In this study, we extend the chorus wave model to higher latitudes by combining measurements from the Van Allen Probes and Arase satellite. As a first step, we intercalibrate chorus wave measurements by comparing statistical features of chorus wave observations from Van Allen Probes and Arase missions. We first investigate the measurements in the same latitude range during the two years of overlap between the Van Allen Probe data and the Arase data. We find that the statistical intensity of chorus waves from Van Allen Probes is stronger than those from Arase observations. After the intercalibration, we combine the chorus wave measurements from the two satellite missions and develop an analytical chorus wave model which covers all magnetic local time and extends to higher latitudes. This chorus wave model will be further used in radiation belt and ring current simulations.
Author(s): Georg Blüthner, Manuela Temmer, Florian Koller
Institute of Physics, University of Graz, Austria; Institute of Physics, University of Graz, Austria; Institute of Physics, University of Graz, Austria
Abstract: Small-scale solar wind structures, consistently impacting Earth, provide a fundamental transfer of energy from Sun to Geospace, hence contribute to Space Weather. However, what we measure at L1 might not be consistent with structures arriving at Earth. We explore how well OMNI data resemble direct near-Earth measurements using THEMIS. We focus on variations in large-scale solar wind structures such as coronal mass ejections (CMEs) and stream interaction regions (SIR) together with their distinct substructures. Our study is based on existing CME/SIR lists of events defined by Koller et al. [2022] in OMNI data. For the given time ranges, we compare the timing and appearance for the structures in the solar wind plasma and magnetic field parameters as probed by OMNI, and THEMIS. Our approach involves creating a database of identified structures, especially those observed by multiple spacecraft, facilitating statistical analysis. This research will contribute to a more comprehensive understanding of solar wind dynamics and the relationships between their substructures measured at different locations.
Author(s): Claudio Corti, Kathryn Whitman
CCMC; University of Hawaii; NASA/JSC/SRAG; KBR
Abstract: Galactic cosmic rays (GCRs) are an important component of the deep-space radiation environment and include all ions from hydrogen up to nickel and beyond, ranging from a few tens of MeV/n up to more than hundreds of GeV/n. GCRs are affected by solar modulation while they propagate through the heliosphere resulting in a large variability of the GCR intensity in space and time. GCR models used to predict/estimate the deep-space radiation environment need to characterize GCRs at different locations in the heliosphere and on time scales from days to years to centuries. Since the space age, GCRs have been measured by hundreds of instruments. However, the time and spatial coverage of high-quality data is not uniform.
Here we present a comprehensive database of GCR measurements collected from multiple sources, spanning a wide range of heliospheric locations, energy, and time intervals. We describe the method used to remove contamination from solar energetic particles, anomalous cosmic rays, and other particle populations of solar origin. We also highlight some potential issues in cross-instrument calibration and comment on the usability of some datasets for the purpose of tuning and validating GCR deep-space radiation models.
Author(s): Xiaoyu Wang, Dedong Wang, Yuri Shprits, Xing Cao, Binbin Ni
GFZ Germany Research Cnetre for Geosciences; GFZ Germany Research Cnetre for Geosciences; GFZ Germany Research Cnetre for Geosciences; Wuhan University; Wuhan University
Abstract: The relativistic electrons in the Earth’s outer radiation belt are recognized to experience dynamical evolutions due to complicated competitions between acceleration and loss processes, especially during geomagnetic storms. Here we perform a detailed analysis of prompt dynamics of relativistic electrons during the strong storm happening during 10-19 May 2024. In the storm main phase, dropouts of > 700 keV relativistic electrons are observed by LEO NOAA 18 throughout the outer and inner radiation belts. In addition, precipitation ring current electrons and protons are captured at L > 2. During the storm recovery phase, the fluxes of relativistic electrons locally increase by about more than two orders of magnitude at L > 2, contributing to the disappearance of slot region. To clarify underlying mechanisms accounting for the relativistic electron dynamics, we conduct simulations by using 3-dimensional Versatile Electron Radiation Belt code. In these simulations, the measurements from Geostationary Operational Environmental Satellite are derived to set up the outer L* boundary. Magnetopause shadowing effect is included by using the location of magnetopause, which results in significant dropouts of relativistic electrons at L* > 4 during storm main phase. Due to the rapid erosion of the plasmapause (down to the inner belt), the local accelerations outside the plasmapause during the recovery phase are reproduced by including local diffusions driven by chorus waves, following by the appearance of slot region and remnant belt inside the plasmapause. Our results highlight the prompt dynamics of relativistic electrons in the slot and inner belt, thus providing valuable references for in-depth understanding relativistic electron dynamics in the Earth’s radiation belts in response to strong storms.
Author(s): Richard Fallows
UKRI – STFC – RAL Space
Abstract: Observations of interplanetary scintillation (IPS) have been used for many years to provide a global 3-D picture of solar wind density and velocity throughout the inner heliosphere. Regular monitoring observations carried out by dedicated systems, such as ISEE in Japan, are fed into a tomographic modelling package, which applies a standard weak scattering model to correct for the effects of integrating along an extended line of sight, and inverts the data to produce 3-D visualisations and forecasts of density and velocity at L1. These are under test with space weather forecast agencies as an additional source of ground-based information to that provided by space-based systems.
Observations using the Low-Frequency Array (LOFAR) – a system of wide-bandwidth radio receivers, with a large cluster of stations in the Netherlands and others spread widely across western Europe – can provide a wealth of additional information by applying techniques impossible with smaller systems. These have recently been demonstrated on select observations of a CME and scintillation due to a comet tail (Fallows+, 2022a,b), but full weak-scattering modelling has yet to be applied, meaning that these results are still subject to the effects of line of sight integration. In this poster, we develop a modelling package and use it to demonstrate how integration along an extended line of sight affects the results and make a first attempt at applying it to the results presented in these papers. This is the first step necessary to extract more-accurate information from individual LOFAR observations of IPS, and then use these to help constrain the results from space weather models used in operational forecasting.
Author(s): Navin Kumar Dwivedi, Arpad Kis, Istvan Lemperger, Peter Kovacs, Emiliya Yordanova, Zoltan Vӧrӧs, Marius Echim, Shobhana Singh
HUN-REN Institute of Earth Physics and Space Science, Hungarian Research Network, 9400 Sopron, Hungary; HUN-REN Institute of Earth Physics and Space Science, Hungarian Research Network, 9400 Sopron, Hungary; HUN-REN Institute of Earth Physics and Space Science, Hungarian Research Network, 9400 Sopron, Hungary; HUN-REN Wigner Research Centre for Physics, Space Physics and Space Technology Department, Budapest, Hungary; Swedish Institute of Space Physics, Uppsala, Sweden; Space Research Institute, Austrian Academy of Sciences, 8042 Graz, Austria; Institut Royale d’Aeronomie Spatiale de Belgique, 1180 Brussels, Belgium; Department of Mechanical Engineering, Indian Institute of Technology Jodhpur, 342037 Jodhpur, India
Abstract: The vast majority of the visible Universe is in a plasma state, and one of the most widespread behaviors observed in such plasmas is turbulence – the transfer of energy across a broad range of scales that leads to complex chaotic motions, structure formation, and energy conversion. Not only is this turbulence a fascinating area of fundamental plasma physics, it is thought to be important in a variety of important open questions in space and astrophysics, such as the heating of the solar corona, generation of the solar wind, structure of the heliosphere, acceleration of energetic particles, disk physics, galaxy cluster heating, and space weather. As we all know that space weather is driven by the sun, which continuously changes its magnetic field. When this field accumulate excess energy, it can erupt and send energetic particles into space, sometimes towards Earth. We know the existence of space turbulence or plasma turbulence, but don’t understand its properties in totality until now. Unlike wind gusts that create air and water turbulence on Earth, it turns out that space turbulence results from the interaction of plasma waves or wave particles interacting with each other. Turbulence acts to transfer energy from large-scale motion into small scale motion and heat. In collisionless plasmas, energy is dissipated by particles interacting with waves in the plasma. Understanding turbulence is important because it influences particle heating and acceleration, such as solar energetic particles and cosmic rays. It is also important because it heavily influences the structure and dynamics of the Earth’s magnetosphere as well as energy and mass inflow to the magnetosphere.
In the present work, we investigate the power-law behavior of the magnetic field spectra in the Earth’s magnetosheath region using Cluster spacecraft data under solar minimum condition. The power spectral density of the magnetic field data and spectral slopes at various frequencies are analyzed. Propagation angle, θkB, and compressibility, R‖, are used to test the nature of turbulent fluctuations. The magnetic field spectra have the spectral slopes, α, between -1.5 to 0 down to spatial scales of 20 λi (where λi is ion inertial length), and show clear evidence of transition to steeper spectrum for smaller scales with a second power-law, having α between – 3 to -1.6. At low frequencies, fsc < fci (where fci is ion gyro-frequency), θkB ̴ 90 to the mean magnetic field, B0 , and R‖ shows a broad distribution, 0.1≤ R‖ ≤ 0.9. On the other hand at fsc > fci, θkB exhibits a broad range, 30≤ θkB ≤90, while R‖ has a small variation: 0.2≤ R‖ ≤ 0.5. We conjecture that at high frequencies, the perpendicularly propagating Alfvén waves could partly explain the statistical analysis of spectra. To support our prediction of kinetic Alfvèn wave dominated spectral slope behavior at high frequency, we also present a theoretical model and simulate the magnetic field turbulence spectra due to nonlinear evolution of kinetic Alfvèn waves. The present study also shows the analogy between the observational and simulated spectra.
Author(s): Asim Khawaja, Bernhard Haas, Matyas Szabo-Roberts, Artem Smirnov, Angelica Maria Castillo Tibocha, Stefano Bianco, Dedong Wang, Yuri Shprits
GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences; GFZ German Research Centre for Geosciences
Abstract: This study aims to predict the flux of energetic electrons at energies of 0.8 MeV, 1.2 MeV, 1.6 MeV, and higher at geosynchronous orbit in real-time, using a machine learning approach with inputs such as magnetic local time (MLT), solar wind speed, solar wind pressure, and Kp indices, all available in real-time. We perform feature engineering by incorporating past data points to enhance prediction accuracy. A portion of the data is used to train an artificial neural network (ANN) model for each energy level to achieve accurate predictions. The trained ANN model is then evaluated on the remaining, unseen dataset and subsequently adapted for real-time predictions.
Current experiments focus on optimizing feature engineering by evaluating the influence of past data on forecasting accuracy, adjusting the quantity and resolution of historical data considered. This is followed by tuning model parameters to identify the best model. This research underscores the potential of machine learning models for real-time radiation belt electron flux prediction, contributing to the broader goal of improving space weather forecasting capabilities.
Additionally, we introduce GeoML, a Python package designed for data processing, feature engineering, model training, and flux forecasting. GeoML is built with a modular architecture, facilitating the easy integration of updates to data, code, and models. One use case of GeoML is predicting flux for available input features and providing boundary conditions for radiation belt modeling using the Versatile Electron Radiation Belt (VERB) code.
Author(s): Ashwin Shirke (1), Yuri Shprits (1,2,3),Stefan Bianco (1), Dedong Wang (1), Matyas Szabo-Roberts (1), Bernhard Haas (1), Asim Khawaja (1), Karina Wilgan (1), Julia Himmelbasch (1), Tony Arber (4), Keith Bennet (4), Ondrej Santolik (5), Ivana Kolmasova (5,6), Ulrich Taubenschuss (5), Mike Liemohn (7), Bart van der Holst (7), Julien Forest (8), Arnaud Trouche (8), Benoit Tezenas du Montcel (8),
(1) GFZ Potsdam, Germany (2) University of Potsdam, Germany (3) University of California, Los Angeles (UCLA), USA (4) University of Warwick, UK (5) Institute of Atmospheric Physics, Prague, Czech Republic (6) Charles University, Prague, Czech Republic (7) University of Michigan, USA (8) ARTENUM, Paris, France
Abstract: Accurate space weather forecasting is essential for mitigating the risks posed by geomagnetic storms to technological systems, particularly satellites. The PAGER project provides an advanced probabilistic framework for space weather prediction, employing state-of-the-art ensemble simulations to forecast solar wind parameters, ring current dynamics, and the radiation belt environment. By leveraging cutting-edge models, data assimilation techniques, and uncertainty quantification, PAGER produces forecasts of Kp and Hpo indeces, cold plasma density, and relativistic electron fluxes, addressing both surface charging and deep dielectric charging risks to satellite infrastructure.
In this study, we utilize the PAGER framework to simulate the 2024 Mother’s Day Solar Storm. The simulation is initialized with GONG magnetogram data, which provides the boundary conditions for ensemble solar wind predictions at L1. These predictions include solar wind velocity, proton density, and magnetic field components. By comparing simulation outputs to in-situ observations from the OMNIWeb database, we assess the predictive accuracy of PAGER’s ensemble forecasting capabilities. Additionally, we demonstrate the integration of these solar wind predictions with radiation belt and satellite charging models, illustrating PAGER’s capacity to link solar wind dynamics with downstream effects in the Earth’s magnetosphere and their impact on satellite operations.
PAGER’s ensemble approach incorporates sophisticated models of magnetospheric dynamics and ring current evolution, offering critical insight into the radiation environment surrounding Earth during extreme space weather events. This study will highlight the ensemble predictions for the Mother’s Day Solar Storm and demonstrate PAGER’s broader capability to address uncertainty in space weather forecasting, thus enhancing our ability to protect satellite infrastructure from adverse space weather effects.
Author(s): Federico Pinna, Leonardo Tolomei, Rosario Messineo, Chiara Leuzzi, Filomena Solitro, Roberto Susino, Daniele Telloni, Silvano Fineschi, Alessandro Bemporad, Sabrina Guastavino, Michele Piana
ALTEC; ALTEC; ALTEC; ALTEC; ALTEC; INAF; INAF; INAF; INAF; DIMA -UNIGE; DIMA -UNIGE
Abstract: The Heliospheric Space Weather Centre (HSWC) is an ALTEC, INAF – OATo, and University of Genoa (UniGe) joint project aimed at providing and supporting services related to the heliosphere. The long run aim of the HSWC is to provide various services for monitoring the heliosphere and forecasting events such as geomagnetic storms, flares, and CMEs. It currently hosts two tools developed by ALTEC and INAF: the Geo Magnetic Effectiveness (H103d) and the CME propagation prediction (H103e). The tools are part of the SWESNET project, within the ESA Space Weather programme. The algorithms are developed by INAF and are integrated into ALTEC’s infrastructure, which handles data retrieval, scientific product generation, storage, and web interface.
The H103d tool uses data from DSCOVR spacecraft to compute magnetic helicity, a key quantity used to identify geo-effective events. It analyses near real-time measurements from DSCOVR Faraday Cup (FC) and magnetometer (MAG), and generates plots of magnetic field, solar wind speed, proton density, proton temperature, DST index, magnetic helicity spectrogram, and integrated magnetic helicity. The plots are generated and published over a 7 days period every 12 minutes.
The H103e tool employs data from DSCOVR/FC and images from LASCO/C2-C3. Its algorithms can detect earthward halo CMEs, calculating their features (such as mass, speed, acceleration, …), model solar wind, and model CME propagation. The pipeline computes 48 solar wind and proton density maps daily from DSCOVR/FC data over the previous 28 days; when an earthward CME is detected, its parameters and arrival time are calculated from LASCO images, and a video representing the CME propagation front is produced.
ALTEC infrastructure is being upgraded to host AI support tools developed by UniGe. In the next future, AI-based modules will be added to both the H103d, in the context of AIxtreme-I project, and H103e tools; the AI models will support the current physics-based models, improving their performances (e.g. forecasting ability and accuracy). A third tool, dedicated to predict the occurrence of intense solar flares within the following 24 hours, is currently in the integration phase. The forecasting is twofold, being performed in two independent ways: one based on solar spot features, the other based on video. Both methods use data acquired by SDO HMI instrument. The AI algorithms have already been developed and are currently in the integration phase in ALTEC infrastructure.
The existing tools, their working mechanisms and results will be presented, as well as their AI future improvements and related preliminary results. The latest updates of the AI-based Flare forecasting tool will be shown too.