Session CD6 - Near Earth Space Radiation and Plasma Environment: Science and Space Weather Applications
Yihua Zheng, onsite (NASA Goddard Space Flight Center, USA), Ian Mann (University of Alberta, Canada), Natalia Yu Ganushkina (Finnish Meteorological Institute, Finland/University OF Michigan, USA)
Near-Earth space is a region consisting of diverse populations of particles spanning a broad energy range from a few eV to 100s MeVs that could lead to different space weather impacts on space hardware and/or human. This session aims to engage the community in seeking innovative ways to improve modeling of the near-Earth space radiation and plasma environment for the benefit of space weather operations and applications, which includes identifying knowledge gaps and research and measurement needs to help advance science understanding of this important region with complex dynamics. The session welcomes submissions on topics including (but not limited to):
- how AI/machine learning, data assimilation, ensemble modeling, open science, and other innovative methods can be utilized
- how we can continuously carry out user-oriented systematic model validations (together with uncertainty quantification) to ensure the healthy cycle of space weather models and to ready them for space weather purposes.
This session is in line with COSPAR/ISWAT G3 Cluster activities and objectives (https://www.iswat-cospar.org/g3).
Monday October 24, 09:00 - 14:00, Poster AreaTalks
Monday October 24, 16:00 - 17:00, Fire Hall
Tuesday October 25, 15:45 - 16:45, Earth HallClick here to toggle abstract display in the schedule
Talks : Time scheduleMonday October 24, 16:00 - 17:00, Fire Hall
Tuesday October 25, 15:45 - 16:45, Earth Hall
|16:00||International Radiation Environment Near Earth (IRENE) - collaboration developments||Jiggens, P et al.||Oral|
| ||Piers Jiggens, Paul O'Brien, Ingmar Sandberg, William Johnston, Sigiava Aminalragia-Giamini, Stuart Huston, Constantinos Papadimitriou, Alexander Boyd, Matteo Martucci, Tim Guild|
| || ESA/ESTEC,  Aerospace Corporation,  Space Applications & Research Consultancy,  AFRL,  AER,  INFN|
| ||The International Radiation Environment Near Earth (IRENE) collaboration is an effort to create specification models of the radiation and plasma environments near Earth for application on a broad range of space missions covering the full range of Earth orbits. The development incorporates the AE9 and AP9 models of the Van Allen radiation belts and the low energy component covered by SPM (the Space Plasma Model). For the past 2-3 years the IRENE modelling effort has been expanded from a solely US enterprise to include more international participation. The IRENE collaboration includes extensive data sets upon which model flux maps are based, extended modelling of the radiation belts and plasma environments, solar energetic particle modelling for the near-Earth environment and simulation of effects (so-called effects kernels).
This presentation will provide the latest updates made to IRENE with a special focus on European contributions. This shall include new datasets being incorporated into the model database (including PAMELA and Proba-V/EPT), updated radiation belt methodologies and algorithms, and spectrally consistent solar energetic particle modelling functionality (SAPPHIRE-2S) including time series outputs for single event effecs analysis. This talk shall also highlight what goals the IRENE collaboration has for the future and how interested parties can contribute to achieving these. |
|16:15||Applications of RAM-SCB to Advance Space Weather Forecasting||Jordanova, V et al.||Oral|
| ||Vania Jordanova, Steven Morley, Miles Engel, Humberto Godinez, Kateryna Yakymenko, and Michael Henderson|
| ||Los Alamos National Laboratory, Los Alamos, NM, USA|
| ||Energetic particle fluxes (in the keV energy range) can intensify significantly in the near-Earth space environment during space weather events like geomagnetic storms and could cause severe damage to ground-based and satellite-based technologies. There are large ongoing efforts to develop accurate models of this space plasma environment with both nowcasting and predictive capabilities. We provide a brief description of the physics and numerical implementation of one such model, our kinetic ring current-atmosphere interactions model with self-consistent magnetic field (RAM-SCB). This model has grown from a research-grade code with limited options to a rich, highly configurable research and operations tool with a multitude of applications and output products. Specific examples that demonstrate RAM-SCB capabilities and limitations to reproduce the near-Earth space weather environment, as well as plans for its further improvement are discussed.|
|16:30||SHELLS Model: Specifying High-altitude Electrons using Low-altitude LEO Systems ||Boyd, A et al.||Oral|
| ||Alexander Boyd, Janet Green, Paul O'Brien, Seth Claudepierre|
| || The Aerospace Corporation,  Space Hazards Applications,  UCLA|
| ||Specifying the internal charging hazard for non-GEO orbits (LEO, MEO and HEO) remains a challenging problem. To address this, we’ve developed the SHELLS model, a deep learning artificial neural network model of the near-Earth space environment. The model uses inputs of geomagnetic indices and LEO electron flux measurements from the NOAA POES spacecraft to output the energetic electron flux as observed by the MagEIS instrument on NASA’s Van Allen Probes. We have recently completed improvements to the model architecture including integration of L-shell and B-mirror dependences into a single neural network. These improvements allow for better spatial and temporal coverage. Here, we will discuss the model architecture, present out-of-sample validation results, and demonstrate where the model can be accessed and run.|
|16:45||Mitigation of satellite surface charging by means of ionic liquid coating||Wendt, M et al.||Oral|
| ||Mirco Wendt , Regina Lange , Franziska Dorn , Jens Berdermann, Ingo Barke , Sylvia Speller |
| || University of Rostock, Institute for Physics,  German Aerospace Center, Institute for Solar-Terrestrial Physics Neustrelitz|
| ||To reduce the impact of charging effects on satellites, cheap and lightweight conductive coatings are desirable. Space-like environments can be imitated in ultra-high vacuum (UHV) chambers during deposition of charges via the electron beam of a scanning electron microscope (SEM). As a performance test for discharging via a thin ionic liquid (IL) film we use the quality of electron microscopy on insulating surfaces such as glass or SrTiO3 (STO), that were structured by nanosphere lithography and coated with IL. The IL film (BMP-DCA) was applied ex situ and a thickness between 10 and 30 nm was determined by reflectometry, assuming a refractive index of 1.45. Such a film of ionic liquid would lead to additional mass of below 20 mg and material costs of < 15 cent per square meter. At about 5 A /m2 ≈ 3·1019 e/(sec·m2) steady state SEM imaging is possible with no appreciable contrast changes over many hours; note that this electron current density is already 6 orders of magnitudes higher than “worst case geosynchronous environments” of 3·10-6 A/m2 . At space orbit altitudes large periodic temperature variations are faced. Below -16° C, weak charging effects can be observed. The lifetime of charges is in the regime of 20 minutes and rises with further sample cooling. Different participating mechanisms such as polarisation, reorientation and ion-drift will be discussed.
 Henry B. Garrett and Albert C. Whittlesey, Guide to Mitigating Spacecraft Charging Effects. Wiley, 1st edition (2012), page 160|
|15:45||Assessing and Predicting Lunar Charging Environments Using THEMIS||Parker, L et al.||Oral|
| ||L. Parker, J. Green, J. Likar, A. Turner, D. Pitchford, C. Keys|
| ||Space Weather Solutions; Space Hazards Applications; Johns Hopkins Applied Physics Laboratory; SES; Maxar|
| ||Over the next few years, NASA and its partners will launch a series of lunar exploration missions with crewed missions set to begin in 2024. These plans for long-term sustained operations at the moon carry an inherently higher risk from space weather than previous endeavors. The intense and highly variable space radiation poses a risk to astronaut health as well as to the technology that protects and enables their efforts. The goal of our research is to provide effective and actionable information about the lunar space environment that will allow users to anticipate and mitigate impacts to space systems. More specifically we are developing a statistical and neural network model of the lunar particle populations responsible for both spacecraft surface and internal charging.
We present here results from the initial development of the neural network and statistical plasma models using the THEMIS data. We will show results of the region classification using a Gaussian Mixture Model into pre-wake, lunar wake, uncompressed and compressed solar wind, magnetosheath, and magnetosphere regions. Using the date to define these regions rather than a model reduces the level of uncertainty. We also show results to date of Nascap-2k surface charging analyses using a NASA supplied model for the Gateway. Environments used for the analyses are from the NASA Design Specification for Natural Environments (DSNE) lunar plasma environments and THEMIS data environments identified in our work. Ultimately, the results of this effort will provide a model that will give the statistically expected densities, temperatures, and potentials at a lunar location.|
|16:00||Solar Particle Radiation Storms Forecasting and Analysis within ESA/SSA- The HESPERIA SEP Real-Time Forecasting products ||Malandraki, O et al.||Oral|
| ||Olga Malandraki, Michalis Karavolos, Dimitris Kokkinis, Nikolaos Milas, Norma Crosby, Mark Dierckxsens|
| ||National Observatory of Athens (NOA), IAASARS, Athens, Greece (firstname.lastname@example.org), Royal Belgian Institute for Space Aeronomy, Brussels, Belgium|
| ||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 aircraft specifically above high-latitudes. SEP Real-Time Forecasting products were developed by the HESPERIA H2020 project (Project Coordinator: Dr. Olga Malandraki). The HESPERIA UMASEP-500 product makes real-time predictions of the occurrence of >500 MeV proton events and Ground Level Enhancement (GLE) events based on the analysis of soft X-ray and high energy differential proton fluxes measured by the GOES satellite network. Based on the Relativistic Electron Alert System for Exploration (REleASE) forecasting scheme, the HESPERIA REleASE product generates 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 products have attracted attention by various space organizations (e.g. NASA/CCMC, SRAG), due to the real-time, highly accurate and timely performance offered. ESA selected the HESPERIA products to be integrated in the ESA Space Weather (SWE) Service Network (https://swe.ssa.esa.int/noa-hesperia-federated). During the integration period, the HESPERIA products underwent a transformation phase in which a new framework was developed for providing the SEP forecasting results to ESA. Keeping the forecasting core identical, various changes have been implemented concerning the user interface and the mechanisms to provide the forecasting results to the end users. This includes the HESPERIA REleASE Alert product, a notification system that informs about the expected radiation impact in real-time using an illustration and a distribution system for registered users. We will present the HESPERIA products as provided through the ESA SWE Service Network under the Space Radiation Expert Service Centre (R-ESC), fully compliant with the strict operating framework set by ESA and the international SWE forecasting community. Solar cycle 25 solar radiation storms successfully predicted will also be presented and discussed. (Work performed in the frame of ESA Space Safety Programme’s network of space weather service development and pre-operational activities, and supported under ESA Contract 4000134036/21/D/MRP).|
|16:15||Prediction of electron fluxes in the outer radiation belts using neural networks with PROBA-V/EPT data||Botek, E et al.||Oral|
| ||Edith Botek  and Viviane Pierrard [1,2]|
| || Royal Belgian Institute for Space Aeronomy, Solar Wind, Space Physics and STCE, Brussels, Belgium,  Université Catholique de Louvain, Center for Space Radiations, ELI-C, Louvain-La-Neuve, Belgium|
| ||The wide use of artificial intelligence (AI) techniques in nearly every domain of knowledge allows nowadays a deeper analysis and prediction using increasing powerful models.
We present our contribution to the investigation of the Earth outer radiation belts dynamics by employing Recurrent Neural Networks (RNN) to predict the electron fluxes. We test several combinations of time series inputs involving solar wind and geomagnetic data, based on previous knowledge of their impact onto the fluxes. We also introduce the PROBA-V/EPT electron fluxes data to train the AI data-driven model. PROBA-V ensures a broad coverage of the near-Earth radiation environment along its low altitude polar orbit at around 820 km spanning all the L-shells during its orbital period of about 101 minutes. Two energy channels of the EPT instrument are used to feed this RNN case study for non-relativistic (500-600 keV) and relativistic (1-2.4 MeV) electrons fluxes.
We demonstrate a good performance of the obtained model employing different time resolutions from minutes to days with a correlation > 0.8 between the predicted and test fluxes. The analysis of the input parameters and time resolutions allows to construct the best time series structure and improve the model so as to identify relevant effects as dropouts, flux increases and recovery features.|
|16:30||Electron flux measurements from ESA Next Generation Radiation Monitor on-board GEO EDRS-C satellite and LEO Sentinel-6 satellite||Aminalragia-giamini, S et al.||Oral|
| ||Sigiava Aminalragia-Giamini, Ingmar Sandberg, Constantinos Papadimitriou, Wojciech Hajdas[2,3], Radoslaw Marcinkowski, Daniel Heynderickx, Rian van Gijlswijk, Melanie Heil, Hugh Evans|
| ||Space Applications and Research Consultancy (SPARC), Athens, Greece; SE2S, 8113 Boppelsen ZH, Switzerland; Paul Scherrer Institut, 5232 Villigen, Switzerland; DH Consultancy, Leuven, Belgium; Solenix-DE, Darmstadt, Germany; ESOC, European Space Agency, Darmstadt, Germany; ESTEC, European Space Agency, 2200 AG Noordwijk, The Netherlands|
| ||European Space Agency’s (ESA) Next Generation Radiation Monitor (NGRM) is the successor of the Standard Radiation Environment Monitor (SREM). Two NGRM units have been embarked on two hosted payload flights as a part of ESA’s Distributed SWE Sensor System (D3S) and more units are envisioned to be hosted in future missions. The first NGRM was placed on-board the Geostationary (GEO) European Data Relay System Satellite-C (EDRS-C) and was set in nominal operation on August of 2019 providing 1-min cadence measurements, while the second unit was placed on board the Low Earth Orbit (LEO) Sentinel-6 Michael Freilich (S-6-MF) satellite, launched on November 2020 providing 15-sec cadence measurements.
In this work, we focus on the derivation and analysis of high-quality differential electron fluxes from the count-rate measurements of the electron detection system of the NGRM on-board EDRS-C and show first electron flux results from the unit on Sentinel-6. The electron response functions of the units were derived using GEANT4 simulations re-adjusted with experimental results based on the unit’s experimental calibrations at Paul Scherrer Institut, Switzerland. Using the instrument’s response functions, we have applied an advanced Artificial Intelligence technique (GenCORUM) (Aminalragia-Giamini et al. 2018 DOI: 10.1051/swsc/2018041) to the production of electron differential fluxes from the monitor’s measurements. Our method utilizes a genetic algorithm and allows for the derivation of electron spectra in a wide energy range.
The EDRS-C NGRM Level-1 datasets include differential and integral electron fluxes in the 0.18-4.0 MeV energy range and 0.35-2.5 MeV respectively and have been evaluated and validated with third-party measurements during the geostationary transfer orbit (GTO) (Sandberg et al. 2022 DOI: 10.1109/TNS.2022.3160108) and at the nominal Geostationary orbit. Real time and archived fluxes from the EDRS-C/NGRM unit are accessible through a dedicated webpage as well as an API as a part of the ESA Space Weather (SWE) portal providing an important new asset for the real-time monitoring and characterization of the GEO radiation environment as well as Radiation Belt modelling efforts.
Acknowledgements: This work is supported by the SSA P3-SWE-XXI NGRM Data Processing activity led by SPARC under ESA Contract No 4000127954/19/D/CT. NGRM development was sponsored under ESA contract AO/l-6659/IO/NLiAT. The authors acknowledge ESA Directorate of Operations - S|
|1||10th year of the Proba-V/EPT mission: possible applications of long energetic particles flux time series in model development.||Borisov, S et al.||Poster|
| ||Stanislav Borisov, Sylvie Benck|
| ||Center for Space Radiations, Earth and Life Institute, Université catholique de Louvain (UCL/ELI-C/CSR), Place Louis Pasteur, 3, B-1348 Louvain-la-Neuve, Belgium|
| ||By now the Energetic Particle Telescope (EPT) on-board Proba-V (launched on 7th May 2013 onto a polar Low Earth Orbit of 820 km altitude) has provided quasi continuously more than 9 years of flux spectra data for electrons (0.5–8 MeV), protons (9.5–248 MeV) and α-particles (38–980 MeV) with a time resolution of 2 seconds. The data are transmitted to ground 3 – 4 times per day, where within several hours they are processed towards scientific data products.
This presentation will focus on observed spectral and space distribution features of electrons, protons and α-particles measurements during the last 9 years linked to solar activity. Effects of storms and SEPs of various intensity and type, on the outer and inner belts will be shown as well as solar cycle variation. Being a LEO orbit, these data can be used in model validation and provide boundary conditions for advanced physics models.|
|3||Plasma Environment Modelling in Earth’s Magnetosphere (PEMEM): new specification model for surface charging risk assessment.||Dubyagin, S et al.||Poster|
| ||Stepan Dubyagin,Natalia Ganushkina,Angélica Sicard,Loanne Monnin,Jean-Charles Matéo Vélez,Daniel Heynderickx,Piers Jiggens,Gregoire Deprez,Fabrice Cipriani|
| ||Finnish Meteorological Institute (FMI), Helsinki, Finland, Office National d’Etudes et de Recherches Aérospatiales (ONERA), Toulouse, France, DH Consultancy BV, Leuven, Belgium, European Space Research and Technology Centre (ESTEC), ESA, Noordwijk, The Netherlands|
| ||New near-Earth plasma environment specification models have been developed under the ESA contract No. 4000128226/19/NL/AS. The models cover the energy range 1-100 keV for electrons and 50eV - 50keV for protons and are intended to be used for the surface charging risk assessment for space missions with near-equatorial orbits. The models are based upon the Van Allen probes dataset and cover the region inside GEO but can be extended up to McIlwain L = 9. The models’ design includes the radial and local time dependence. The model primary input is a planned spacecraft trajectory, and it outputs statistical characteristics of the plasma environment which are expected to be encountered during mission lifetime. These characteristics include differential flux percentiles (percentile spectra) for electrons and protons, percentiles of the electron integrated flux, worst-case electron spectra, and integrated flux for the user-specified confidence level. Since the extreme surface charging usually occurs when a spacecraft is in shadow, the same characteristics can be separately output for the eclipse periods. Finally, the worst-case characteristics are computed for the expected average geomagnetic activity disturbance level for a future mission. This level is defined by selecting an equivalent period (the same solar cycle phase) in the past.|
|4||Multi-Purpose Model Validation Efforts for Space Plasma and Radiation Environment in the Near-Earth Region||Zheng, Y et al.||Poster|
| ||Yihua Zheng|
| ||NASA Goddard Space Flight Center|
| ||Model validation is a critical component in moving scientific research models and scientific understanding forward. At the same time, it is an indispensable step in transitioning a model from research to operations. To combine such efforts into one, working with different experts from science, engineering, operational communities, we have selected the Essential Space Environment Quantities (ESSEQ) that are most relevant (and easy to interpret) to the corresponding space weather impact assessments. In this presentation, initial community-wide model validation efforts relevant to internal charging (https://iswat-cospar.org/G3-04) and surface charging (https://iswat-cospar.org/G3-02) of satellites will be shown, focusing on progresses and challenges.
Note: this work is contributed by all G3-02 and G3-4 team members. |
|5||Forecasting the electron ring current population using the VERB-4D model, data assimilation, and ensemble modelling||Haas, B et al.||Poster|
| ||Bernhard Haas[1,2], Yuri Y. Shprits[1,2,3], Michael Wutzig, Dedong Wang|
| ||GFZ German Research Centre for Geosciences, Potsdam, Germany; Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany; Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, Los Angeles, CA, United States|
| ||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 spacecrafts, due to surface charging effects, which can cause satellite anomalies. Additionally, ring current electrons interacting with plasma waves, can be scattered to lower altitudes, where they collide with molecules of the atmosphere causing the diffusive aurora and the production of NOx, responsible for ozone holes.
Here, we present the most recent advancements in forecasting the electron ring current population using the VERB-4D model. The ring current model is coupled with a machine-learning based Kp forecasting model, predicting an ensemble of possible Kp time series. Furthermore, a data-assimilative nowcast of the ring current is performed to provide an accurate initial condition for the forecast. Using the Kp time series and initial condition as input, an ensemble of ring current simulations is performed, forecasting the electron dynamics 3 days in advance. By validating this approach for events during the Van Allen Probes era, we found that a data-assimilative nowcast is crucial for predicting slow dynamics of the ring current correctly, while ensemble simulations help to quantify the uncertainty of variable regions within the ring current.|
|6||Radiation Belt Simulations Using the VERB Code in Response to the COSPAR ISWAT Challenge||Wang, D et al.||Poster|
| ||Dedong Wang , Yuri Shprits [1,2,3], Alexander Drozdov , Hayley Allison , Angelica Castillo Tibocha [1,2]|
| || GFZ German Research Centre for Geosciences, Potsdam, Germany,  University of Potsdam, Potsdam, Germany,  University of California, Los Angeles, California, USA|
| ||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 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 our 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. We also point out ways to potentially improve our model performance.
This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 870452 for the PAGER project.