APL1 – The path from models and data to operational services
Talks
APL1 Mon 4/11 14:00-16:00, room C2D – Almedina
Author(s): Jenny Knuth, Greg Lucas, Eelco Doornbos, Thomas E. Berger
SWx TREC, University of Colorado (CU) Boulder; SWx TREC, University of Colorado (CU) Boulder; KNMI; SWx TREC, University of Colorado (CU) Boulder
Abstract: Space weather missions, data, and models are currently under-utilized. We have an abundance of tools and applications that require expert knowledge, training, webinars, local computing resources, and/or technical know-how just to attempt to use them. This presentation will shine a light on a frequently overlooked and historically undervalued approach to making the most of our space weather assets: user-centered web applications.
In this presentation I will outline the current state of the art in space weather applications beyond the VSWMC and CCMC, such as the SWx TREC Model Staging Platform and the KNMI Space Weather Timeline Viewer .
I’ll bring in successful examples from industry and the earth sciences to show how we can improve the visibility and reach of space weather data. Agile workflows that center user needs and early adopter programs are two examples of processes that can increase access and understanding for scientists, forecasters, and the public alike. A little competition and cross-fertilization has also been shown to be helpful to users and consumers. Variety in the ecosystem is not always a waste of effort.
In addition to early adopter programs, user-centered agile workflows, and real-world experimenting and evolution, I’ll illustrate concrete steps we can take as a community to increase data access and adoption such as interoperable metadata catalogs, unified APIs, established design systems, and usability testing.
Our investment in missions, data, and models can be enhanced when usability and user input are part of the design and budget from the beginning instead of an afterthought. A relatively small investment in functional web applications can lead to large dividends in space weather science and space weather communication.
Intuitive and inviting space weather applications—and ideally, broad support for a Space Weather Applications Program—can advance space weather operations, science, and public understanding.
Author(s): Gregory E. Tucker
University of Colorado Boulder USA
Abstract: The challenge of making numerical models and their associated datasets interoperable spans the physical sciences. This presentation reviews approaches and lessons learned in the earth-surface dynamics community. The take-home message is that some of the tools and concepts used in earth-surface dynamics may be useful for improving the access and standardization for space-weather-related models and datasets.
Earth-surface dynamics refers to the constellation of geoscience and engineering disciplines that deal with the processes that modify earth’s surface, shaping terrain and sedimentary deposits. Like space-weather science, earth-surface dynamics bridges traditional disciplines. Earth’s surface is the interface where the atmosphere, lithosphere, hydrosphere, cryosphere and biosphere connect, and therefore research in earth-surface dynamics often involves connections with meteorology, hydrology, oceanography, geodynamics, and ecosystems, as well as human dimensions.
To support the broad range of computational activities and tools used in earth-surface dynamics research, the US National Science Foundation supports a facility called the Community Surface Dynamics Modeling System (CSDMS; https://csdms.colorado.edu). CSDMS develops and maintains a variety of open-source tools, protocols, and educational programs to coordinate computational research. To make model codes more findable and accessible, CSDMS maintains an online Model Repository where community members can share their codes together with metadata and bibliographic information. To enable interoperability and model coupling, CSDMS supports a language-agnostic interface standard called the Basic Model Interface (BMI). BMI describes a core set of functions that enable model codes to interoperate; the standard has been adopted by a variety of projects and agencies, such as the US NOAA, US Geological Survey, and Deltares. To bridge across different programming languages, CSDMS uses Python as a hub language, and provides a language interoperability tool that wraps codes with a Python front end such that coupling and analysis can be performed in Python scripts regardless of the underlying development languages. To support data access and model-data workflows, CSDMS uses Data Components: Python utilities that use BMI syntax to access various data sets programmatically. To support the rapid development and benchmarking of new models, CSDMS coordinates the development of Landlab Toolkit, a Python library that allows efficient construction of 2D grid-based codes using modular components. One lesson from CSDMS’ experience, however, is that tools and protocols like these are necessary but not sufficient. Educational resources and outreach programs are vital to encourage community adoption and contributions. Overall, parallels between the space-weather and earth-surface research communities suggest that there may be opportunities for sharing of resources and methodologies.
Author(s): Gamal Zayed
The American University in Cairo
Abstract: Ground-based navigation systems are indispensable in modern multidisciplinary applications, ranging from emergency response to precision agriculture. The integration of space weather data with these systems not only improves their accuracy and reliability but also aligns perfectly with the transition from theoretical models to operational services. This research explores the implementation of navigation location estimation using data from the Weak Signal Propagation Reporter Network (WSPRnet).
The WSPRnet database, part of the Ham Radio Science Citizen Investigation (HamSCI), offers extensive spatial coverage through voluntarily provided data. This dataset includes key parameters such as transmitter-receiver operation timestamps, frequency bands, grid locations, separating distances, callsigns, transmitter Signal to Noise Ratio (SNR), drift, power, and receiver azimuth and mode.
By utilizing the robust IntlWSPR transmitting beacon structure, which features approximately 40 active beacons globally distributed and continuously operating, we obtain a resilient, real-time dataset. These beacons transmit very low noise-buried signals around 23 dBm, allowing for reliable non-interfering location estimation functionality.
We evaluate the performance of our localization system by generating a test dataset through ideal calculations using the free space path loss propagation model. Our findings indicate that the HamSCI-based localization system achieves an acceptable error margin, with a worst-case scenario error of just 10 meters per grid.
Future work will involve the application of Artificial Neural Networks (ANNs) to incorporate additional ionospheric parameters, enhancing the precision of received power measurements for user location grids.
Acknowledgements: Special thanks to Prof. Nathaniel A. Frissell (W2NAF), lead of the Ham Radio Science Citizen Investigation (HamSCI), Mr. Gary Mikitin (AF8A), Radio Operators Expert, and Mr. Bill Liles (NQ6Z), HamSCI Community Diversity Recruitment Chair, and Case Western Reserve University in collaboration with the University of Scranton for their invaluable contributions. Special thanks for the financial support of U.S. National Science Foundation Grant AGS-2404997 and Amateur Radio Digital Communications (ARDC).
Author(s): Maksym Petrenko, Anders Lundkvist, Chinwe Didigu, Chiu Wiegand, Christine Verbeke, Christopher Light, Claudio Corti, Damian Barrous-Dume, Darren De Zeeuw, Edgar Russel, Elana Resnick, Elon Olsson, Jack Topper, Jack Wang, Jia Yue, Joshua Pettit, Joycelyn Jones, Karen Scheiber, Katherine Garcia-Sage, Kornyanat Hozumi, Leila Mays, Liutauras Rusaitis, Lutz Rastaetter, Martin Reiss, Masaru Kogure, Masha Kuznetsova, Matthew Lesko, Maya Levisohn, Michelle Mendoza, Min-Yang Chou, Mostafa El Alaoui, Peter Macneice, Phil Poole, Poly Manessis, Richard Mullinix, Sandro Taktakishvili, Sarabjit Bakshi, Tina Tsui, Tyler Schiewe, Yihua Zheng, Yuta Hozumi
Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Centre for mathematical Plasma Astrophysics, Katholieke Universiteit Leuven, Leuven, Belgium; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Abstract: Over the span of 20 years, the Community Coordinated Modeling Center (CCMC) has been leading a number of community-driven services and applications that provide a free and open access to the cutting-edge space weather and Heliophysics models through a simple web-based interface. CCMC also oversees an open archive of user model simulations and related metadata, maintains space weather-related data streams, curates validation and event datasets, and more.
To maximize utility of its complementary services and data holdings, CCMC has been gradually building up an ad-hoc set of interfaces and specifications that facilitate coupling and interconnection within the organization, while also simplifying management and monitoring of the data streams. As the models continue to grow in maturity and complexity, CCMC is looking to reduce the complexity for its end users by making some of the internal APIs publicly available as well as implementing dedicated interfaces as required by the community. In this presentation, we will overview the current run services at CCMC and will describe our current and near-future efforts in providing interfaces to these services.
Author(s): Peter J. Kirsch, Sarah A. Glauert, Pak Yin Lam
British Antarctic Survey; British Antarctic Survey; British Antarctic Survey
Abstract: The British Antarctic Survey Radiation Belt Model (BAS-RBM) is a physics-based model of the Earth’s radiation belts that was initially conceived as a research tool to investigate the behaviour of this highly dynamic environment. Over the course of several projects the model has evolved as a research tool, but it has also become the basis of two space weather forecasting systems, providing information on the radiation environment for satellite operators, insurers and designers. Since 2019 we have been providing 24/7 nowcasts and forecasts on the European Space Agency space weather portal (SaRIF) and recently we have deployed a similar system to the UK Met Office. These systems collect real-time data from multiple providers, process it to create model inputs, run the BAS-RBM, use the BAS-RBM output to simulate the effect of the environment on satellites and produce a series of graphical displays with varying levels of detail. We will briefly describe the model itself before discussing the real-time systems that we have developed to provide the forecasts. We will discuss the challenges and lessons learnt in turning a research tool into an operational system.
Posters
Posters I Display Tue 5/11 – Wed 6/11, room C1A – Aeminium
Authors in attendance: Tue 5/11 10:15–11:30, 15:15-16:15; Wed 6/11 10:15–11:30
Author(s): Shane Maloney, Sophie Murray, Peter Gallagher, Alasdair Wilson, David Connolly, Imogen Nagle, Paul Wright
Dublin Institute for Advanced Studies; Dublin Institute for Advanced Studies; Dublin Institute for Advanced Studies; University of Oxford; Technical University Dublin; Brown University; Dublin Institute for Advanced Studies
Abstract: For over 2 decades, Solarmonitor.org has presented scientists, forecasters, and the general public with an up-to-date summary of solar activity. This includes observational data in the form of in-situ and remote observations and derived data such as coronal hole mapping and flare forecasts.
The system was originally written with a combination IDL, PHP, HTML and CSS and is overdue for a significant update. SolarMonitor 2 combines imaging and timeseries data from space missions such as Solar Orbiter, SDO, GOES, and STEREO with ground-based observations, derived data and meta-data, such as events or active region information. It is a near real-time, integrated tool for monitoring solar activity as well as providing historical data all via a fast, easy-to-use and reliable website and API.
SolarMonitor 2 aims to improve on the original with a streamlined user experience, by providing an even more extensive suite of data products and, most importantly, by increasing reliability and reducing the cost of continual development. This has been achieved with a switch to a modern, robust Python, JavaScript and SQL based application framework.
We present a look at the framework that has made this possible, the current status of the project, the future direction of the project and how the community can be involved in shaping this revamped website, which we hope will continue to serve the solar community for decades more to come.
Author(s): Kerry Lee, T. Paul O’Brien, Tim Guild, Alex Boyd
The Aerospace Corporation; The Aerospace Corporation; The Aerospace Corporation; The Aerospace Corporation
Abstract: There is a need to be able to produce survivability specifications for the natural radiation environment and the resulting effects for a spacecraft mission. Over the years more environment models have become available for the various sources of the natural radiation environment. These sources include Earth’s atmosphere, trapped radiation, solar plasma, solar energetic particles, and galactic cosmic rays. These host of models have been developed with the goal to predict the state of these sources at any point in space at any given time. There are also a wide range of radiation transport modeling options to choose from to calculate the particle and energy spectra that arrive at the regions of the spacecraft where effects are needed to be known for proper part, material and shielding selections. The fidelity of radiation transport that is required can vary greatly depending on mission parameters and requirements. The more detailed transport can be costly in terms of time and computation resources and if such detail isn’t needed then more approximated and faster options can be chosen. The resulting environment at the regions of interest are then used as inputs to response functions and effects models to determine the kinds of effects that can be expected in mission. A spacecraft mission planner desires to have the results from the chain of models for environmental, radiation transport and effects that are thought to provide the required accuracy while minimizing the resources needed for the assessment for that particular spacecraft mission. It is also desirable to be able to easily add in new models as they become available and to compare to legacy specifications that were created using older model tool chains. The Space Environment Effects Digital Laboratory is under development at Aerospace that will allow for ‘a la carte’ model selection that permits any included models to be chained together into an integrated package, that will then produce concise templated reports with data and graphs of the environment and effects to spacecraft components for a specified mission or comparing various notional missions for a given spacecraft geometry.
Author(s): Balazs Asztalos, Timothy Butterley, Szabolcs Soós, Marianna Korsós, Noémi Zsámberger, Steven Wrathmall, Robertus Erdélyi
1Department of Astronomy, Eötvös Loránd University, Budapest, Hungary; Durham University, UK; 1Department of Astronomy, Eötvös Loránd University, Budapest, Hungary; 5Solar Physics and Space Plasma Research Centre (SP2RC), School of Mathematics and Statistics (SoMaS), University of Sheffield, UK; 5Solar Physics and Space Plasma Research Centre (SP2RC), School of Mathematics and Statistics (SoMaS), University of Sheffield, UK; Durham University, UK; 5Solar Physics and Space Plasma Research Centre (SP2RC), School of Mathematics and Statistics (SoMaS), University of Sheffield, UK
Abstract: The Solar Activity Monitor Network (SAMNet) is an international network development of ground-based solar telescope stations with the mandate to continuously monitor the Sun’s magnetic and Doppler velocity fields at multiple heights in the solar atmosphere (from photosphere to upper chromosphere) [1]. The objective of SAMNet is to provide observational data for space weather research and forecast by utilizing telescopes equipped with magneto-optical filters (MOFs) to take observations in the K I, Na D and Ca I spectral bands. A prototype of the telescope was established at Gyula, Hungary to prove the concept and to establish the necessary scientific and technical backbone before the global rollout. A robust image processing pipeline has been built and will be presented that pushes the scientific data through a meticulous process considering SOLARNET’s metadata recommendations to ensure that this new data can be shared and used widely within the research community [2]. Scientific images taken in the K I spectral band go through the processing pipeline resulting in magnetograms and Dopplergrams, showing the conditions in the solar atmosphere ~400 km above the photosphere. Science-ready magnetograms were obtained with the help of first calibrating the Dopplergrams based on theoretically modelling the Doppler velocity for the Sun at the time of the scientific image capture.[1] Erdelyi, R. et al., (2022). The Solar Activity Monitor Network – SAMNET. Journal of Space Weather and Space Climate, 12, 2. https://doi.org/10.1051/swsc/2021025[2] Haugan, S.V.H. and Fredvik,T., SOLARNET Metadata Recommendations for Solar Observations, 2020, DOI:10.5281/zenodo.5719255
Author(s): Jun Wang, Tzu-Wei Fang, Dominic Fuller-Rowell, Sarah Schultz Beeck
CU-Boulder CIRES; NOAA Space Weather Prediction Center; NOAA Space Weather Prediction Center and CU-Boulder CIRES; Technical University of Denmark, DTU Space
Abstract: Ionospheric scintillations disrupt GNSS positioning and navigation systems. Existing mitigation strategies primarily depend on ionospheric Total Electron Content (TEC) and scintillation products derived from ground-based GNSS measurements. However, these methods lack global coverage, particularly over oceans and remote areas.
This study investigates the feasibility of using commercial Low-Earth Orbit (LEO) constellations to create a global ionospheric scintillation specification. We combined data from the commercial LEO constellations Spire Global and PlanetiQ with existing ground-based and LEO data (including COSMIC-2) to achieve real-time, global coverage.
GNSS-LEO geometries introduce technical challenges, such as downlink trigger metrics and the need for Radio Frequency Interference (RFI) mitigation. Additionally, geolocation of the scintillating plasma volume and converting scintillation magnitude from LEO to ground-based GNSS geometry require further research.
The National Oceanic and Atmospheric Administration’s (NOAA) Space Weather Data Pilot (SWDP) project assessed the suitability of commercial LEO data for operational space weather applications. The project concluded that TEC data from commercial sources is nearing operational readiness, while low-latitude scintillation data shows promise but requires further validation. High-latitude scintillation data needs significant development.
Key findings from the SWDP highlight the need for advancements in:
Limb-to-disk (L2D) processing algorithms for estimating scintillation on ground-based receivers.
Geolocation of GNSS-RO-based scintillation observations.
Scintillation detection algorithms, potentially utilizing Machine Learning (ML) for anomaly identification.
Scintillation downlink trigger algorithms in high-inclination orbits for phase scintillation detection
The SWDP project significantly advanced the development of operational ionospheric products from commercial GNSS-RO data, particularly for TEC and low-latitude scintillation. With further development, commercial LEO data has the potential to revolutionize global ionospheric scintillation monitoring.
Author(s): Juan Emmanuel Johnson, Christoph Schirninger, Robert Jarolim, Anna Jungbluth, Lilli Freischem, Anne Spalding, Cormac Purcell, Richard Galvez, Noah Kasmanoff, James Parr
CSIC-UCM-IGEO; Universitat Graz; Universitat Graz; ESA; University of Oxford; Trillium; Trillium; FDL-X; AE Studio; Trillium
Abstract: There are a variety of instruments that are used to study and monitor the Sun including ground-based observatories and space telescopes. Regular technological improvements including different instrumentation, different image characteristics, and atmospheric correction procedures, produce a variety of data products making it difficult to obtain harmonized datasets that make use of the full spectrum of information available. Furthermore, there are various applications which need these harmonized datasets; like solar cycle studies, multi-viewpoint investigations, or mitigating atmospheric seeing effects.
In this work, we present ITI (Instrument to Instrument translation) an AI-based tool (Jarolim et al., 2023), which is capable of translating datasets from two different domains. The tool is based on a Generative Adversarial Network (GAN) with unpaired image-to-image translation. It allows one to translate two datasets from different domains without spatial and temporal overlap. This enables image enhancement, instrument intercalibration, and super-resolution observations across multiple wavelength bands.
We tested the ITI tool on data from the 1.5 m GREGOR telescope to mitigate atmospheric seeing effects. For instrument intercalibration, enhance space-based solar observations, and achieve super-resolution, ITI was applied to data from Solar Orbiter, PROBA2, and the Solar Dynamics Observatory (SDO).
The results showed promise which demonstrates that ITI is a powerful tool that can be applied to various problem settings in solar physics.
Author(s): Gamal Zayed
The American University in Cairo
Abstract: The ionosphere plays a critical role in the propagation of RF signals, making it a key factor in intercontinental communications. This study explores the utilization of RF signal reflections within the ionosphere for enhancing communication reliability between Ham radio nodes, with an emphasis on the implications of space weather phenomena on signal propagation.
Leveraging the Weak Signal Propagation Reporter (WSPR) network, which provides a global dataset of real-time beacon transmissions, this research integrates the WSPRlive dataset with the Friis propagation model to develop an effective localization algorithm. The process involves two primary stages: (1) the creation of a comprehensive reference dataset through the calculation of ideal received powers based on continuous beacon data, and (2) the implementation of a Received Signal Strength (RSS)-based localization algorithm to estimate positions accurately.
The resulting data grid, comprising approximately 65.5 thousand locations, serves as a robust framework for analyzing signal propagation affected by ionospheric conditions. Our findings indicate that the proposed method achieves an absolute localization error of less than 10 meters, demonstrating its precision in a variety of environments.
Understanding how space weather impacts ionospheric conditions is essential for improving the resilience of communication systems. By examining the correlation between our localization data and variations in ionospheric electron content, we can infer the influence of space weather events on signal propagation. This approach provides valuable insights into the dynamics of the ionosphere and helps in predicting and mitigating the adverse effects of space weather on communication channels.
Future work will focus on enhancing the localization algorithm using Artificial Neural Networks (ANNs) to refine the WSPR channel propagation models further. This will improve real-time applications, offering more accurate predictions of ionospheric conditions and contributing to the development of more robust global communication systems.
Author(s): Z. Iqbal, I. Sandberg, S. Clucas, P. Truscott, D. Heynderickx
SPARC; SPARC; ESA; Kallisto Consultancy; DHConsultancy
Abstract: In the pursuit of converting models and data into practical services, the ESA Network of Models (ESA NoM) – originally designed to access and utilise space radiation environment and effects tools – represents a significant advancement as a software environment. ESA NoM can be employed to develop operational services that ingest real-time datasets and run space radiation models and effects tools within automated pipelines, significantly enhancing the efficiency and accuracy of space weather forecasting and analysis.
This presentation will explore the features and functionalities of ESA NoM, developed as part of the LeNoM project, and provide a comprehensive demonstration of its capabilities, highlighting its efficiency, robustness, and security. Key aspects such as the automation of data processing, real-time model execution, and the integration of diverse datasets will be showcased to illustrate how ESA NoM streamlines complex workflows.
ESA NoM has the potential to reduce the resources and maintenance typically required for data accessibility, model development, and deployment. By standardising metadata specifications and leveraging generic APIs, ESA NoM aligns with efforts to create more cohesive and unified software environments for operational services. This standardisation not only simplifies the integration of new models and datasets but also ensures compatibility and interoperability across different systems and platforms including cloud and on-premise.
Furthermore, ESA NoM aims to foster enhanced knowledge sharing and collaboration among users, developers, and scientists. By providing a centralised platform that supports the dissemination of information and resources, ESA NoM helps prevent the duplication of efforts and promotes a more collaborative and efficient space weather services community. The platform encourages the sharing of best practices, tools, and techniques, thereby accelerating innovation and improving the overall quality of space weather predictions.
In summary, ESA NoM represents a significant leap forward in the field of space weather services. Its advanced capabilities, coupled with a focus on efficiency, security, and collaboration, make it an invaluable tool for the space weather community, paving the way for more accurate and reliable operational services.
Acknowledgments
This work has been supported through ESA contract 4000139878/22/NL/CRS
Author(s): Camilla Scolini, Lukas Vinoelst, Yana Maneva, Jennifer O\’Hara, Freek Verstringe, Véronique Delouille, Judith de Patoul
Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium; Solar-Terrestrial Centre of Excellence – SIDC, Royal Observatory of Belgium
Abstract: Research to operations and operations to research (R2OO2R) has been a key topic of discussion for the last years and although we can see large strides in the areas of research to operations, with new models being introduced and run operationally, often the operation to research falls behind.
One of the vital components for Operations to Research (O2R) is having reliable datasets and catalogues for developing and testing new capacity. In recent years, various event catalogues and datasets have been developed, covering both manually and automatically detected events, such as flares, sunspots, CMEs, K-indexes, coronal holes, and more. Some, like the NOAA Active Regions list produced by SWPC, have also become standard references for research.
The SIDC is developing a dedicated workflow for forecasters to analyze and catalogue space weather events using multiple information sources, including existing catalogues, automated detections, and advance models. The “SIDC Moderated Solar Weather Event List,” available through the ESA SWE portal, currently includes SIDC sunspot groups, SIDC solar flares, and SIDC coronal holes. This list employs a versioning database system that allows for updates and tracking, enabling forecasters to adjust the data as new information emerges. These distinct datasets are often studied separately. To support research on chains of events from solar sources to their impacts on Earth, forecasters use their real-time analysis expertise to identify relationships between events, such as recurring sunspot groups, coronal holes, and the connections between sunspot groups and flares. They also integrate SIDC event data with other catalogues, such as associating sunspots with NOAA active regions.
This presentation will explain how duty forecasters capture and document event analysis and event chains with their interrelationships sharing insights and proposing strategies for open development and resource sharing. It will also detail plans to enhance the service with new models, datasets, and connections, such as CME lists, solar radio bursts, solar wind shocks, geomagnetic storms, or ICMEs from EUHFORIA models, integrating these with other cataloged events. Additionally, we will discuss the benefits of the new SIDC catalogue for research and compare it to the CCMC DONKI catalogue.
Author(s): Gamal Zayed
The American University in Cairo
Abstract: Global Navigation Satellite System (GNSS) reliability is essential for diverse applications, particularly in mitigating ionospheric disturbances’ impact. This study advances the prediction and optimization of ionospheric vertical total electron content (VTEC) using the NeQuickG model, driven by Galileo coefficients. NeQuickG, a globally recognized ionospheric model, offers high spatial and temporal resolution, sanctioned by the European Space Agency for Galileo users.
Our innovative approach integrates Particle Swarm Optimization (PSO) to precisely forecast VTEC peaks, identifying critical latitude, longitude, and time parameters. Using recent Galileo coefficients from NASA’s Geodesy CDDIS archive, we enhance VTEC prediction accuracy. This methodology not only provides vital insights for atmospheric and ionospheric research but also significantly improves GNSS data assimilation and operational service reliability. By anticipating high VTEC conditions, we bolster GNSS signal integrity, crucial for applications in navigation, communication, and space weather services, ensuring robust operational performance.
Author(s): Pete Truscott, Daniel Heynderickx, Simon Clucas
Kallisto Consultancy Ltd; DH Consultancy BV; European Space Agency
Abstract: Most of the current systems of tools to model space radiation environments and effects assume one or a few standard workflows which the user must follow to perform their analysis. This means that in non-standard analyses, the user must often intervene in the workflow to perform additional processing on results files using custom Python, Matlab, etc., code, before “re-injected” new results back into another part of the system’s workflow. In contrast, SPECTIRES is a Python-based toolkit that can be easily adapted to their own workflow all in one programming environment. The key features of the toolkit are:
It provides access to many of the standard environments and effects models implemented locally either directly as Python versions or through interfaces with the models’ Fortran/C++ libraries.
Geant4 shielding analysis models such as MULASSIS, GRAS, and SSAT can also be run through interfaces g4_space_apps docker containers, developed under the ESA HIERRAS Project.
The user can alternatively execute models on ESA’s Network of Models (NoM) server in an almost identical fashion to running them with the local models.
Interfaces exist with local and online ODI databases to process space instrument spectra and to generate effects predictions for those environments.
The strong object-oriented nature of the toolkit allows a user to set up and run different models using common object definitions to allow the results from one model to be passed seamlessly to the next, and without the need for interface files. It also overcomes the problem of managing data at a granular (primitive- variable) level. Instead, the user manages single, high-level quantities (objects) representing, e.g., orbital elements, trajectories, spectra, dose, counts, etc., and the operators (e.g., trajectory generators and radiation belt models) which convert these quantities into other forms, in this case orbital elements to trajectory objects and then to spectra objects.
This presentation will describe the SPECTIRES toolkit and the benefits or otherwise of using the object-based data-management and model interface approach as the “modelling engine” in the development of new systems for different applications, including well-defined networked and real-time operational services to more experimental local systems exploring different data processing methods.
Author(s): Charlotte Martinkus, Manasi Gopala, Michael Husler
Cooperative Institute for Research in Environmental Sciences (CIRES), Univ. Colorado Boulder; NOAA Space Weather Prediction Center (SWPC); NOAA Space Weather Prediction Center (SWPC)
Abstract: The International Civil Aviation Organization (ICAO) was established by the United Nations to encourage collaboration and standardization of hazards within the aviation community. Given the dangerous impacts of space weather on aviation, ICAO created a space weather branch with operational centers around the world, the United States’ Space Weather Prediction Center (SWPC) among them. This work details the latest advisory application SWPC is developing to both comply with ICAO requirements and empower forecasters with intuitive polygon drawing functionalities and advanced data visualizations. The software facilitates precise forecasting by allowing users to effortlessly draw polygons directly onto interactive maps, enabling the delineation of specific areas of interest with unprecedented accuracy. Moreover, the software offers a comprehensive suite of data visualization tools, presenting critical model data in dynamic and informative formats. Through interactive maps, charts, and overlays, forecasters can now gain deeper insights into space weather patterns, trends, and anomalies, facilitating more informed decision-making. By amalgamating cutting-edge technology with user-centric design principles, this software redefines the standards of space weather forecasting within the realm of aviation. The application is intended to be operational by the end of year, 2025.
Author(s): Antoine Ferlin, V. Maget, S. Poedts, C. Papadimitriou, I. Sandberg, S. Aminalragia-Giamini, Z. Iqbal, M. Dierckxsens, N. Ganushkina, S. Dubyagin, K. Schiess, J. Neijt, J. Lichtenberger, B. Heilig, I. Daglis, C. Katsavrias, A. Isavnin, A. Glover, R. Keil, H. Evans
ONERA; ONERA; KU Leuven; SPARC; SPARC; SPARC; SPARC; BIRA-IASB; FMI; FMI; Solenix; Solenix; ELTE; SSE; IASA; IASA; Ray of Space; ESA/ESOC/OPS-SW; Rhea System GmbH for ESA/ESOC/OPS-SW; ESA/ESTEC-TEC/EPS
Abstract: In the frame of the ESA Space Safety Programme’s Space Weather Service Network (S2P), the Radiation Belt Forecast And Nowcast framework 2(RB-FAN 2) has been developed to nowcast and forecast the particle populations and their dynamics within the radiation belts.
This project is the logical continuation of RBFAN project (ESA Space Situational Awareness Program) and aim at providing new risk indicators depending on the orbit, to improve the forecast of Earth radiation belts impact on spacecraft and human spaceflight. They will allow to extend current RBFAN website, already available throughout the SWE Service Network.
This new project supported by ten institutes and companies study all aspects from the architecture design to the user requirements, including modelling/simulation consideration, and provision of products to end-users.
The RBFAN framework currently used in the SWE Service Network is composed of several models chained thanks to VSWMC, the Virtual Space Weather Modelling Centre, from EUHFORIA models, to IMPTAM model. Salammbô-DA provides the forecast of the radiation belts dynamics using IMPTAM and EUHFORIA outputs, both for electrosn (100 keV up to 8 MeV) and protons (1 MeV up to 400 MeV). A data assimilation process is also used to enhance and correct the radiation belt dynamic, using in situ measurements coming from different databases (ONERA -IPODE, BIRA-IASB and SPARC).
In the new environment, three additional models will upgrade RBFAN framework. The PLASMA model provides information about plasmasphere density evolution, as well as location and shape of the plasmapause. EMERALD will provide to Salammbô-DA the radial diffusion coefficient inside radiation belt as a function of time. Finally, Solar Proton Event (SPE) model will provide alerts of SEP events in the coming 24 hours as well as estimation of the total fluence of the expected/ongoing event.
The website will also be upgraded in order to enhance the end-users experience. In addition to new indicators of interest for end-users on demand computation of specific products for given orbits will be made available throughout the web interface.
Acknowledgement: This work is supported by the S2P S1-SW-14.2 Space Environment Nowcast and Forecast Development – Part 2 activity RB-FAN2 under contract number “4000140076/22/D/KS”.
Author(s): Benjamin Reid
SERENE / University of Birmingham
Abstract: The International Reference Ionosphere (IRI) is a global empirical model of the ionosphere. The ionosphere exhibits variability on smaller spatial and temporal scales than the climatological IRI can resolve, particularly during periods of elevated geomagnetic activity. This has lead to a great deal of interest in using data assimilation to augment the IRI, including producing a real-time ionospheric specification or nowcast. The limitations of the IRI are shared by other empirical climatological models, such as the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM) or the NeQuick model. The Advanced Ionospheric Data Assimilation (AIDA) model is an operational, real-time data assimilation model of the global ionosphere and plasmasphere. It uses NeQuick as a background state, and so is effectively a high-resolution, real-time NeQuick. AIDA assimilates live data streams from over 2000 Global Navigation Satellite System (GNSS) receivers worldwide, along with automatically scaled ionosonde data from the Global Ionosonde Radio Observatory (GIRO). AIDA uses a Monte Carlo data assimilation technique known as a Particle Filter to ingest the nonlinear slant Total Electron Content (sTEC) observations produced by the GNSS receivers. This same technique can be used to assimilate this data into any ionospheric model, including the IRI. This study will examine how the existing AIDA framework can be adapted to produce a real-time ionospheric specification and forecast based on the IRI.
Author(s): B. Tezenas du Montcel, B. Jeanty-Ruard, A. Trouche, J. Forest, N. Chabalier
Artenum, Toulouse, France; Artenum, Toulouse, France; Artenum, Toulouse, France; Artenum, Paris, France; Artenum, Toulouse, France
Abstract: Space environment is populated by a wide variety of energetic particles, whether they originate from the sun, are trapped by planetary magnetic fields, or come from cosmic sources, they are sources of significant threats to the spacecraft integrity. To address the estimation of these threats, Artenum has developed a wide variety of physical tools regrouped within the SpaceSuite solution.
Among the environmental threats, the total ionizing dose (TID) can affect spacecraft devices by degrading electronic components, causing memory errors, reducing sensor sensitivity, or damaging optoelectronic devices and SpaceSuite includes several software able to estimate the TID. The Sector Shielding Analysis Module (SSAM), based on ray tracing and sector shielding analysis methods offers a quick and easy way to calculate this TID.
A validation of SSAM has been carried out by comparing the dose deposited on a CubSat in interplanetary medium. Next illustration cases are
Proposed on a realistic 1U CubeSat using realistic and variable environments, including radiation belt electron flux spectra deduced from the Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER). These results are a proof of concept for an operational service computing cumultaive TID using data from space weather forecast such as the ones used in PAGER.
Author(s): Mike Heyns, Adrian LaMoury, Norah Kwagala, Jonathan Eastwood
Imperial College London; Imperial College London; University of Bergen; Imperial College London
Abstract: Providing actionable space weather forecasts has become crucial in ensuring the resilience of modern infrastructure in the face of severe geomagnetic storms. Physics-based models, such as global magnetohydrodynamic (MHD) simulations, provide an attractive approach to deliver generalised forecasting products globally. Here we present recent developments withing the ESA Bergen-Imperial Global Geospace (BIGG) project, and specifically the deployments of the GorgonOps and SWMF forecasting suites in this platform. These modelling suites are running faster than real-time in an operational context to deliver tailored space weather forecasts for the European sector. Key aspects of GorgonOps are discussed, including its implementation at the UK Met Office as part of the SWIMMR programme and its current real-time service provision at Imperial College London. We will demonstrate the forecasting paradigm utilised, highlighting the adaptive forecast horizon and use of ground field measurements to constrain forecast baselines. Validation efforts within this paradigm are showcased, focusing on the accuracy and reliability of the model’s forecasts during recent geomagnetic storms. We will discuss the implications of these findings and provide recommendations for future deployments across the space weather forecasting community. Additionally, we will introduce the current service provision of real-time data access and visualisation at Imperial College London.
Author(s): Amandine Finot, Sébastien Hess, Julien Jarrige, Ludivide Leclercq, Pierre Sarrailh
ONERA; ONERA; ONERA; ONERA; ONERA
Abstract: Because of the interaction between the surrounding plasma of the magnetosphere and their surfaces, spacecrafts in orbit are submitted to electrostatic charging. As their surfaces are made with diverse materials, with different properties, differential charging could occur and ultimately formation of electrostatic discharge (ESD) that may damage the spacecraft. To extend satellites time in operation, preventing and predicting the appearance and the characteristics of ESD is crucial. This is done by performing charging simulations using software such as the Spacecraft Plasma Interaction Software (SPIS) developed in Europe and widely used across the world.
In order to provide good prediction of the electrostatic risk on spacecraft, the software requires a good description of the space environment and of its dynamic. Thus, we developed an interoperability layer between the space environment databases using the SPASE standard and SPIS which allows to computed the spacecraft electrostatic charge in representative and dynamic environments.
However, the dynamic of charging in the current version of SPIS does not consider the dynamics of ESDs, allowing for the final computed potential could reach thousands of volts, while ESDs occur at much lower voltage difference. Thus, we developed more advanced simulations including the partial discharge by ESD : when the onset threshold is reached, the ESD occurs and discharges partially the spacecraft. This allows us to predict the ESD occurrence periodicity and their characteristics (current, released energy…) that determine the risk for the spacecraft.
Hence, SPIS is now able to links actual space weather events to operational spacecraft ESD risk management.