Conveners
CD5 - Open Validation in Space Weather Modeling: Orals - Part 1
- Barbara Perri (AIM - OSUPS)
- Martin Reiss (NASA CCMC)
- Evangelia Samara (NASA/GSFC)
- Karin Muglach
CD5 - Open Validation in Space Weather Modeling: Orals - Part 2
- Evangelia Samara (NASA/GSFC)
- Barbara Perri (AIM - OSUPS)
- Karin Muglach
- Martin Reiss (NASA CCMC)
Description
Progress in space weather research and forecasting depends on an accurate assessment of our current modeling capabilities. As space weather models become more complex and sophisticated, and play an increasingly important role in operational forecasting, the need for an improved validation infrastructure becomes clear. To enable meaningful model validation, this infrastructure must be based on comprehensive, reproducible, and consistent validation protocols. Developing these protocols requires community-wide initiatives to agree on essential physical properties, events or time periods, and metrics. Therefore, close collaboration between scientists, model developers, forecasters, and software engineers across space weather domains is needed.
In this session, we welcome contributions that highlight:
1) Progress in validating and verifying space weather and space science models;
2) Use of multi-spacecraft observations for model validation;
3) Development of software, tools, and repositories that facilitate open validation;
4) Applications of artificial intelligence and machine learning in space weather model validation;
5) Strategies for (near) real-time validation of space weather models and forecasts;
6) Community challenges and initiatives.
Geomagnetic indices such as the Dst index are relevant for quantifying global geomagnetic storm impacts, yet their operational forecasting remains constrained by reliance on solar wind measurements from L1-based spacecrafts like ACE or DSCOVR. Current models depend on near-real-time L1 data to make the predictions, creating a fundamental limitation: the magnitude of the geomagnetic storm...
Electrons in Earth’s radiation belts exhibit significant variability in both space and time during geomagnetic storms, posing potential risks to satellites and astronauts. Physics-based models aim to describe the behavior of energetic electrons in the radiation belts but often face challenges due to uncertainties and inaccuracies, especially in the initial and boundary conditions. Data...
The ionosphere and thermosphere are critical regions of Earth’s upper atmosphere, playing a significant role in technologies such as radio communication and Global Navigation Satellite Systems (GNSS). However, their variability, driven by solar and geomagnetic activity, as well as interactions with neutral molecules and the lower atmosphere, makes accurate prediction of their state...
In this study, we present the results of a comprehensive assessment of thermosphere models under geomagnetic storm conditions, defined by a geomagnetic index ap ≥ 80. This work builds upon Bruinsma et al. (2024, DOI: 10.1051/swsc/2024027), which evaluated the performance of empirical and physics-based thermosphere models during storm periods. Utilizing models hosted at NASA's Community...
The ionosphere is a significant error source in radio communication and modern GNSS satellite navigation. Variations in electron density, especially during the geomagnetic storm, can lead to signal distortion, fading, and transmission delays. Therefore, accurately predicting and forecasting ionospheric conditions is essential for mitigating these effects, which requires the use of advanced...
Recurring Coronal Holes (CHs) are long-lived structures in the solar corona that survive over multiple solar rotations. They are generating high speed solar wind streams that can have a recurring geoeffective impact. For our study we employ the Potential Field Source Surface (PFSS) and the Schatten Current Sheet (SCS) models incorporated in the coronal modelling domain of EUHFORIA (European...
Coronal Holes (CHs) are the major source of origin of the fast solar wind, which is its most geo-effective component. Identifying the coronal hole configuration and the large-scale structures of the solar corona enables prediction of the solar wind at 1 AU, thus allowing validation of solar wind models in reference to 1 AU observations. In this work, we contribute to the WindTRUST project,...
Space weather forecasting needs fast and reliable prediction of the solar wind in the inner heliosphere. The complex physics of the corona, the turbulent heating and acceleration of the solar wind are thus often bypassed using empirical models driven by observations. In 2023, we introduced a novel technique based on white light coronagraph observations made by LASCO C2 to infer the state of...
One of the major challenges in space weather forecasting is to reliably predict the magnetic structure of interplanetary coronal mass ejections (ICMEs) in the near-Earth space. In the framework of global MHD modelling, several efforts have been made to model the CME magnetic field from Sun to Earth. However, it remains challenging to deduce a flux-rope solution that can reliably model the...
Building on the methods established in Edward-Inatimi et al. (2024), we calibrate an ambient solar-wind ensemble driven by the Wang-Sheeley-Arge (WSA) model. Ensemble methods are powerful tools which allow forecast uncertainty to be better characterised. Using a coupled coronal-heliospheric modelling approach we generate ensembles using the WSA model, used operationally, with the Heliospheric...
Many operational space weather forecasting frameworks are based on the Potential Field Source Surface (PFSS) model of the magnetic field. The output of PFSS serves as input in many heliospheric models that provide solar wind velocity predictions at L1. Previous studies in the context of prediction of open magnetic flux observed at L1 have suggested different source surface heights ($R_{ss}$)...
In this presentation I will review the current progress and challenges for improving forecasts of the geomagnetic effects of solar coronal mass ejections (CME), and will present a future roadmap, including metrics and validation efforts. This should not only include the solar wind drivers but also the magnetospheric response, which is facilitated through the combined expertise of a recently...
Accurate forecasting of solar wind is essential for space weather predictions, but uncertainties persist due to incomplete solar magnetic field observations of the Sun. Disentangling the impact of these limitations on solar wind predictions remains challenging. This research explores the sources of uncertainty in solar wind models caused by the lack of comprehensive full-Sun magnetic field...
Geomagnetic storms pose substantial risks to modern technological infrastructure, making accurate forecasting critical for mitigating their impacts on essential systems. Traditionally, space weather research has emphasized forecasting global geomagnetic indices. While these global indices provide valuable insights, local geomagnetic indices remain relatively understudied, despite their crucial...
