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C. Bard

Publications and source records attributed to C. Bard.

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Advancing Heliophysics and Space Weather Modeling through Open Science

We present a community-wide effort to develop a strategy and action plan to advance heliophysics and space weather modeling through open science. While open science has the potential to enhance the quality and pace of scientific discovery, its application to scientific modeling requires more careful consideration regarding open data and open software guidelines, as scientific models differ significantly from data analysis software. We gathered feedback from modeling teams worldwide through a living survey and discussion sessions at the 2024 Open Science Workshop in College Park, USA, and at the 2025 COSPAR ISWAT Working Meeting in Cape Canaveral, USA. We complement these findings with lessons learned from almost 25 years of experience at the Community Coordinated Modeling Center in enabling open use of models. We identify key roadblocks in current open science practices and guidelines and offer recommendations for future progress across four overlapping themes: open use of models and simulation results, open validation, open development, and open collaboration. An essential outcome of the discussion is the need for model developers and model users to speak with a united voice and promote the role of models in future open science efforts. We introduce a new cross-domain community initiative called the Heliophysics Open Modeling Environment (HOME), which will be integrated as an overarching activity within COSPAR ISWAT. HOME will serve as a platform for modelers and model users to work together, facilitate community modeling, improve the scientific return on modeling investment, and advance understanding, modeling, and forecasting in heliophysics and space weather.

physics.space-ph

Elucidating the Grey Atmosphere: SHAP Value Analysis of a Random Forest Atmospheric Neutral Density Model

We apply SHAP (SHapley Additive exPlanations) analysis using the TreeSHAP algorithm to a Random Forest model (RANDM) designed to predict thermospheric neutral density based on solar-terrestrial data. The analysis shows that RANDM identifies solar irradiance as a significant predictor of thermospheric density. Additionally, the model differentiates between magnetic local times, finding that dusk sectors have higher densities than dawn sectors, in line with prior research. When comparing storm and quiet-time conditions, we find these trends persist regardless of geomagnetic activity levels. The analysis further demonstrates that larger geomagnetic disturbances during storms, as parameterized by the SYM-H index, are associated with higher neutral densities. Notably, SYM-H begins to have the overall largest contribution to density prediction among model inputs at a threshold of -60 nT. This suggests a quantitative definition where ``storm-time'' begins at SYM-H $< -60$ nT. Overall, using TreeSHAP enhances our understanding of the factors influencing thermospheric density and demonstrates the value of explainable machine learning techniques in space weather research, enabling more interpretable models.

physics.space-ph

On the role of system size in Hall MHD magnetic reconnection

We study the effects of the Hall electric field on magnetic island coalescence in the large island limit and find evidence for both a elongated electron current sheet layer with a Sweet-Parker-like reconnection rate and a collapsed, Petschek-like electron sheet with a peak reconnection rate approaching the 0.1 vA B0 Hall MHD rate. The state observed in our simulations appears to depend on grid scale. Furthermore, even at the largest system sizes, we find that flux-pileup effects cause the islands to "bounce" despite the presence of a collapsed current sheet allowing for fast instantaneous reconnection. The average reconnection rate in the large island limit is slow though the peak reconnection rate is fast.

physics.plasm-ph