An automated pipeline forecasts CME magnetic fields at L1 using initial magnetic obstacle data, achieving errors of roughly 5 hours in timing and 10 nT in strength comparable to full-event reconstructions.
J., Nieves-Chinchilla, T., & M¨ ostl, C
2 Pith papers cite this work. Polarity classification is still indexing.
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astro-ph.SR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
MHD modeling of the 2024 October 26 CME demonstrates that specific pre-eruptive magnetic flux rope footpoint locations and near-real-time background fields are required to reproduce observed complex morphology from multiple viewpoints without fine-tuning.
citing papers explorer
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Towards a Fully Automated Pipeline for Short-Term Forecasting of In Situ Coronal Mass Ejection Magnetic Field Structure
An automated pipeline forecasts CME magnetic fields at L1 using initial magnetic obstacle data, achieving errors of roughly 5 hours in timing and 10 nT in strength comparable to full-event reconstructions.
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Understanding the complex morphology of a CME II: how pre-eruptive conditions shape CME evolution
MHD modeling of the 2024 October 26 CME demonstrates that specific pre-eruptive magnetic flux rope footpoint locations and near-real-time background fields are required to reproduce observed complex morphology from multiple viewpoints without fine-tuning.