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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SKA's higher sensitivity and bandwidth will enable fuller exploitation of radio methods for measuring CME magnetic fields and improving space weather predictions.
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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Role of SKA in Advancing Remote Measurements of Magnetic Fields of Solar Coronal Mass Ejections
SKA's higher sensitivity and bandwidth will enable fuller exploitation of radio methods for measuring CME magnetic fields and improving space weather predictions.