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Solar Surface Magnetic Field Simulation Enabled Prediction of the Large-Scale Coronal Structure of the 21 August 2017 Great American Eclipse: An Assessment of Model Predictions and Observations
- Publication Year :
- 2017
-
Abstract
- On 21 August 2017 a total solar eclipse swept across the contiguous United States providing excellent opportunities for diagnostics of the Sun's corona. The Sun's coronal structure is notoriously difficult to observe except during solar eclipses; thus theoretical models must be relied upon for inferring the underlying magnetic structure of the Sun's outer atmosphere. These models are necessary for understanding the role of magnetic fields in the heating of the corona to a million degrees and generation of severe space weather. Here we present a methodology for predicting the structure of the coronal field based on long-term surface flux transport simulations whose output is utilized to extrapolate the coronal magnetic field structures. This prescription was applied to the 21 August 2017 solar eclipse. Post-eclipse analysis shows good agreement between model simulated and observed coronal structures and their locations on the limb. We demonstrate that slow changes in the Sun's surface magnetic field distribution driven by long-term flux emergence and evolution govern large-scale coronal structures with a (plausibly cycle-phase dependent) dynamical memory timescale on the order of few solar rotations -- opening up the possibility of large-scale, global corona predictions at least a month in advance.<br />Comment: Revised version of manuscript detailing the methodology, models and data utilized to predict the coronal magnetic field structure of the solar eclipse on 21 August, 2017, now including post-eclipse comparisons between predictions and observations. This version replaces the older version and incorporates a correction in the PFSS rendering of the corona
- Subjects :
- Astrophysics - Solar and Stellar Astrophysics
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1708.05996
- Document Type :
- Working Paper