On Solutions of the PFSS Model With GONG Synoptic Maps for 2006–2018
Bibliographic record
Abstract
Abstract The potential field source surface (PFSS) model is widely used to derive the magnetic field of the solar corona. The only free parameter in the PFSS model is the radius of the so‐called source surface, where magnetic field lines are forced to open. The radius of this surface is typically set to 2.5 solar radii in research and operational PFSS numerical models. Here, using Global Oscillation Network Group (GONG) synoptic maps of the photospheric field, solutions of the PFSS model for various heights of the source surface are investigated for 2006–2018. In particular, numerically derived open solar magnetic flux and coronal holes are examined. Solutions of the PFSS model based on GONG synoptic maps are particularly important since they are often used to drive operational space weather forecast models. Comparisons between observations and numerical results in this paper suggest that the radius of the source surface is significantly lower than 2.5 solar radii during the active phase of solar cycle 24. The fact that the source surface location depends on the solar activity suggests that relations which associate solar wind properties with the coronal magnetic field in the PFSS‐based solar wind modes should be revisited. Furthermore, although the correction of the polar magnetic field is part of GONG synoptic map production pipeline, the results suggest that better treatment of polar fields is needed to cover observational gaps. The issue with the polar fields in GONG maps is particularly pronounced in recent years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".