Semi-annual, annual and Universal Time variations in the magnetosphere and in geomagnetic activity: 3. Modelling
Bibliographic record
Abstract
This is the third in a series of papers that investigate the semi-annual, annual and Universal Time variations in the magnetosphere. In this paper, we use the Lin et al. (2010) empirical model of magnetopause locations, along with the assumption of pressure equilibrium and the Newtonian approximation of magnetosheath pressure, to show that the equinoctial pattern arises in both the cross-tail current at the tail hinge point and in the total energy stored in the tail. The model allows us to study the effects of both dipole tilt and hemispheric asymmetries. As a test of the necessary assumptions made to enable this analysis, we also study simulations by the BATSRUS global MHD magnetosphere model. These also show that the reconnection voltage in the tail is greatest when the dipole tilt is small but this only applies at low solar wind dynamic pressurepSWand does not, on its own, explain why the equinoctial effect increases in amplitude with increasedpSW, as demonstrated by Paper 2. Instead, the effect is consistent with the dipole tilt effect on the energy stored in the tail around the reconnection X line. A key factor is that a smaller/larger fraction of the open polar cap flux threads the tail lobe in the hemisphere that is pointed toward/away from the Sun. The analysis using the empirical model uses approximations and so is not definitive; however, because the magnetopause locations in the two hemispheres were fitted separately in generating the model, it gives a unique insight into the effect of the very different offsets of the magnetic pole from the rotational pole in the two hemispheres. It is therefore significant that our analysis using the empirical model does predict aUTvariation that is highly consistent with that found in both transpolar voltage data and in geomagnetic activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".