Semiannual variation of Pc5 ultra-low frequency (ULF) waves and relativistic electrons over two solar cycles of observations: comparison with predictions of the classical hypotheses
Bibliographic record
Abstract
Abstract. Pc5 ULF (ultra-low frequency) waves can energize electrons to relativistic energies of >2 MeV in geostationary orbits. Enhanced fluxes of such electrons can induce operational anomalies in geostationary satellites. The variations of the two quantities in timescales ranging from days to solar cycles are thus of interest in gauging their space weather effects over different time frames. In this study, we present a statistical analysis of two 11-year solar cycles (cycles 22 and 23) of data comprising the daily relativistic electron fluence observed by Geostationary Environment Satellites (GOESs) and daily Pc5 ULF wave power derived from auroral zone magnetic observatories in Canada. First, an autocorrelation analysis is carried out, which indicates a 27 d periodicity in both parameters for all solar phases, and such a periodicity is most pronounced in the declining and late declining phase. Also, a 9 and 13 d periodicity are seen in some years. Then, a superposed epoch analysis is performed to scrutinize semiannual variation (SAV), which shows that fluence near the equinoxes is 1 order of magnitude higher than near solstices, and Pc5 ULF wave power is 0.5 orders of magnitude higher near the equinoxes than near the solstices. We then evaluate three possible SAV mechanisms (which are based on the axial, equinoctial, and Russell and McPherron effect) to determine which one can best explain the observations. Correlation of the profiles of the observational curves with those of the angles that control each of the SAV mechanisms suggests that the equinoctial mechanism may be responsible for the SAV of electron fluence, while both the equinoctial and the Russell and McPherron mechanisms are important for the SAV of Pc5 ULF wave power. Comparable results are obtained when using functional dependencies of the main angles instead of the angles mentioned above. Lastly, superposed curves of fluence and Pc5 ULF wave power were used to calculate least-square fits with a fixed semiannual period. Comparison of the maxima and minima of the fits with those predicted by the three mechanisms shows that the equinoctial effect better estimates the maxima and minima of the SAV in fluence while for the SAV in Pc5 ULF wave power the equinoctial and Russell and McPherron mechanisms predict one maximum and one minimum each.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".