Seasonal and diurnal variations of geomagnetic activity and their role in Space Weather forecast
Bibliographic record
Abstract
A possible test for different models explaining the seasonal variation in geomagnetic activity is the diurnal variation. We computed diurnal variations both in the occurrence of large AE (auroral electrojet) indices and in the AO index. (AO is the auroral electrojet index that provides a measure of the equivalent zonal current.) Both methods show a similar diurnal variation in geomagnetic activity with a deep minimum around (37) UT (universal time) in winter and a shallower minimum near 59 UT in equinoctial months. The observed UT variation is consistent with the results of other scientists, but it is different from that expected from the RussellMcPherron mechanism proposed to explain the seasonal variation. It is suggested that the possible cause for the diurnal and seasonal variations may be variations in nightside ionospheric conductivity. Recent experimental results show an important role for ionospheric conductivity in particle acceleration and geomagnetic disturbance generation. They also show that low ionospheric conductivity is favorable to the generation of auroral and geomagnetic activity. The conductivity in conjugate nightside auroral zones (where substorm generation takes place) is minimum at equinoxes, when both auroral zones are in darkness. The low ionospheric conductivity at equinoxes may be a possible cause for the seasonal variation in the geomagnetic activity with maxima in equinoctial months. The diurnal variation in geomagnetic activity can be produced by the UT variation in the nightside ionospheric conductivity, which in winter and at equinoxes has a maximum around 45 UT that may lead to a minimum in geomagnetic activity at this time. We calculated the correlation patterns for the AE index versus solar-wind parameters inside and outside the (27) UT sector related to the minimum in geomagnetic activity. The correlation patterns appear different in these two sectors indeed, which is well consistent with the UT variation in geomagnetic activity. It also shows that it is possible to improve significantly the reliability of the Space Weather forecast by taking into account the dependence of geomagnetic activity not only on solar-wind parameters but also on UT and season. Our test shows that a simple account for the dependence of geomagnetic activity on UT can improve the reliability of the Space Weather forecast by at least 50% in the 27 UT sector in winter and equinoctial months. PACS No.: 91.25Le
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".