Studying the Impact of the Geospace Environment on Solar Lithosphere Coupling and Earthquake Activity
Bibliographic record
Abstract
In solar–terrestrial physics, there is an open question: does a geomagnetic storm affect earthquakes? We expand research in this direction, analyzing the seismic situation after geomagnetic storms (GMs) accompanied by the precipitation of relativistic electrons from the outer radiation belt to form an additional radiation belt (RB) around lower geomagnetic lines. We consider four widely discussed cases in the literature for long-lived (weeks, months) RBs due to GMs and revealed that the 1/GMs 24 March 1991 with a new RB at L~2.6 was followed by an M7.0 earthquake in Alaska, 30 May 1991, near footprint L = 2.69; the 2/GMs 29 October 2003 (Ap = 204) with new RB first in the slot region at L = 2–2.5 cases followed by an M7.8 earthquake on 17 November 2003 at the Aleutian Islands near footprint L = 2.1, and after forming an RB at L~1.5 which lasted for ~26 months, two mega quakes, M9.1 in 2004 and M8.6 in 2005, occurred at the globe; the 3/GMs 3 September 2012 with a new RB at L= 3.0–3.5 was followed by an M7.8 earthquake in Canada near footprint L = 3.2; and the 4/GMs 21 June 2015 with a new RB at L = 1.5–1.8 was followed by an M6.3 earthquake on 7 September 2015 in New Zealand, near footprint L = 1.58. The obtained results suggest that (1) major earthquakes occur near the footprints of geomagnetic lines filled with relativistic electrons precipitating from the outer radiation belt due to geomagnetic storms, and (2) the time delay between geomagnetic storm onset and earthquake occurrence may vary from several weeks to several months. The results may expand the framework for developing mathematical magnetosphere–ionosphere coupling models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".