Spectral features of Forbush Decrease during Geomagnetic Storms
Bibliographic record
Abstract
In this paper, we study the variations of the solar-wind parameters (solar wind velocity, plasma density, and IMF-B z component) and the Earth’s disturbance storm-time index (D st ), in relation to cosmic ray flux measurements from 8 neutron monitor stations distributed over Canada, Russia, Finland, and Greenland, during 3 intense geomagnetic storms occurred during the 24 th solar cycle (March 16-18, 2015, June 21-23, 2015, and September 7-9, 2017). The wavelet analysis of the Forbush decrease seen in the cosmic ray intensity reveals the clear evolution of the classical two-step process, and with a peak period of approximately 2.1 h. The correlation-delay analyses show a very strong correlation (~0.9) between the relative count rate changes cosmic ray intensity and the indices of solar wind velocity and D st . We obtain similar time-delay responses to the solar wind velocity for all the cases (~4 hours), but large discrepancies are seen for the D st index between the storms. We therefore recommend not using the D st index for predicting Forbush decreases. Finally, we employ the resulting delay-times to parameterize the Forbush decreases in terms of solar wind, and we obtain a predictive model with R 2 parameter of an approximate value of 0.8. Moreover, we observe a possible dependence on solar wind proton density which modulates the magnitude of Forbush decreases under similar solar wind velocity conditions. Our results verify the suitability of using solar wind parameters to predict Forbush decreases in the cosmic ray flux.
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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 | 0.001 | 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 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".