Study of Spatiotemporal Development of Global Distribution of Magnetospheric ELF/VLF Waves Using Ground‐Based and Satellite Observations, and RAM‐SCB Simulations, for the March and November 2017 Storms
Bibliographic record
Abstract
Abstract Magnetospheric Extremely Low‐Frequency/Very Low‐Frequency (ELF/VLF) waves have an important role in the acceleration and loss of energetic electrons in the magnetosphere through wave‐particle interaction. It is necessary to understand the spatiotemporal development of magnetospheric ELF/VLF waves to quantitatively estimate this effect of wave‐particle interaction, a global process not yet well understood. We investigated spatiotemporal development of magnetospheric ELF/VLF waves using 6 PWING ground‐based stations at subauroral latitudes, Exploration of energization and Radiation in Geospace and RBSP satellites, POES/MetOp satellites, and the RAM‐SCB model, focusing on the March and November 2017 storms driven by corotating interaction regions in the solar wind. Our results show that the ELF/VLF waves are enhanced over a longitudinal extent from midnight to morning and dayside associated with substorm electron injections. In the main to early storm recovery phase, we observe continuous ELF/VLF waves from ∼0 to ∼12 MLT in the dawn sector. This wide extent seems to be caused by frequent occurrence of substorms. The wave region expands eastward in association with the drift of source electrons injected by substorms from the nightside. We also observed dayside ELF/VLF wave enhancement, possibly driven by magnetospheric compression by solar wind, over an MLT extent of at least 5 h. Ground observations tend not to observe ELF/VLF waves in the post‐midnight sector, although other methods clearly show the existence of waves. This is possibly due to Landau damping of the waves, the absence of the plasma density duct structure, and/or enhanced auroral ionization of the ionosphere in the post‐midnight sector.
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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".