New pathways for EMIC wave propagation within the ionosphere: SWARM observations and modelling
Bibliographic record
Abstract
Electromagnetic ion cyclotron (EMIC) waves are important because of their essential role in reducing the amount of radiation in the Earth's radiation belts under geomagnetic storm conditions. In this presentation, we show results from a new simulation model of EMIC waves and compare them with SWARM satellite data and ground-based observations [I. P. Pakhotin et al., Geophys. Res. Lett., 2022, doi:10.1029/2022GL098249]. The EMIC wave model is a first-of-a-kind in accounting for wave propagation in the magnetosphere and a realistic ionosphere specified using the IRI and MSIS empirical models. The inclusion of a realistic ionosphere in the model enables new pathways to the upper atmosphere to be identified, which is crucial for understanding the waves detected on the ground. We show using a model-data comparison that EMIC wave energy is reflected at different locations in the ionosphere toward the equator to form standing waves. This is a new resonance phenomenoncreated by interference of waves that produces an amplitude peak in the upper atmosphere at lower latitudes, far from the location of the initial source. Understanding such pathways is crucial for correctly diagnosing the location of EMIC wave populations in space, and assessing their role in radiation belt loss.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".