Electrodynamics of magnetosphere‐ionosphere coupling and feedback on magnetospheric field line resonances
Bibliographic record
Abstract
We present a new dynamic model that describes coupling between standing inertial or ion‐acoustic‐gyroradius‐scale shear Alfvén waves, compressional modes, and auroral density disturbances. The model is applied to the excitation of field line resonances (FLRs) in dipolar and stretched geomagnetic fields in Earth's magnetosphere. Magnetosphere‐ionosphere coupling is included by accounting for the closure of magnetospheric field‐aligned currents (FACs) through Pedersen currents in the ionosphere. A second new aspect is that the height‐integrated Pedersen conductivity is treated as a dynamic parameter by electrodynamically coupling the two‐dimensional finite element wave model “Topo” to the ionospheric ionization model “Global Airglow Model (GLOW).” We demonstrate that field line stretching brings the equatorial plasma β above unity, where the reduced MHD formulism for low‐frequency plasma breaks down. As an application of our model, we study a specific FLR event observed on 31 January 1997, when the NASA FAST satellite was over the Canadian Auroral Network for the OPEN Program Unified Study (CANOPUS) Gillam station. Using geomagnetic fields computed from the T96 magnetic field model, we show that auroral electron precipitation produces strong Pedersen conductivity enhancements that control the final amplitude and width of the excited FLR, along with the amplitude of associated density fluctuations. The predictions of the model are generally consistent with observations of this event.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".