Efficient diffuse auroral electron scattering by electrostatic electron cyclotron harmonic waves in the outer magnetosphere: A detailed case study
Bibliographic record
Abstract
This paper is a companion to a paper by Liang et al. (2011) which reports a causal connection between the intensification of electrostatic ECH waves and the postmidnight diffuse auroral activity in the absence of whistler mode chorus waves at L = 11.5 on the basis of simultaneous observations from THEMIS spacecraft and NORSTAR optical instruments during 8–9 UT on February 5, 2009. In this paper, we use the THEMIS particle and wave measurements together with the magnetically conjugate auroral observations for this event to illustrate an example where electrostatic electron cyclotron harmonic (ECH) waves are the main contributor to the diffuse auroral precipitation. We use the wave and particle data to perform a comprehensive theoretical and numerical analysis of ECH wave driven resonant scattering rates. We find that the observed ECH wave activity can cause intense pitch angle scattering of plasma sheet electrons between 100 eV and 5 keV at a rate of >10 −4 s −1 for equatorial pitch angles α eq < 30°. The scattering approaches the strong diffusion limit in the realistic ambient magnetic field to produce efficient precipitation loss of <∼5 keV electrons on a timescale of a few hours or less. Using the electron differential energy flux inside the loss cone estimated based upon the energy‐dependent efficiency of ECH wave scattering for an 8‐s interval with high resolution wave data available, the auroral electron transport model developed by Lummerzheim (1987) produced an intensity of ∼2.3 kR for the green‐line diffuse aurora. Separately, Maxwellian fitting to the electron differential flux spectrum produced a green‐line auroral intensity of ∼2.6 kR. This is in good agreement with the ∼2.4 kR green‐line auroral intensity observed simultaneously at the magnetic foot point (as inferred using the event‐adaptive model of Kubyshkina et al. (2009, 2011)) of the location where the in situ observations were obtained. Our results support the scenario that enhanced ECH emissions in the central plasma sheet (CPS) can be an important or even dominant driver of diffuse auroral precipitation in the outer magnetosphere. This paper is an important compliment to recent work that has shown lower band and upper band chorus to be mainly responsible for the occurrences of diffuse aurora in the inner magnetosphere.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".