Multiscale equatorial electrojet turbulence:Baseline 2‐D model
Bibliographic record
Abstract
Abstract The spatial and spectral characteristics of the turbulent plasma density, electric fields, and ion drift in ionospheric E region are studied using a new set of nonlinear plasma fluid equations. The fluid model combines both Farley‐Buneman (Type‐I) and Gradient‐Drift (Type‐II) plasma instabilities in the equatorial electrojet. In our unified model of the plasma instabilities, we include the ion viscosity in the ion momentum equation and electron inertia in the electron momentum equation. These two terms play an important role in stabilizing the growing modes in the linear regime and in driving the Farley‐Buneman instability into the saturation state. The simulation results show good agreements with a number of features of rocket and radar observations, such as (1) saturation of plasma density perturbations depends on the solar condition and reaches 7–15% relative to the background, (2) fluctuation of the horizontal secondary electric field reaches 8–15 mV/m, (3) stabilization of the phase velocity of the perturbed density wave around the value of the ion‐acoustic speed inside the electrojet, (4) “up‐down” asymmetry in the vertical fluxes of the plasma density, (5) “east‐west” asymmetry of the plasma zonal drifts, and (6) generation of small scale of the order of meter scale lengths irregularities embedded in large‐scale structures. Spectral analysis of the density fluctuations reveals the energy cascade due to the nonlinear coupling between structures of different scales. The break‐up of the large‐scale structures into small‐scale structures explains the disappearance of Type‐II echoes in the presence of Type‐I instabilities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".