Thermospheric density structures over the polar regions observed with CHAMP
Bibliographic record
Abstract
Abstract. We report on the unexpected detection of considerable structure in high latitude thermospheric densities, as derived from an accelerometer onboard the CHAMP satellite. The width of the structures, which can either be maxima or minima, varies between a few hundred km and 2000 km. The amplitudes of these density extrema can reach 50% of ambient. Maxima cluster around 75° (N and S), while minima are found closer to the poles. In a magnetic latitude-magnetic local time frame the maxima are found mainly around the cusp region. Overall, the observed structures somewhat resemble so-called density cells previously found in model calculations. However the models generate their cells around 140–300 km altitude and show little, if any remnant at 400 km or above. This has to be contrasted with the fact that the CHAMP observations were obtained near 430 km altitude. We have explored Joule heating as a possible mechanism for the generation of the structures, at least in density enhancement regions, using Hall currents measured on CHAMP and simultaneous incoherent scatter measurements with EISCAT. However, the electric fields were usually quite small during the period of observation, making the quest for an explanation for the structures all the more challenging. Keywords. Meteorology and atmospheric dynamics (Thermospheric dynamics) – Magnetospheric physics (Polar cap phenomena) – Atmospheric composition and structure (Pressure, density, and temperature)
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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 | 0.000 |
| 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) | 0.001 | 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".