Equinoctial Asymmetry in the Upper Ionosphere: Comparison of Satellite Observations and Models
Bibliographic record
Abstract
Abstract The terrestrial ionosphere displays significant equinoctial asymmetry despite the upper atmosphere receiving similar levels of solar ionization energy at a given location and local time in March and September during similar solar activity conditions. This intriguing feature is not well understood or modeled, particularly in the upper ionosphere, and causes of the asymmetry are not fully established and quantified. Yet, their study is important to provide better insights into the atmosphere‐ionosphere coupling processes. Analysis of Langmuir probe data from ESA's Swarm B satellite at ∼525 km altitude reveals that the daytime electron density is larger for all latitudes during the March equinox than during the September equinox, while the electron temperature shows an inverted asymmetry except at low latitudes. Simultaneously obtained neutral density data from Swarm GPS accelerations indicate that the thermosphere is denser during the March equinox. The asymmetry seen by Swarm electron density observations is also present in electron densities obtained using GPS radio occultation measurements from the COSMIC satellites. Simulations were performed using physics‐based ionosphere models (SAMI3, WACCM‐X, and TIE‐GCM) to determine their ability to produce the observed asymmetry, understand the generation mechanism(s), and establish the relative role of physical drivers. Results produced by TIE‐GCM are closest to the observations when seasonally varying eddy diffusivity is considered in the model. The asymmetry produced by other models is noticeably weaker. Modeling of the asymmetry by SAMI3 driven with the TIE‐GCM neutral atmosphere shows that both neutral density and winds play a critical role, but the density has a greater effect.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".