Variations of Thermospheric Winds Observed by a Fabry–Perot Interferometer at Mohe, China
Bibliographic record
Abstract
Abstract A Fabry–Perot interferometer (FPI) system was deployed to observe the thermospheric winds at Mohe (53.5°N, 122.3°E), the northernmost observatory of space environment in the mainland of China, in July 2019. Thermospheric winds variations revealed from the 1 year FPI observations are as follows: (1) For the diurnal variation, southward meridional winds prevail at night and peak after midnight with amplitudes from 70 to 110 m/s; meridional winds are northward (∼40 m/s) at dusk and dawn in winter. For the zonal winds, eastward winds prevail only at dusk in summer, while it can sustain after midnight in winter. The maximum amplitudes of eastward winds are 50–130 m/s. Westward winds are strongest at dawn, with amplitudes of 75–120 m/s. (2) For the seasonal variation, both the meridional and zonal winds are dominated by annual oscillations. The semi‐annual oscillations can be observed at midnight. (3) The eastward (southward) winds become strong (weak) at midnight in January and December. An empirical model of thermospheric winds was established based on Mohe FPI observations and compared with HWM14. The variation trends of thermosphere winds described by HWM14 is basically consistent with the observations at Mohe. Moreover, Mohe FPI observations were compared with those by Kelan (38.7°N, 111.6°E) FPI. Variations of thermospheric winds showed some discrepancies between these two locations. The southward winds were significantly stronger at Mohe than at Kelan after midnight; and the semi‐annual and tri‐annual oscillations in the midnight zonal winds are observed at Mohe but not significant at Kelan.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".