Three‐Dimensional Fourier Analysis of the Phase Velocity Distributions of Mesospheric and Ionospheric Waves Based on Airglow Images Collected Over 10 Years: Comparison of Magadan, Russia, and Athabasca, Canada
Bibliographic record
Abstract
Abstract We studied atmospheric gravity waves (AGWs) and nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) using a three‐dimensional spectral analysis technique for airglow images at wavelengths of 557.7 nm (altitude: 90–100 km for AGWs) and 630.0 nm (200–300 km for MSTIDs), obtained from Athabasca (ATH), Canada (55°N, 247°E, 2005–2017), and Magadan (MGD), Russia (60°N, 151°E, 2008–2017), over 10–13 years. The AGW propagation direction in summer was from northward to northeastward in ATH and northeastward in MGD with phase speeds of 20–60 m/s. In winter at ATH, they are more omnidirectional with weak preference from northward to southwestward with a speed less than 40 m/s, while another weaker power exists from northeastward to southeastward from 70 to 120 m/s. In winter at MGD, there was no dominant direction in the phase‐velocity spectra with spectral power an order smaller than ATH. We suggest that these AGW characteristics were caused by wind filtering and intensity and locations of tropospheric sources. The MSTIDs at ATH propagated westward in spring and winter and eastward in summer and fall. The MSTIDs at MGD propagated northeastward, eastward, and westward in spring, fall, and winter, respectively, with weaker power than that at ATH. The phase speeds are mostly less than 50 m/s except for fall. The propagation direction tends to change from southwest‐westward in the evening to northeast‐eastward after the midnight at ATH and from south‐southwestward in the evening to north‐northeastward after the midnight at MGD. We discuss possible reasons for these MSTID characteristics at high latitudes based on Perkins and E‐F coupling instabilities, high‐latitude plasma convection, and thermospheric neutral winds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 teacher head, 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".