A comparison of northern hemisphere winds using SuperDARN meteor trail and MF radar wind measurements
Bibliographic record
Abstract
The main purpose of the Super Dual Auroral Radar Network (Super‐DARN) is to use paired radars to deduce the F ‐region convection from Doppler measurements of backscatter seen at large ranges, typically beyond ∼900 km. Nearer to each HF radar, the nearest ranges at ∼165–400 km are dominated by meteor trail echoes. Once formed, the motion of these meteor trails is normally controlled by neutral winds in the 80–110 km altitude range. By combining the line‐of‐sight velocities from all 16 receiver beams (∼52° in azimuth) of a given SuperDARN radar, it is possible to determine the full horizontal wind vector field over the meteor trail height range. Elevation angles are also measured using an interferometer mode and as such height information can, in principle, be obtained from the combined range and elevation angle data. A comparison with neutral wind measurements from a colocated (Saskatoon, Canada) MF wind radar indicates good agreement between the two radar systems at heights of ∼95 km. Based on these detailed comparisons, a simple common method for determining two‐dimensional winds for all SuperDARN radars, which have extensive longitudinal coverage, was developed. Comparisons with other systems used for dynamical studies of tides and planetary waves are desirable and prove to be essential to obtain a good SuperDARN neutral wind motion analysis. The MF radars at Saskatoon and Tromsø, Norway, are located near the western and eastern ends of the Northern Hemisphere network of six SuperDARN radars. Comparisons between the two types of radars for two seasonal intervals (September and December) show that the SuperDARN radars provide good longitudinal coverage of tides in support of the more detailed MF radar data. The two systems complement each other effectively.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".