Comparing interhemispheric differences of mesosphere/lower thermosphere dynamics from ground-based observations and three general circulation models
Bibliographic record
Abstract
Meteor radars have been proven to be valuable assets in investigating and monitoring mesosphere/lower thermosphere winds for the last two decades. In this study we present a comparison of almost continuous meteor radar measurements obtained from six meteor radars located at mid- and polar conjugate latitudes in both hemispheres. For this purpose we havecompiled harmonized data sets for the Sodankylä (67.9°N, 21.1°E), Esrange (67.4°N, 26.6°E), Davis (68.6°S, 78.0°E), Collm (51.3°N, 13.0°E), Tierra del Fuego meteor radar (53.7°S, 67.7°W) and the Canadian Meteor Orbit Radar (CMOR) (43.3°N, 80.8°W). The analysis revealed characteristic differences between the northern and southern hemisphere in the mean winds, in the strength of the mesospheric jets as well as in the tidal climatologies. In particular, semidiurnal tides show significant and distinct interhemispheric differences, notably a strong seasonal asymmetry in amplitude and phase, most prominent during the hemispheric fall transition from September to November. We also compared the observational climatologies with predictions from the three general circulation models GAIA, WACCM-X(SD) and ICON-UA. The model data were analyzed by simulating the radar in the model domain and applying an identical diagnostic to extract mean winds, tides and gravity wave activity. Our comparison reveals substantial differences between model and observational mean winds and tides that vary seasonally, by model and hemisphere. GAIA indicates similar winds during the hemispheric winter conditions compared to the observations, whereas WACCM-X(SD) showed a better agreement to the observations for the summer zonal wind reversal. The models are only partially able to capture interhemispheric differences, with the free-running ICON-UA model best reproducing the interhemispheric difference of the semidiurnal tide in reasonable agreement to observations.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".