Interhemispheric comparison of mesosphere/lower thermosphere winds from GAIA, WACCM-X and ICON-UA simulations and meteor radar observations at mid- and polar latitudes
Bibliographic record
Abstract
There is a growing scientific interest to investigate the forcing from the middle atmosphere dynamics on the thermosphere and ionosphere. This forcing is driven by atmospheric waves at various temporal and spatial scales. In this study, we cross-compare the nudged models Ground-to-topside model of Atmosphere and Ionosphere for Aeronomy (GAIA) and Whole Atmosphere Community Climate Model Extended Version (Specified dynamics) ( WACCM-X(SD)), a free-running version of Upper Atmosphere ICOsahedral Non-hydrostatic (ICON-UA) with six meteor radars located at conjugate polar and mid-latitudes. Mean winds, diurnal and semidiurnal tidal amplitudes and phases were obtained from the radar observations at the mesosphere and lower thermosphere (MLT) and compared to the GAIA, WACCM-X(SD), and ICON-UA data for similar locations applying a harmonized diagnostic. Our results indicate that GAIA zonal and meridional winds show a good agreement to the meteor radars during the winter season on both hemispheres, whereas WACCM-X(SD) and ICON-UA seem to reproduce better the summer zonal wind reversal. However, the mean winds also exhibit some deviation in the seasonal characteristic concerning the meteor radar measurements, which are attributed to the gravity wave parameterizations implemented in the models. All three models tend to reflect the seasonality of diurnal tidal amplitudes, but show some dissimilarities in tidal phases. We also found systematic interhemispheric differences in the seasonal characteristic of semidiurnal amplitudes and phases. The free-running ICON-UA apparently shows most of these interhemispheric differences, whereas WACCM-X(SD) and GAIA trend to have better agreement of the semidiurnal tidal variability in the northern hemisphere.
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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 | 0.000 |
| 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".