Study of the tidal variations in mesospheric temperature at low and mid latitudes from WINDII and potassium lidar observations
Bibliographic record
Abstract
Abstract. Zonal mean daytime temperatures from the Wind Imaging Interferometer (WINDII) on the Upper Atmosphere Research Satellite (UARS) and nightly temperatures from a potassium (K) lidar are employed in the study of the tidal variations in mesospheric temperature at low and mid latitudes in the Northern Hemisphere. The analysis is applied to observations at 89km height for winter solstice, December to February (DJF), at 55° N, and for May and November at 28° N. The WINDII results are based on observations from 1991 to 1997. The K-lidar observations for DJF at Kühlungsborn (54° N) were from 1996–1999, while those for May and November at Tenerife 28° N were from 1999. To avoid possible effects from year-to-year variability in the temperatures observed, as well as differences due to instrument calibration and observation periods, the mean temperature field is removed from the respective data sets, assuming that only tidal and planetary scale perturbations remain in the temperature residuals. The latter are then binned in 0.5h periods and the individual data sets are fitted in a least-mean square sense to 12-h and 8-h harmonics, to infer semidiurnal and terdiurnal tidal parameters. Both the K-lidar and WINDII independently observed a strong semidiurnal tide in November, with amplitudes of 13K and 7.4K, respectively. Good agreement was also found in the tidal parameters derived from the two data sets for DJF and May. It was recognized that insufficient local time coverage of the two separate data sets could lead to an overestimation of the semidiurnal tidal amplitude. A combined ground-based/satellite data set with full diurnal local time coverage was created which was fitted to 24h+12h+8h harmonics and a novel method applied to account for possible differences between the daytime and nighttime means. The results still yielded a strong semidiurnal tide in November at 28° N with an amplitude of 8.8K which is twice the SD amplitude in May and DJF. The diurnal tidal parameters were practically the same at 28° N and 55° N, in November and DJF, respectively, with an amplitude of 6.5K and peaking at ~9h. The diurnal and semidiurnal amplitudes in May were about the same, 4K, and 4.6K, while the terdiurnal tide had the same amplitudes and phases in May and November at 28° N. Good agreement is found with other experimental data while models tend to underestimate the amplitudes. Key words. Atmospheric composition and structure (pressure, density and temperature) – Meteorology and atmospheric dynamics (middle atmosphere dynamics; waves and tides)
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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) | 0.000 | 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 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".