Short term tidal variability in stratosphere using ERA-interim and CMAM temperature data and comparison with satellite retrievals
Bibliographic record
Abstract
A short term variability of migrating and non migrating tide is investigated in the stratosphere from the regular Canadian Middle Atmosphere Model (CMAM) and reanalysis ERA-interim temperature and wind dataset during winter of 2006 to 2010. Short term variability of tides is examined by ±10 day’s window size from Earth’s surface to 1hPa pressure level. To examine the short term variability of migrating and non migrating tide in stratosphere, we applied the fast fourier transform method to the CMAM30 and ERA-interim observation. The results reveal that tide changes with amplitude of 1-2K regularly on short timescales (21days) in stratosphere. Similar variability occurs in ERA-interim reanalysis observation. Non-migrating tide DS0 shows strong winter features with finer variation during 2009 and 2010 at 65°N. The short term variability of DE3 tide in stratosphere during 2008 and 2010 may be driven by zonal mean wind and non linear interaction with planetary wave. Amplitude of DW1 shows day to day variabilities clearly during winter of 2006, 2008 and 2009 at 0.7hPa over the equator and mid-latitude while the peak of DW1 is absent at 1hPa and 10hPa from CMAM temperature data set. Short term tidal variability in the stratosphere is not related to a single source. It depends on ozone density, zonal mean wind, and wave-wave non linear interactions. By using smaller window size, short term variabilities and finer variation of non migrating tides and SPW1 are understood. These results will be compared to results from satellite temperature data set, particularly FORMOSAT-3/COMSIC, for investigating short term tidal variability in the stratosphere.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".