10.1016/0967-0653(93)94631-8
Bibliographic record
Abstract
The impact of gravity wave drag (GWD) on the COLA (Center for Ocean-Land-Atmosphere Interactions) –GCM is studied by simulating two pairs of 30-day extended range forecasts. One is initialized on January 8, 1990, and the other on July 15, 1989. With each initial condition forecasts were made both with and without the GWD effects. The results show that GWD effects improve the forecast for both January and July particularly in the winter hemisphere. The GWD reduces the westerly bias in the zonal wind and the cold bias in the temperature. As a consequence of the changes in the momentum and temperature there are changes in the meridional mass transport such that monthly mean sea level pressures are improved particularly in the polar regions. Furthermore, as the westerly bias in the zonal momentum is reduced the momentum of the large scale flow is brought down to the Earth's surface where it is dissipated. This dissipation process increases the effective surface drag and enhances the mean meridional circulations. The results indicate that the mean meridional circulations are enhanced by 15 and the divergent kinetic energy is enhanced by 30% after day-15. Associated with the enhanced secondary circulations is increased zonally averaged precipitation in the summer hemisphere and decreased zonally averaged precipitation in the winter hemisphere in July. In January the precipitation increases in both hemispheres.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.989 | 0.991 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".