Compensation between Resolved Wave Driving and Parameterized Orographic Gravity Wave Driving of the Brewer–Dobson Circulation and Its Response to Climate Change
Bibliographic record
Abstract
Abstract Following recent findings, the interaction between resolved (Rossby) wave drag and parameterized orographic gravity wave drag (OGWD) is investigated, in terms of their driving of the Brewer–Dobson circulation (BDC), in a comprehensive climate model. To this end, the parameter that effectively determines the strength of OGWD in present-day and doubled CO 2 simulations is varied. The authors focus on the Northern Hemisphere during winter when the largest response of the BDC to climate change is predicted to occur. It is found that increases in OGWD are to a remarkable degree compensated by a reduction in midlatitude resolved wave drag, thereby reducing the impact of changes in OGWD on the BDC. This compensation is also found for the response to climate change: changes in the OGWD contribution to the BDC response to climate change are compensated by opposite changes in the resolved wave drag contribution to the BDC response to climate change, thereby reducing the impact of changes in OGWD on the BDC response to climate change. By contrast, compensation does not occur at northern high latitudes, where resolved wave driving and the associated downwelling increase with increasing OGWD, both for the present-day climate and the response to climate change. These findings raise confidence in the credibility of climate model projections of the strengthened BDC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".