Analysis of the slope of isentropic surfaces and its tendencies over the North Atlantic
Bibliographic record
Abstract
The maintenance of baroclinicity along mid‐ and high‐latitude storm tracks is a matter of ongoing debate. Using an isentropic framework, a novel diagnostic based on the tendency equation for the slope of isentropic surfaces – a measure of the potential for baroclinic development – is presented. The tendency comprises contributions from dynamic processes, latent heat release, radiation and subgrid‐scale turbulence, which incorporates the effect of sensible heat fluxes. A climatology of these tendencies over the North Atlantic is compiled for the winters of 2009 and 2010. It is found that adiabatic tilting flattens the isentropic surfaces, reflecting the action of growing baroclinic cyclones. This tendency is balanced climatologically by the generation of slope by diabatic processes. In the lower troposphere, the most intense diabatic increase of slope is found along the oceanic frontal zone associated with the Gulf Stream and at higher latitudes in the Labrador Sea, the Nordic Seas and the Barents Sea. Latent heat release and sensible heat fluxes both contribute substantially in these regions. A quantitative analysis of cold‐air outbreaks emphasizes their important role in restoring the slope in the lower troposphere over the Gulf Stream region and off the sea‐ice edge at high latitudes. In the upper troposphere, latent heat release due to cloud microphysical processes is the dominant mechanism maintaining the slope.
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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 | 0.000 |
| 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 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".