Idealized Models of Slantwise Convection in a Baroclinic Flow
Bibliographic record
Abstract
Intermediate, or deep, convection in a baroclinic flow occurs along slanted paths parallel to the alongflow absolute momentum surfaces. These surfaces are principally tilted due to the vertical shear in velocity but can be further modified by a nonvertical axis of rotation. An inviscid Lagrangian parcel model, using realistic parameters, is utilized to illustrate, qualitatively, the different scenarios resulting from the combined action of inertial and gravitational forces acting on sinking parcels of dense fluid. More quantitative results are derived from a series of numerical experiments using a zonally invariant, high-resolution, nonhydrostatic model. Convection occuring in a flow with tilted absolute momentum surfaces will mix properties along these slanted surfaces. This implies that the fluid can retain a weak vertical stratification while overturning and also, more importantly, that the evolution of the convective layer cannot be described in terms of one-dimensional, vertical mixing. The authors show, for conditions typical of the Labrador Sea, that the convective layer depth difference between that estimated by mixing vertically and one obtained allowing for slantwise mixing can be greater than 100 m; slantwise convection reaches deeper because of the reduced stratification along the slanted paths. An alternative slantwise mixing scheme, based on the assumption of zero potential vorticity of the convected fluid, is proposed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".