Effects of diapycnal and isopycnal mixing on the ventilation of CFCs in the North Atlantic in an isopycnic coordinate OGCM
Bibliographic record
Abstract
Simulated distributions of the chlorofluorocarbons CFC-11 and CFC-12 are used to examine the ventilation of the North Atlantic Ocean in a global version of the Miami Isopycnic Coordinate Ocean Model (MICOM). Three simulations are performed: one with a diapycnal diffusivity K d= 3 x 10 -7/N m2 s -1 and an isopycnal diffusive velocity (i.e., diffusivity divided by the size of the grid cell) v trac= 0.01 m s -1 (Exp. 1); Exp. 2 is as Exp. 1 but with K d= 5 x 10 -8/N m2 s -1 plus increased bottom mixing; and Exp. 3 is as Exp. 2 but with v trac= 0.0025 m s -1. The main features of the simulated ventilation are strong uptake of the CFCs in the Labrador, Irminger and Nordic Seas, and a topographically aligned geostrophically controlled southward transport of CFC-enriched water in the Atlantic. It is found that the Overflow Waters (OW) from the Nordic Seas, the penetration of the western boundary currents, the ventilation of the subtropical surface waters, the vertical density stratification and the meridional overturning are all critically dependent on the applied isopycnal and diapycnal diffusivities, with Exp. 3 (Exp. 1) yielding the most (least) realistic results. Furthermore, it is the combined rather than the isolated effect of the isopycnal and diapycnal diffusivities that matter. For instance, the strength of the simulated Meridional Overturning Circulation (MOC) is similar in Exps. 1 and 3, but the simulated CFC-distributions are far too diffusive in Exp. 1 and fairly realistic in Exp. 3. It is demonstrated that the simulated distributions of transient tracers like the CFCs can be used to set the strength of the applied isopycnal mixing parameterization, a task that is difficult to conduct based on the simulated hydrography alone.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".