Simulation of CFCs in the North Atlantic Ocean using an adiabatically corrected ocean circulation model
Bibliographic record
Abstract
A three‐dimensional ocean circulation model is used to examine the uptake, spreading and interannual variability of chlorofluorocarbons (CFCs) in the North Atlantic Ocean during the 50‐year period from 1948 to 1997. The model is forced by climatological and North Atlantic Oscillation (NAO) related monthly mean surface forcing, and a realistic, time‐varying air‐sea flux of CFCs. Different from previous studies, the model uses the modified semiprognostic method to correct for systematic bias, leading to improvements in the modeled ocean circulation near the western boundary. Comparisons are made between simulated concentrations and observations made along three World Ocean Circulation Experiment transects, and between the simulated inventory of CFCs in the Labrador Sea and estimates based on observations. The model reproduces the general structure of the observed concentrations, including the concentration maxima associated with Labrador Sea Water (LSW) near the western boundary, although quantitative comparisons indicate that the model CFC concentrations associated with LSW are generally too high. The equatorward spreading rate of LSW is estimated from CFC effective age and found to be about 1.3 cm s−1, in agreement with observational estimates. We also discuss the close relationship between the NAO and interannual variability in the uptake and inventory of CFCs in the Labrador Sea, and the spreading of CFCs along the western boundary.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".