A model study of the interannual to decadal scale variability in the North Atlantic Ocean
Bibliographic record
Abstract
A forced experiment with the global version ORCA2LIM of the LODYC ocean-ice model has been carried out to simulate regional to basin scale variability in the ocean currents and the thermodynamic fields for the period 1948 to 1998. This study is part of the PREDICATE Work Package 2 (WP2) project, which purpose is to determine mechanisms of decadal fluctuations in the North Atlantic ocean. The realistic forcing fields are derived from the NCEP reanalysis using an iterative scheme (derived from the TOGA COARE scheme) for the bulk formula calculation. The thermohaline circulation (following the maximum of the meridional stream function above 20N) presents a strong jump (~5 Sv) in the early 70s, in accordance with an enhancement of the North Atlantic Oscillation some years earlier. The relationship between the THC and the atmospheric forcing (heat fluxes, wind stresses) is done through statistical methods (EOF-based methods, regression methods), in order to understand the respective roles of the atmospheric fields versus oceanic ones, like the salinity, the ice formation/dilution, and the convection. Strong variations in the thermohaline circulation are related to the mechanisms of deep-water formation in the Labrador Sea, region where the increasing salinity leads to the sinking of cold waters, the enhancement of the convection and of the thermohaline circulation. The understanding of the variability of these atmospheric and oceanic fields helps us to set up the characteristics of the simulated variability modes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".