The impact of surface flux anomalies on the mid-high latitude Atlantic Ocean Circulation in HADCM3. RAPID Project – The Role of Air-Sea Forcing in Causing Rapid \nChanges in the North Atlantic Thermohaline Circulation \nReport No. 1
Bibliographic record
Abstract
forcing in the Hadley Centre coupled ocean-atmosphere model (HadCM3) are reported; the study forms part of a Natural Environment Research Council (NERC) Rapid programme project. An analysis of 100 years of the HadCM3 control run indicates that deep convection occurs in the Greenland Sea, the Irminger Basin and the Labrador Sea. However, a composite analysis of mixed layer depth only reveals a clear connection between deep convection and air-sea flux anomalies in the Greenland Sea, and we have focused on this region in our subsequent analysis. Evaluation of the different components of the density flux in the Greenland Sea shows that the net heat flux is a more important influence on surface density than both net evaporation and ice melt. A composite analysis of the ocean circulation was carried out for years with anomalously strong and weak heat loss over the Greenland Sea. Years of strong heat loss are associated with increased Greenland Sea convection and a rapid increase in the southward flow through the Denmark Strait by about 30%. Evidence of more widespread changes in the circulation at mid-high latitudes was also found but we have not yet established whether they are directly linked to the anomalous Greenland Sea forcing.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 0.001 |
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".