Subduction and Transport in the Indian and Pacific Oceans in a 2 × CO2 Climate
Bibliographic record
Abstract
Abstract Subduction, water mass transformation, and transport rates in the Indo-Pacific Ocean are diagnosed in a recent version of the Canadian Centre for Climate Modelling and Analysis coupled model. It is found that the subduction across the base of the winter mixed layer is dominated by the lateral transfer, particularly within the relatively dense water classes corresponding to the densest mode and intermediate waters. However, within lighter densities, including those characterizing the lighter varieties of mode waters, the vertical transfer has a strong positive input to the net subduction. The upper-ocean volume transports across 30°N and 32°S are largest within the density classes that correspond to mode waters. In the North Pacific, the buoyancy flux converts the near-surface waters mostly to denser water classes, whereas in the Southern Ocean the surface waters are transformed both to lighter and denser water classes, depending on the density. In response to a doubling of CO2, the subduction, transformation, and transport of mode waters in both hemispheres shift to lighter densities but do not change significantly, whereas the subduction of intermediate waters decreases. The area of large winter mixed layer depths decreases, particularly in the Southern Hemisphere. In the low latitudes, the thermocline water flux that enters the tropical Pacific via the western boundary flows generally increases. However, its anomaly has a complex structure, so that integrated estimates can be sensitive to the isopycnal ranges. The upper part of the Equatorial Undercurrent (EUC) strengthens in the warmer climate, whereas its lower part weakens. The anomaly in the EUC closely follows the anomaly in stratification along the equator. The Indonesian Throughflow transport decreases with part of it being redirected eastward. This part joins with the intensified equatorward thermocline flows at the western boundaries and contributes to the EUC anomaly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".