Argon supersaturation indicates low decadal‐scale vertical mixing in the ocean thermocline
Bibliographic record
Abstract
The rate of vertical mixing in the ocean's stratified waters limits the uptake of anthropogenic CO2, influences the strength of the overturning circulation, and regulates the transport of nutrients to the lighted surface waters, controlling global biological production. Despite this fundamental importance, there is a long‐standing conundrum in oceanography that experimentally‐measured rates of turbulent mixing across density surfaces (diapycnal mixing) in the main thermocline cannot support sufficient nutrient fluxes from below to explain rates of biological production measured in the subtropical euphotic zone. Possible solutions to this problem are transport mechanisms that occur intermittently on short time and space scales that would be difficult to observe in tracer‐ release experiments and are not resolved in large‐scale ocean models. We tested this hypothesis by measuring highly‐accurate argon profiles from the subtropical thermocline in the North Pacific Ocean. It has been shown theoretically that the change in argon supersaturation along density surfaces is a measure of diapycnal mixing averaged over the decadal time‐scale of thermocline ventilation. Two different model interpretations of our data indicate that the mean rate of diapycnal mixing on density surfaces betweenσθ = 26.4 – 26.7 (depths 150–600 m) is no more than 0.2 × 10−4 m2 s−1. This supports low diapycnal mixing rates even on decadal time‐scales and rules out enhancement of diapycnal mixing on this density interval by intermittent mixing or mixing at boundaries that propagates into the ocean interior.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".