Parameterizing bubble‐mediated air‐sea gas exchange and its effect on ocean ventilation
Bibliographic record
Abstract
Bubbles play an important role in the exchange of gases between the atmosphere and ocean, altering both the rate of exchange and the equilibrium gas saturation state. We develop a parameterization of bubble‐mediated gas fluxes for use in Earth system models. The parameterization is derived from a mechanistic model of the oceanic boundary layer that simulates turbulent flows and the size spectrum of bubbles across a range of wind speeds and is compared against other published formulations. Bubble‐induced surface supersaturation increases rapidly with wind speed and is inversely related to temperature at a given wind speed, making the effect of bubbles greatest in regions that ventilate the deep ocean. The bubble‐induced supersaturation in high‐latitude surface waters compensates a substantial fraction of the undersaturation caused by surface cooling. Using a global ocean transport model, we show that this parameterization reproduces observed saturation rate profiles of the noble gas Argon in the deep Atlantic and Pacific Oceans. The abyssal argon supersaturation caused by bubbles varies according to gas solubility, ranging from ∼0.7% for soluble gases like CO2 to ∼1.7% for less soluble gases such as N2. Bubble‐induced supersaturation may be significant for biologically active gases such as oxygen.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".