The impacts of ocean physics on the efficiency of ocean alkalinity enhancement in a one-dimensional model
Bibliographic record
Abstract
We use a one-dimensional diffusion model to examine the relative effects of air-sea gas exchange and interior mixing on the efficiency of ocean alkalinity enhancements in drawing down atmospheric CO2 under a range of oceanic conditions. First, a series of highly idealized simulations are run to explore the impacts of deployment depth, wind speed, mixed layer depth, interior diffusivities and seasonality on the efficiency of CO2 uptake following an alkalinity addition. For additions made within the mixed layer subject to typical wind speeds and diffusivity profiles, we find efficiencies one year after deployment of around 50%, with wind speeds playing a dominant role in determining efficiency compared to mixed layer depth or interior diffusivities. Next, we use wind speeds, surface buoyancy and momentum fluxes from reanalysis to produce realistic, time varying diffusivities that we use to drive the model, producing estimates of efficiencies at different global locations over one annual cycle. Our simulations lend insight into the underlying processes that determine OAE efficiency and aid in the interpretation of similar calculations that have been performed using more complex models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".