The impact of atmospheric <i>p</i>CO<sub><b>2</b></sub> on carbon isotope ratios of the atmosphere and ocean
Bibliographic record
Abstract
Abstract It is well known that the equilibration timescale for the isotopic ratios 13C/12C and 14C/12C in the ocean mixed layer is on the order of a decade, 2 orders of magnitude slower than for oxygen. Less widely appreciated is the fact that the equilibration timescale is quite sensitive to the speciation of dissolved inorganic carbon (DIC) in the mixed layer, scaling linearly with the ratio DIC/CO2, which varies inversely with atmospheric pCO2. Although this effect is included in models that resolve the role of carbon speciation in air‐sea exchange, its role is often unrecognized, and it is not commonly considered in the interpretation of carbon isotope observations. Here we use a global three‐dimensional ocean model to estimate the redistribution of the carbon isotopic ratios between the atmosphere and ocean due solely to variations in atmospheric pCO2. Under Last Glacial Maximum (LGM) pCO2, atmospheric Δ14C is increased by ≈30‰ due to the speciation change, all else being equal, raising the surface reservoir age by about 250 years throughout most of the ocean. For 13C, enhanced surface disequilibrium under LGM pCO2 causes the upper ocean, atmosphere, and North Atlantic Deep Water δ13C to become at least 0.2‰ higher relative to deep waters ventilated by the Southern Ocean. Conversely, under high pCO2, rapid equilibration greatly decreases isotopic disequilibrium. As a result, during geological periods of high pCO2, vertical δ13C gradients may have been greatly weakened as a direct chemical consequence of the high pCO2, masquerading as very well ventilated or biologically dead Strangelove Oceans. The ongoing anthropogenic rise of pCO2 is accelerating the equilibration of the carbon isotopes in the ocean, lowering atmospheric Δ14C and weakening δ13C gradients within the ocean to a degree that is similar to the traditional fossil fuel “Suess” effect.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".