Current estimates of K <sub>1</sub> * and K <sub>2</sub> * appear inconsistent with measured CO <sub>2</sub> system parameters in cold oceanic regions
Bibliographic record
Abstract
Abstract. Seawater absorption of anthropogenic atmospheric carbon dioxide (CO2) has led to a range of changes in carbonate chemistry, collectively referred to as ocean acidification. Stoichiometric dissociation constants used to convert measured carbonate system variables (pH, pCO2, dissolved inorganic carbon, total alkalinity) into globally comparable parameters are crucial for accurately quantifying these changes. The temperature and salinity coefficients of these constants have generally been experimentally derived under controlled laboratory conditions. Here, we use field measurements of carbonate system variables taken from the Global Ocean Data Analysis Project version 2 and the Surface Ocean CO2 Atlas data products to evaluate the temperature dependence of the carbonic acid stoichiometric dissociation constants. By applying a novel iterative procedure to a large dataset of 948 surface-water, quality-controlled samples where four carbonate system variables were independently measured, we show that the set of equations published by Lueker et al. (2000), currently preferred by the ocean acidification community, overestimates the stoichiometric dissociation constants at temperatures below about 8 ∘C. We apply these newly derived temperature coefficients to high-latitude Argo float and cruise data to quantify the effects on surface-water pCO2 and calcite saturation states. These findings highlight the critical implications of uncertainty in stoichiometric dissociation constants for future projections of ocean acidification in polar regions and the need to improve knowledge of what causes the CO2 system inconsistencies in cold waters.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".