Sea‐air CO<sub>2</sub> exchange in the western Arctic coastal ocean
Bibliographic record
Abstract
Abstract The biogeochemical seascape of the western Arctic coastal ocean is in rapid transition. Changes in sea ice cover will be accompanied by alterations in sea‐air carbon dioxide (CO 2 ) exchange, of which the latter has been difficult to constrain owing to sparse temporal and spatial data sets. Previous assessments of sea‐air CO 2 flux have targeted specific subregional areas of the western Arctic coastal ocean. Here a holistic approach is taken to determine the net sea‐air CO 2 flux over this broad region. We compiled and analyzed an extensive data set of nearly 600,000 surface seawater CO 2 partial pressure ( p CO 2 ) measurements spanning 2003 through 2014. Using space‐time colocated, reconstructed atmospheric p CO 2 values coupled with the seawater p CO 2 data set, monthly climatologies of sea‐air p CO 2 differences (Δ p CO 2 ) were created on a 0.2° latitude × 0.5° longitude grid. Sea‐air CO 2 fluxes were computed using the Δ p CO 2 grid and gas transfer rates calculated from climatology of wind speed second moments. Fluxes were calculated with and without the presence of sea ice, treating sea ice as an imperfect barrier to gas exchange. This allowed for carbon uptake by the western Arctic coastal ocean to be assessed under existing and reduced sea ice cover conditions, in which carbon uptake increased 30% over the current 10.9 ± 5.7 Tg C (1 Tg = 10 12 g) yr −1 of sea ice‐adjusted exchange in the region. This assessment extends beyond previous subregional estimates in the region in an all‐inclusive manner and points to key unresolved aspects that must be targeted by future research.
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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 | 0.000 | 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) | 0.000 | 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".