Annual cycle of air‐sea CO<sub>2</sub> exchange in an Arctic Polynya Region
Bibliographic record
Abstract
During the Canadian International Polar Year projects in the Cape Bathurst polynya region, we measured a near–complete annual cycle of sea surface CO2 (pCO2sw), atmospheric CO2 (pCO2atm), sea surface temperature (SST), salinity (S), and wind speed (U). In this paper, we combine these data with ancillary measurements of sea ice concentration (Ci) to estimate the mean annual (September 2007–September 2008) air–sea CO2 exchange for the region. For the non–freezing seasons the exchange was calculated using a standard bulk aerodynamic approach, whereas during the freezing seasons we extrapolated eddy covariance measurements of CO2 exchange. Our results show that in 2007–08 the region served as a net sink of atmospheric CO2 at a mean rate of ‐10.1 ± 6.5 mmol m− 2 d− 1. The strongest calculated uptake rate occurred in the fall when wind velocities were highest, pCO2sw was significantly lower than pCO2atm, and ice was beginning to form. Atmospheric CO2 uptake was calculated to occur (at lower rates) throughout the rest of the year, except for a brief period of outgassing during late July. Using archival U, Ci, and pCO2sw data for the region, we found that winds in 2007–08 were 25–35 % stronger than the decadal mean and were predominately easterly, which appears to have induced a relatively late freeze–up (by ∼ 3 weeks relative to mean conditions) and an early polynya opening (by ∼ 4 weeks). In turn, these conditions may have given rise to a higher CO2 uptake than normal. Estimated winter CO2 exchange through leads and small polynya openings made up more than 50% of the total CO2 uptake, consistent with recent observations of enhanced CO2 exchange associated with open water components of the winter icescape. Our calculations for the Cape Bathurst polynya region are consistent with past studies that estimated the total winter CO2 uptake in Arctic coastal polynyas to be on the order of 1012 g C yr− 1.
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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 | 0.000 |
| 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 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".