Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic
Bibliographic record
Abstract
Abstract. Melt pond formation is a common feature of the spring and summer Arctic sea ice. However, the role of the melt ponds formation and the impact of the sea ice melt on both the direction and size of CO2 flux between air and sea is still unknown. Here we describe the CO2-carbonate chemistry of melting sea ice, melt ponds and the underlying seawater associated with measurement of CO2 fluxes across first year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase of the ice temperature and the subsequent decrease of the bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. Later on, melt pond formation affects both the bulk sea ice and the brine system. As melt ponds are formed from melted snow the in situ melt pond pCO2 is low (36 μatm). The percolation of this low pCO2 melt water into the sea ice matrix dilutes the brine resulting in a strong decrease of the in situ brine pCO2 (to 20 μatm). As melt ponds reach equilibrium with the atmosphere, their in situ pCO2 increase (up to 380 μatm) and the percolation of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".