Calcium carbonate saturation in the surface water of the Arctic Ocean: undersaturation in freshwater influenced shelves
Bibliographic record
Abstract
Abstract. In the summer of 2005, we sampled surface water and measured pH and total alkalinity (AT) underway aboard IB Oden along the Northwest Passage from Cape Farewell (South Greenland) to the Chukchi Sea. We investigated the variability of carbonate system parameters, focusing particularly on carbonate concentration [CO32−] and calcium carbonate saturation states, as related to freshwater addition, biological processes and physical upwelling. Measurements on AT, pH at 15°C, salinity (S) and sea surface temperature (SST), were used to calculate total dissolved inorganic carbon (CT), [CO32−] and the saturation of aragonite (ΩAr) and calcite (ΩCa) in the surface water. The same parameters were measured in the water column of the Bering Strait. Some surface waters in the Canadian Arctic Archipelago (CAA) and on the Mackenzie shelf (MS) were found to be undersaturated with respect to aragonite (ΩAr<1). In these areas, surface water was low in AT and CT (<1500 μmol kg−1) relative to seawater and showed low [CO32−]. The low saturation states were probably due to the likely the effect of dilution due to freshwater addition by sea ice melt (CAA) and river runoff (MS). High AT and CT and low pH, corresponded with the lowest [CO32−], ΩAr and ΩCa, observed near Cape Bathurst and along the South Chukchi Peninsula. This was linked to the physical upwelling of subsurface water with elevated CO2. The highest surface ΩAr and ΩCa of 3.0 and 4.5, respectively, were found on the Chukchi Sea shelf and in the cold water north of Wrangel Island, which is heavily influenced by high CO2 drawdown and lower CT from intense biological production. In the western Bering Strait, the cold and saline Anadyr Current carries water that is enriched in AT and CT from enhanced organic matter remineralization, resulting in the lowest ΩAr (~1.2) of the area.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".