Modelling carbon exchange in the air, sea, and ice of the Arctic Ocean
Bibliographic record
Abstract
The purpose of this study is to investigate the evolution of the Arctic Ocean’s carbon uptake capacity and impacts on ocean acidification with the changing sea-ice scape. In particular, I study the influence on air-ice-sea fluxes of carbon with two major updates to commonly-used carbon cycle models I have included. One, incorporation of sea ice algae to the ecosystem, and two, modification of the sea-ice carbon pump, to transport brineassociated Dissolved Inorganic Carbon (DIC) and Total Alkalinity (TA) to the depth of the bottom of the mixed layer (as opposed to releasing it in the surface model layer). I developed the ice algal ecosystem model by adding a sympagic (ice-associated) ecosystem into a 1D coupled sea ice-ocean model. The 1D model was applied to Resolute Passage in the Canadian Arctic Archipelago and evaluated with observations from a field campaign during the spring of 2010. I then implemented an inorganic carbon system into the model. The carbon system includes effects on both DIC and TA due to the coupled ice-ocean ecosystem, ikaite precipitation and dissolution, ice-air and air-sea carbon exchange, and ice-sea DIC and TA exchange through a formulation for brine rejection to depth and freshwater dilution associated with ice growth and melt. The 1D simulated ecosystem was found to compare reasonably well with observations in terms of bloom onset and seasonal progression for both the sympagic and pelagic algae. In addition, the inorganic carbon system showed reasonable agreement between observations of upper water column DIC and TA content. The simulated average ocean carbon uptake during the period of open water was 10.2 mmol C m−2 day−1 ( 11 g C m−2 over the entire open-water season). Using the developments from the 1D model, a 3D biogeochemical model of the Arctic Ocean incorporating both sea ice and the water column was developed and tested, with a focus on the pan-Arctic oceanic uptake of carbon in the recent era of Arctic sea ice decline (1980 – 2015). The model suggests the total uptake of carbon for the Arctic Ocean (north of 66.5 N) increases from 110 Tg C yr−1 in the early eighties (1980 – 1985) to 140 Tg C yr−1 for 2010 – 2015, an increase of 30%. The rise in SST accounts for 10% of the increase in simulated pan-Arctic sea surface pCO2. A regional analysis indicated large variability between regions, with the Laptev Sea exhibiting low sea surface pH relative to the pan- Arctic domain mean and seasonal undersaturation of arag by the end of the standard run. Two sensitivity studies were performed to assess the effects of sea-ice algae and the sea-ice carbon pump in the pan-Arctic, with a focus on sea surface inorganic carbon properties. Excluding the sea ice-carbon-pump showed a marked decrease in seasonal variability of sea-surface DIC and TA averaged over the Arctic Ocean compared to the standard run, but only a small change in the net total carbon uptake (of 1% by the end of the no icecarbon-pump run). Neglecting the sea ice algae, on the other hand, exhibits only a small change in sea-surface DIC and TA averaged over the pan-Arctic Ocean, but a cumulative effect on the net total carbon uptake of the Arctic Ocean (reaching 5% less than that of the standard run by the end of the no-ice-algae run).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".