Impact of additional freshwater around Antarctica on the Southern Ocean carbon cycle : an inter-model comparison
Bibliographic record
Abstract
The ongoing increase of global mean temperature, caused by anthropogenic CO2 emissions, will most likely lead to enhanced melting and calving of Antarctic ice shelves in the coming decades. As a consequence, the freshwater input into the Southern Ocean is expected to increase as well. The resulting change in ocean salinity could have significant consequences for ocean circulation, water column stratification, and water mass formation in the Southern Ocean, which are all expected to affect the capacity of the surface ocean to remove CO2 from the atmosphere, and the sequestration of carbon in the deep ocean. However, the magnitude and spatio-temporal patterns of these changes and their links to freshwater forcing are not yet well understood. To reduce these uncertainties, increase our understanding, and better quantify the feedbacks on the climate system, the international SOFIA initiative (Swart et al., 2023) defines freshwater input protocols for consistent use in various Earth System Models. Here we study the impact of additional freshwater around Antarctica on circulation and carbon fluxes in a steady preindustrial climate state using four Earth System Models. Most of the models show a decrease in the uptake of CO2 by the surface of the Southern Ocean, caused by a strengthened outgassing of natural CO2 between 50°S and 60°S. The stronger outgassing can be attributed to an increase in sub-surface dissolved inorganic carbon concentration south of the Antarctic Circumpolar Current that is associated with a redistribution of water masses in the Southern Ocean. Furthermore the reduction of the production and downward flow of Antarctic Bottom Water is leading to a decrease of its volume, and the expansion of carbon-rich Circumpolar Deep Water, which increases the carbon content at depth and thus weakens the overall CO2 uptake. However, the models disagree in terms of the intensity of the weakened Southern Ocean CO2 uptake. This difference seems to be mainly linked to the model resolution and the representation of the ocean mean state, e.g. the strength of the stratification, which is a determining factor for the redistribution of the additional freshwater to depth. To pursue this work, experiments with additional freshwater forcing in various climate states are conducted to analyse the ocean carbon cycle’s response and quantify potential climate feedbacks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".