Arctic freshwater export in the 20th and 21st centuries
Bibliographic record
Abstract
Climate simulations suggest that the emissions of carbon dioxide and other greenhouse gases will lead to strong climate changes in the 21st century. Here the resulting effects of the freshwater balance of the Arctic Ocean in the 21st century are analyzed using coupled Intergovernmental Panel on Climate Change simulations with the Max Planck Institute for Meteorology climate model. For the Arctic region, particularly strong warming and an almost complete removal of sea ice during summer time are predicted. Arctic river runoff and net atmospheric freshwater input (P‐E) are strongly enhanced. Most of this additional freshwater input is stored in the Arctic Ocean. While the total freshwater export out of the Arctic remains almost constant, significant changes occur in its distribution. The dominance of sea ice for the Fram Strait export disappears, while the liquid freshwater export is enhanced. The mean export shows therefore almost no changes, but its interannual variability is slightly reduced. In contrast, both the export through the Canadian Archipelago and its variability are increased in the 21st century. Therefore the importance of the Canadian Archipelago for the total Arctic export grows. Enhanced freshwater input into the Labrador Sea leads to a strong decrease in deep convection. Greenland Sea convection is reduced as well but mainly because of strong warming of the upper ocean layers. The meridional overturning circulation responds with a decline of about 6 sverdrups.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".