Drivers of freshwater (co)variability in the Arctic Ocean and subarctic North Atlantic
Bibliographic record
Abstract
Significant freshwater changes have recently been observed both in the Arctic Ocean and the subpolar North Atlantic. To investigate possible links, we compared the liquid freshwater content of the subarctic North Atlantic with the sum of liquid and solid freshwater content of the Arctic Ocean from observations between 1990 and 2013. We found a distinct anti-correlation of the freshwater anomalies in these two regions with anomalies of almost the same magnitude. \nAn analysis of freshwater fluxes from the global Finite Element Sea ice Ocean Model (FESOM) and the Common Ocean-ice Reference Experiment version 2 (CORE-II) atmospheric forcing data set suggests that the observed freshwater variations resulted from changing freshwater transports. Variations in the Arctic freshwater export to the North Atlantic are found to be most important for the total freshwater content variability of the upper Arctic Ocean and for the liquid freshwater content variability of the western SANA. The eastern SANA freshwater content seems to be mainly influenced by the exchange with the subtropical North Atlantic. \nFurthermore these changes are correlated with large-scale atmospheric pressure and circulation patterns. Thereby the export from the Arctic Ocean through the Canadian Arctic Archipelago is associated with different patterns than the export through the Fram Strait and Barents Sea Opening. We propose, that the recently observed rapid changes in the SANA and upper Arctic Ocean freshwater content resulted from an interplay of these different driving patterns causing parallel changes in the freshwater export on both sides of Greenland. \nAccording to the present phase of the decadal alternations of the atmospheric variability and our freshwater content time series, the fresh water that accumulated in the Arctic Ocean during the previous decades started to be released into the SANA. This release might continue in the following years and could have the potential to impact the Atlantic Meridional Overturning Circulation and the oceanic heat release to the Arctic atmosphere and sea ice.
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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".