Enhanced melting of the Greenland ice sheet and its impact on the Subpolar North Atlantic and AMOC
Bibliographic record
Abstract
Freshwater (FW) fluxes from river runoff and precipitation minus evaporation for the pan Arctic seas are relatively well documented and prescribed in ocean GCMs. Fluxes from Greenland on the other hand are generally ignored altogether, despite their potential impacts on ocean circulation and marine biology. Here, we present a reconstruction of the spatially distributed FW flux from Greenland for 1958-2010. We find a modest increase into the Arctic Ocean during this period. Fluxes into the Irminger Basin, however, have increased by fifty percent (6.30.5 km^3 yr-2) in less than twenty years. This greatly exceeds previous estimates. For the ice sheet as a whole the rate of increase since 1992 is 16.91.8 km^3 yr-2, which is eight times larger than the long term trend for Eurasian rivers. To investigate the impact on ocean dynamics, we force an eddy-permitting global ocean-sea ice model with the FW flux anomalies extended to 2020 based on current trends. Upon invading the surface waters of the subpolar North Atlantic, the additional FW leads to a gradual suppression of deep winter convection in the Labrador Sea, inducing a ten percent weakening of the large-scale meridional overturning circulation. Surface salinity in Baffin Bay is reduced as FW accumulates in the region before being advected by an outflow by the shallow Labrador Current along the continental slope. The FW then begins to spread over the surface waters of the interior Subpolar North Atlantic. Our results suggest that the trends in Greenland FW fluxes in the last twenty years have already begun to significantly influence the circulation and hydrography of the North Atlantic.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".