Emerging impacts of enhanced Greenland melting on Labrador Sea dynamics
Bibliographic record
Abstract
Meltwater input to the subpolar North Atlantic from the Greenland ice sheet has been steadily increasing in the past decades due to global warming. To identify the impacts of this enhanced freshwater input since the late 1990s, we use output from the eddy-rich model VIKING20X (1/20˚) running two nearly identical simulations from 1997–2021 only differing in the freshwater input from Greenland: one with realistic interannually varying runoff increasing in the early 2000s and the other continued after 1997 using the local, grid-cell climatology of 1961–2000 maintaining the mean seasonal runoff cycle. Here, runoff is based on the JRA55-do reanalysis (Tsujino et al., 2018, Ocn.Mod.), which includes the Bamber et al. (2018, JGR-O) Greenland runoff and calving record, where liquid and solid discharge is combined into a single liquid flux entering the ocean through the surface and coast. Apart from this, atmospheric forcing is identical between the two runs. To our knowledge this is the first set of twin experiments with a most realistic, well validated, eddy-rich ocean model to assess the impact of the current, observed increase in Greenland ice sheet mass loss. We find that the majority of the additional freshwater remains within the boundary current. This enhances the density gradient between the fresh and cool slope current and the warm and salty waters of the interior Labrador Sea and leads to a small (.01 m/s) but significant increase in boundary current speed in our experiment. Both, the faster slope current and the enhanced shelf–interior density gradient increase the potential for intensified eddy shedding into the interior Labrador Sea. This more dynamic regime fosters the eddy-driven import of fresh boundary current waters (Polar Water and meltwater) into the nearby deep convection regions. Lastly, our experiments indicate a role of enhanced Greenland runoff in the eastward shift of deep convection reported by Rühs et al. (2021, JGR-O) for the recent period 2015–2018. The experiment with realistically increased runoff exhibits meltwater tracer mixed only to shallower depths before transferred east into the Irminger Sea leading to a weaker stratification in the upper to mid-depth Irminger Sea than in the experiment with less, climatological runoff, which would enable or at least support deep convection southeast of Greenland.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".