Freshwater input from glacier melt outside Greenland alters modeled northern high-latitude ocean circulation
Bibliographic record
Abstract
Abstract. As anthropogenic climate change depletes Earth's ice reservoirs, large amounts of fresh water are released into the ocean. Since the ocean has a major influence on Earth's climate, understanding how the ocean changes in response to an increased freshwater input is crucial for understanding ongoing shifts in the climate system. Moreover, to comprehend the evolution of ice–ocean interactions, it is important to investigate if and how changes in the ocean might affect marine-terminating glaciers' stability. Though most attention in this context has been on freshwater input from Greenland, the other Northern Hemisphere glacierized regions are losing ice mass at a combined rate roughly half that of Greenland and should not be neglected. In order to get a first estimate of how glacier mass loss around the Arctic affects the ocean and how potential changes in the ocean circulation might affect marine-terminating glaciers, we conduct one-way coupled experiments with an ocean general circulation model (NEMO-ANHA4) and a glacier evolution model (Open Global Glacier Model; OGGM) for the years 2010 to 2019. We find an increase in the heat content of Baffin Bay due to an enhanced gyre circulation that leads to an increased heat transport through Davis Strait. We also find changes in the subpolar gyre's structure: an increase in density and a decrease in sea surface height in the eastern part and vice versa in the western part. Additionally, we find a decreased heat transport into the Barents Sea due to increased freshwater input from Svalbard and the Russian Arctic. The rerouting of Atlantic water from the Barents Sea Opening through Fram Strait leads to an increased heat transport into the Arctic Ocean and a decrease in sea ice thickness in the Fram Strait area.
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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 | 0.000 | 0.000 |
| 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".