The climate sensitivity of northern Greenland fjords is amplified through sea-ice damming
Bibliographic record
Abstract
Abstract Record-high air temperatures were observed over Greenland in the summer of 2019 and melting of the northern Greenland Ice Sheet was particularly extensive. Here we show, through direct measurements, that near surface ocean temperatures in Sherard Osborn Fjord, northern Greenland, reached 4 °C in August 2019, while in the neighboring Petermann Fjord, they never exceeded 0 °C. We show that this disparity in temperature between the two fjords occurred because thick multi-year sea ice at the entrance of Sherard Osborn Fjord trapped the surface waters inside the fjord, which led to the formation of a warm and fresh surface layer. These results suggest that the presence of multi-year sea ice increases the sensitivity of Greenland fjords abutting the Arctic Ocean to climate warming, with potential consequences for the long-term stability of the northern sector of the Greenland Ice Sheet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".