New insight into the influence of the Greenland high on summer Arctic sea ice
Bibliographic record
Abstract
Abstract The Greenland high (GL-high) coincides with a local center of action of the summer North Atlantic Oscillation and is known to have significant influence on Greenland ice sheet melting and summer Arctic sea ice. However, the mechanism behind the influence on regional Arctic sea ice is not yet clear. In this study, using reanalysis datasets and satellite observations, the influence of the GL-high in early summer on Arctic sea ice variability, and the mechanism behind it, are investigated. In response to an intensified GL-high, sea ice over the Beaufort Sea shows significant decline in both concentration and thickness from June through September. This decline in sea ice is primarily due to thermodynamic and mechanical redistribution processes. Firstly, the intensified GL-high increases subsidence over the Canadian Basin, leading to an increase in surface air temperature by adiabatic heating, and a substantial decrease in cloud cover and thus increased downward shortwave radiation. Secondly, the intensified GL-high increases easterly wind frequency and wind speed over the Beaufort Sea, pushing sea ice over the Canadian Basin away from the coastlines. Both processes contribute to an increase in open water areas, amplifying ice–albedo feedback and leading to sea ice decline. The mechanism identified here differs from previous studies that focused on northward moisture and heat transport and the associated increase in downward longwave radiation over the Arctic. The impact of the GL-high on the regional sea ice (also Arctic sea ice extent) can persist from June into fall, providing an important source for seasonal prediction of Arctic sea ice. The GL-high has an upward trend and reached a record high in 2012 that coincided with a record minimum summer Arctic sea ice extent, and has strong implications for summer Arctic sea ice changes.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".