Enhanced interannual variability of the May North Atlantic Oscillation and its impact on summer sea ice in the North Atlantic after the mid-2000s
Bibliographic record
Abstract
Based on data diagnosis and numerical experiments, this study investigated the changes in the interannual properties of the May North Atlantic Oscillation (NAO) and their impact on summer (June–July) sea ice in the North Atlantic during 1979–2021. Results showed statistically significant increase in the interannual variability of the May NAO after the mid-2000s, which had remarkably enhanced impact on summer sea ice in the eastern Hudson Bay (EHB) and the western Labrador Sea (WLS). During 2005–2021, corresponding to a positive phase of the May NAO, anomalous surface westerly or northwesterly winds prevailed over the Hudson Bay and Labrador Sea in May. This led to statistically significant increase in sea ice in both the EHB and the WLS in May via dynamic processes (favoring southeastward movement of the sea ice) and thermal processes (changing surface turbulent heating and shortwave radiation). In comparison with the situation in May, the increase in sea ice in the EHB developed further during summer mainly via thermal processes (positive feedback between the increased sea ice and shortwave radiation). In contrast, amplitude of the increased sea ice in the WLS was comparable between May and summer. Dynamic processes (southeastward movement of sea ice), which was induced by a barotropic anomalous high in the troposphere centered over the Labrador Peninsula, favored the increase in sea ice in summer in the WLS. The tripole sea surface temperature anomalies in the North Atlantic and increased snowpack on the Labrador Peninsula in May, triggered by the positive phase of the May NAO, played an important role in the formation of the anomalous high. During 1979–2004, the surface wind, snowpack, and tripole sea surface temperature anomalies in May, triggered by the May NAO, were relatively weak, leading to statistically insignificant changes in summer sea ice in the EHB and WLS.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".