The Observed Evolution of Arctic Amplification over the Past 45 Years
Bibliographic record
Abstract
Abstract. To address research gaps in understanding Arctic Amplification, we use data from ERA5 and sea ice concentration to examine the seasonal, spatial and decadal evolutuion of Arctic 2-meter and lower tropospheric temperatures and lower tropospheric (surface to 850 hPa) static stability over the past 45 years. A Local Amplification Anomaly (LAA) metric is used to examine how spatial patterns of Arctic 2-meter temperature anomalies compare to anomalies for the globe as a whole. Pointing to impacts of seasonally-delayed albedo feedback, growing areas of end-of-summer (September) open water largely co-locate with the strongest positive anomlies of 2-meter temperatures through autumn and winter and their growth through time; small summer trends reflect the effects of a melting sea ice cover. Because of seasonal ice growth, the association between rising 2-meter temperatures and sea ice weakens from autumn into winter, except in the the Barents Sea where there have been prominent downward trends in winter ice extent. Imprints of variable atmospheric circulation are prominent in the Arctic temperature evolution. Low-level (surface to 850 hPa) stability over the Arctic increases from autumn through winter, consistent with the greater depth of surface-based atmospheric heating seen in autumn. However, trends towards weaker static stability dominate the Arctic Ocean in autumn and winter, especially over areas of September and wintertime ice loss. Sea ice thinning, leading to increased conductive heat fluxes though the ice, likely also contributes to reduced stability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".