Recent Northern Hemisphere snow cover extent trends and implications for the snow‐albedo feedback
Bibliographic record
Abstract
Monotonic trend analysis of Northern Hemisphere snow cover extent (SCE) over the period 1972–2006 with the Mann‐Kendall test reveals significant declines in SCE during spring over North America and Eurasia, with lesser declines during winter and some increases in fall SCE. The weekly mean trend attains −1.28, −0.78, and −0.48 × 10 6 km 2 (35 years) −1 over the Northern Hemisphere, North America, and Eurasia, respectively. The standardized SCE time series vary and trend coherently over Eurasia and North America, with evidence of a poleward amplification of decreasing SCE trends during spring. Multiple linear regression analyses reveal a significant dependence of the retreat of the spring continental SCE on latitude and elevation. The poleward amplification is consistent with an enhanced snow‐albedo feedback over northern latitudes that acts to reinforce an initial anomaly in the cryospheric system.
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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) | 0.000 | 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) | 0.002 | 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".