Polar amplification and elevation-dependence in trends of Northern Hemisphere snow cover extent, 1971–2014
Bibliographic record
Abstract
Recent years (i.e., 2007–2014) have exhibited large declines in snow cover extent (SCE) in the Northern Hemisphere (NH), marked by earlier snowmelt in the springtime. In Northern latitudes, the snow-albedo feedback (SAF) is most pronounced in the spring and may be contributing to these decreasing trends in SCE. Rising surface air temperatures and changes in precipitation patterns could also vary the declining trends in SCE depending on latitude and elevation. Previous trend analyses of NH SCE are extended here to cover the period 1 October 1971 to 30 September 2014 using observed data from the National Oceanic and Atmospheric Administration snow chart climate data record. Trends in snow coverage (significant when p < 0.05) with latitude and elevation are investigated using the Mann–Kendall test. Over the 43 year period, strong polar amplification of negative trends in snow cover are observed. The majority of statistically significant negative trends are found in the mid- to high-latitudes, reaching a maximum reduction at 75.5°N. There is also elevation dependence of SCE over time as statistically significant negative trends occur at most elevations, with the strongest observed at 3950 m a.s.l. These significant negative trends exhibited in the mid- to high-latitudes and mid- to high-elevations provide evidence of polar amplification and elevation dependence of trends in snow cover in a warming climate, suggesting a leading role of the SAF on the recent retreat of NH snow cover.
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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 | 0.000 | 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) | 0.001 | 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 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".