Spatial and temporal variability in snowmelt onset over Arctic sea ice
Bibliographic record
Abstract
Abstract Climate models suggest surface warming in the Arctic will be rapid and pronounced, implying substantial changes in snowmelt onset are likely. This research therefore examines spatial and temporal variability in passive-microwave derived snow-melt-onset dates over Arctic sea ice. The objectives are to understand better the regional characteristics of snowmelt and to document whether the snowmelt-onset record shows signs of climate change. Snowmelt-onset dates are derived with Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager brightness-temperature data, and they are subsequently stratified into 13 regions to analyze spatial and temporal variability. Results illustrate significant spatial variability in snowmelt onset, with the median annual snowmelt-onset date in one region of the Arctic typically being statistically different from most other regions. The examination of temporal variability also shows large interannual differences in the median snowmelt-onset date in most regions. Additionally, trends towards earlier snowmelt onset are documented in the West Central Arctic, Lincoln Sea, Beaufort Sea and Canadian Arctic Archipelago regions.
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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".