Snowmelt variability in Polar Bear Pass, Nunavut, Canada, from QuikSCAT: 2000–2009
Bibliographic record
Abstract
Abstract Snowmelt onset and end date estimates are made from QuikSCAT scatterometer measurements in the Canadian High Arctic wetland of Polar Bear Pass (PBP) and the surrounding region of Bathurst Island, Nunavut. In situ data within PBP is used to validate QuikSCAT snowmelt onset/end date estimates. Results indicate that within PBP from 2000 to 2009, the mean snowmelt onset date was Year Day (YD) 162, the mean snowmelt end date was YD179, and the mean snowmelt duration was 17 days. More interannual variability was apparent in snowmelt end date and duration compared with onset, and only snowmelt end date was significantly correlated with mean June air temperature at −0.78. Cooler air temperatures in 2004 contributed to a long snowmelt duration of 24 days, and the very short snowmelt duration in 2007 of just 11 days was caused by rapid and sustained increases in air temperature. For snowmelt end date and duration the mean spatial pattern revealed two centres of later snowmelt end date/longer snowmelt duration over Bathurst Island. They were separated by early snowmelt end date/short snowmelt duration in PBP. These patterns are in agreement with the spatial distribution of mean May to July air temperature over Bathurst Island and are likely influenced by the local‐scale topography of Bathurst Island. Given the correlation between air temperature and snowmelt end date, we might expect quicker snowmelt under increased warming. The latter process may have implications for the sustainability of the PBP wetland under a warmer climate. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".