Surface energy budget of landfast sea ice during the transitions from winter to snowmelt and melt pond onset: The importance of net longwave radiation and cyclone forcings
Bibliographic record
Abstract
Abstract Relatively few sea ice energy balance studies have successfully captured the transition season of warming, snowmelt, and melt pond formation. In this paper, we report a surface energy budget for landfast sea ice that captures this important period. The study was conducted in the Canadian Arctic Archipelago from 10 May to 20 June 2010. Over the first 20 days of the study, we found that short periods (1–3 days) of increased net radiation associated with low longwave loss provided most of the energy required to warm the snowpack from winter conditions. An extended period of low longwave loss (5 days) combined with the seasonal increase in incoming shortwave radiation then triggered snowmelt onset. Melt progressed with a rapid reduction in albedo and attendant increases in shortwave energy absorption, resulting in melt pond formation 8 days later. The key role of longwave radiation in initiating melt onset supports past findings, and confirms the importance of clouds and water vapor associated with synoptic weather systems. However, we also observed a period of strong turbulent energy exchange associated with the passage of a cyclone. The cyclone event occurred shortly after melt pond formation, but it delivered enough energy to significantly hasten melt onset had it occurred earlier in the season. Changes in the frequency, duration, and timing of synoptic‐scale weather events that deliver clouds and/or strong turbulent heat fluxes may be important in explaining observed changes in sea ice melt onset timing.
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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) | 0.000 | 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".