Physical processes contributing to an ice free <scp>B</scp>eaufort <scp>S</scp>ea during <scp>S</scp>eptember 2012
Bibliographic record
Abstract
Abstract During the record September 2012 sea ice minimum, the Beaufort Sea became ice free for the first time during the observational record. Increased dynamic activity during late winter enabled increased open water and seasonal ice coverage that contributed to negative sea ice anomalies and positive solar absorption anomalies which drove rapid bottom melt and sea ice loss. As had happened in the Beaufort Sea during previous years of exceptionally low September sea ice extent, anomalous solar absorption developed during May, increased during June, peaked during July, and persisted into October. However in situ observations from a single floe reveal less than 78% of the energy required for bottom melt during 2012 was available from solar absorption. We show that the 2012 sea ice minimum in the Beaufort was the result of anomalously large solar absorption that was compounded by an arctic cyclone and other sources of heat such as solar transmission, oceanic upwelling, and riverine inputs, but was ultimately made possible through years of preconditioning toward a younger, thinner ice pack. Significant negative trends in sea ice concentration between 1979 and 2012 from June to October, coupled with a tendency toward earlier sea ice reductions have fostered a significant trend of +12.9 MJ m−2 yr−1 in cumulative solar absorption, sufficient to melt an additional 4.3 cm m−2 yr−1. Overall through preconditioning toward a younger, thinner ice pack the Beaufort Sea has become increasingly susceptible to increased sea ice loss that may render it ice free more frequently in coming years.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".