Examining the Transition from a perennial to a seasonal sea ice cover in the Arctic Ocean: A Lagrangian Approach
Bibliographic record
Abstract
Background: Declining Arctic sea ice extent has been accompanied by a large loss in multiyear ice (MYI). The dynamic and thermodynamic processes which affect this transition include promotion of first year ice (FYI) to MYI, demotion (melting) of MYI to open water, and ice export through Fram Strait. In this study we quantify the relative importance of these three processes. Methods: We use the Lagrangian Ice Tracking System which employs satellite-derived sea ice drift vectors combined with sea ice concentrations to find annual areas of promotion, demotion, and export. Results: Over the satellite record (1989-2015), we quantify the total contributions to sea ice extent loss from promotion (+30 million km2), demotion (-19.7 million km2), and export of MYI (-18.6 million km2). The result is a total net loss of 8.3 million km2 of MYI. We find that all three processes are positively correlated with minimum sea ice extent and are increasing with rates of +0.165 million km2/decade, -0.146 million km2/ decade, and -0.096 million km2/decade for promotion, demotion, and export respectively. We also compute the negative ice growth feedback at 0.59 (with r2=0.27). This indicates that ice pack recovers, on average, 59% of the MYI area lost to demotion/export through promotion of FYI the following winter. Limitations: Uncertainties in the drift speed are compounded by the weekly temporal resolution of the model, which affects the resulting estimates of demotion and promotion area. Conclusion: Demotion and export combined are increasing faster than promotion and represent a larger area contribution. This imbalance accounts for the observed loss of MYI area.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".