Characterizing sudden changes in Arctic sea ice drift and deformation on synoptic timescales
Bibliographic record
Abstract
Abstract. In this study, we develop a framework for the assessment of sudden changes in sea ice drift and associated deformation processes in response to atmospheric forcing and ice–coastal interactions, based on analysis of ice buoy triplet centroids and areas. Examined in particular is the spatiotemporal evolution in sea ice floes that are tracked with GPS beacons deployed in triplets in the southern Beaufort Sea at varying distances from the coastline in fall, 2009 – triplets A to D, with A (D) located closest to (furthest from) the coastline. This study illustrates the use of shock-response diagnostics to evaluate eight identified sudden changes or shock events on daily timescales. Results from this analysis show that shock events in the southern Beaufort Sea occur in at least one of two forms: (1) during a reversal in winds, or (2) sustained north/easterly winds, with response mechanisms governed by ice conditions and interactions with the coastline. Demonstrated also is the emergence of a shear-shock event (SSE) that results in reduced ice concentrations for triplets B, C, and D, one, three and five days following the SSE, respectively and loss of synchronicity in ice-atmosphere interactions. The tools developed in this study provide a unique characterization of sea ice dynamical processes in the southern Beaufort Sea, with implications for quantifying "shock-response" systems relevant for ice hazard assessments and forecasting applications required by oil and gas, marine transportation, and indigenous use of near shore Arctic areas.
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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 | 0.001 |
| 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 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".