Sea Ice Drift and Arch Formation in the Robeson Channel Using Daily Coverage of Sentinel-1 SAR Data During the 2016–2017 Freezing Season
Bibliographic record
Abstract
Abstract. Robeson Channel (RC) is a narrow sea water passage between Greenland and Ellesmere Island in the Arctic. It is a pathway of sea ice from the central Arctic and out to the Baffin Bay. This paper uses a set of daily Synthetic Aperture Radar (SAR) images from Sentinel-1A/1B, acquired between September 2016 and April 2017, to study kinematics of individual ice floes as they approach then drift through the RC. Tracking of 39 selected floes was visually performed in the image sequence and their speed was calculated and linked to the reanalysis 10 m wind from ERA5. Results show that drift of ice floes is remarkably slow while in the compact ice regime upstream of the RC unless the floe is surrounded by water or thin ice. In this case the wind has more influence on the drift. On the other hand, ice floe drift is found to be about 4–5 times faster in the open drift regime within the RC and clearly influenced by wind. A linear trend is found between change in wind and change in ice drift speed components, both along the length of the channel. Case studies are presented to reveal the role of wind on ice floe drift in details. The study also addresses the development of the ice arch at the entry of the channel. It started development on 24 January and matured on 1 February 2017. Details of the formation process, using the sequential SAR images, are presented. The arch’s shape continued to adjust by rupturing ice pieces at locations of cracks under the influence of northerly wind (hence the contour keeps displacing northward). The study highlights the advantage of using the high-resolution daily SAR coverage in monitoring aspects of sea ice cover in narrow water passages where the ice cover is highly dynamic. The information will be particularly interesting for possible applications of SAR constellation systems.
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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 | 0.001 | 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) | 0.001 | 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".