Eddies in the Western Arctic Ocean From Spaceborne SAR Observations Over Open Ocean and Marginal Ice Zones
Bibliographic record
Abstract
Abstract The Western Arctic Ocean is a host to major ocean circulation systems, many of which generate eddies that can transport water masses and corresponding tracers over long distances from their formation sites. However, comprehensive observations of critical eddy characteristics are currently not available and are limited to spatially and temporally sparse in situ observations. Here we use high‐resolution spaceborne synthetic aperture radar measurements to detect eddies from their surface imprints in ice‐free sea surface roughness, and in sea ice patterns throughout marginal ice zones. We provide the first estimate of eddy characteristics extending over the seasonally ice‐free and marginal ice zone regions of the Western Arctic Ocean, including their locations, diameters, and monthly distribution. Using available synthetic aperture radar data, we identified over 4,000 open ocean eddies, as well as over 3,500 eddies in marginal ice zones from June to October in 2007, 2011, and 2016. Eddies range in size between 0.5 and 100 km and are frequently found over the shelf and near continental slopes but also present in the deep Canada Basin and over the Chukchi Plateau. We find that cyclonic eddies are twice more frequent compared to anticyclonic eddies at the surface, distinct from the dominating anticyclonic eddies observed at depth by in situ moorings and ice‐tethered profilers. Our study supports the notion that eddies are ubiquitous in the Western Arctic Ocean even in the presence of sea ice and emphasizes the need for improved ocean observations and modeling at eddy scales.
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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 | 0.001 |
| 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) | 0.000 | 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 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".