Morphology of sea ice pressure ridges in the northwestern Weddell Sea in winter
Bibliographic record
Abstract
To investigate the morphology and distribution of pressure ridges in the northwestern Weddell Sea, ice surface elevation profiles were measured by a helicopter‐borne laser altimeter during Winter Weddell Outflow Study with the German R/V Polarstern in 2006. An optimal cutoff height of 0.62 m, derived from the best fits between the measured and theoretical ridge height and spacing distributions, was first used to separate pressure ridges from other sea ice surface undulations. It was found that the measured ridge height distribution was well modeled by a negative exponential function, and the ridge spacing distribution by a lognormal function. Next, based on the ridging intensity Ri (the ratio of mean ridge sail height to mean spacing), all profiles were clustered into three regimes by an improved k‐means clustering algorithm: Ri ≤ 0.01, 0.01 < Ri ≤ 0.026, and Ri > 0.026 (denoted as C1, C2, and C3 respectively). Mean (and standard deviation) of sail height was 0.99 (±0.07) m in Regime C1, 1.12 (±0.06) m in C2, and 1.17 (±0.04) m in C3, respectively, while the mean spacings (and standard deviations) were 232 (±240) m, 54 (±20) m, and 31 (±5.6) m. These three ice regimes coincided closely with distinct sea ice regions identified in a satellite radar image, where C1 corresponded to the broken ice in the marginal ice zone and level ice formed in the Larsen Polynya, C2 corresponded to the deformed first‐ and second‐year ice formed by dynamic action in the center of the study region, and C3 corresponded to heavily deformed ice in the outflowing branch of the Weddell Gyre. The results of our analysis showed that the relationship between the mean ridge height and frequency was well modeled by a logarithmic function with a correlation coefficient of 0.8, although such correlation was weaker when considering each regime individually. The measured ridge height and frequency were both greater than those reported by others for the Ross Sea. Compared with reported values for other parts of the Antarctic, the present ridge heights were greater, but the ridge frequencies and ridging intensities were smaller than the most extreme of them. Meanwhile, average thickness of ridged ice in our study region was significantly larger than that of the Coastal Ross Sea showing the importance of deformation and ice age for ice conditions in the northwestern Weddell Sea.
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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) | 0.000 | 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".