Annual dynamics of Arctic lake ice pressure ridge formation in Teshekpuk Lake, Alaska
Bibliographic record
Abstract
Lake ice pressure ridges are compression ruptures that typically form due to large air temperature variations, occurring mostly on large lakes in cold environments such as the Arctic tundra and boreal regions. Quantifying pressure ridge occurrence is important for societal (e.g., natural hazards) and ecological (e.g., fish habitat) reasons. Lake ice pressure ridges can be categorized into two main types: overlapped and folded. Overlapped ridges, the more common type, occur when one side of the rupture shifts upward and overrides the other. In contrast, folded ridges develop when both sides of the rupture buckle, creating upward or downward folds. Here, we document the presence and dynamics of an annual Arctic lake ice pressure ridge in Teshekpuk Lake, Alaska, which is the largest (~830 km2) thermokarst lake in the world. We combine (1) field observations, including photos, time-lapse camera, temperature and ground-penetrating radar (GPR) measurements, and (2) remote sensing observations, including satellite synthetic aperture radar (SAR) and uncrewed aerial vehicle (UAV) surveys. GPR (800 MHz) data was acquired on April 29 and May 4, 2022, along several transects perpendicular and parallel to the pressure ridge, showing its internal structure and thickness (up to ~3 m) variation. Lake ice temperature dataset, time-lapse camera images, and UAV orthoimages from late April and early May 2022 revealed that the pressure ridge activity increased as the ice surface temperatures warmed. Moreover, we compiled spaceborne SAR data between 2007 and 2025 to document the distribution of pressure ridges in 5 km grid cells over the time series, revealing that ridges occurred across most of the lake area but preferentially along the lake center and north and south margins. Finally, interferometric SAR (InSAR) data between April 19 and May 1, 2022, shows a common "split bullseye" pattern, indicating failure and buckling of the ice under compressive stress. These findings provide a comprehensive understanding of the formation, dynamics, and spatial distribution of lake ice pressure ridge formation in Teshekpuk Lake, offering critical insights into their ecological and societal implications in the context of a changing climate.
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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 | 0.001 | 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".