Seasonal Temperature and Circulation Patterns in a Hybrid Polar Lake, Great Bear Lake, Canada
Bibliographic record
Abstract
Abstract Great Bear Lake (GBL) is the largest lake entirely within Canada and the largest polar‐type lake in the world. It holds cultural and sustenance value to the Délı˛ne Got'ine. However, its baseline physical limnology and how this may be altered by climate warming and anthropogenic stressors have received little attention. To explore the roles that surface heat exchange, wind, seasonal ice cover, and thermodynamic constraints play in the seasonal progression of ventilation and stratification of GBL, we report data from two 2008‐09 moorings, satellite‐derived lake surface temperatures, and observations made in 1964. Three spatially constrained processes regulate seasonal patterns of ventilation and stratification. Mid‐lake temperatures remain below the temperature of maximum density (TMDsurf = 3.98°C) throughout the year. In this area, solar radiation drives vertical convection while cooling develops stratification. Waters along the perimeter of the lake and within its five major arms do rise above TMDsurf in summer and stratify. It follows that mixing between the inner and outer domains form water at TMDsurf to create a convergent sinking zone or thermal bar. Because TMD decreases with increasing pressure, ventilation in the deepest region of the lake (McTavish Arm, Zmax = 446 m) requires wind‐aided downwelling to force cold surface water to a depth where it lies closer to the local TMD, triggering thermobaric instability, which then drives full‐depth ventilation. These patterns of ventilation and stratification constrain the availability of light and nutrients, therefore setting rates of biogeochemical processes, and regulating the lake's overall response to climate change.
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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 | 0.001 | 0.001 |
| 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".