Observations of Mixing and Deep Convection in a deep Fjord-Type Lake, Quesnel Lake, Canada
Bibliographic record
Abstract
Deep lakes in temperate climates represent around 50% of the world’s surface, liquid freshwater storage, yet the mechanisms governing their seasonal deepwater renewal—and, in turn, their ability to support ecosystems—remain somewhat elusive. These lakes have depths of hundreds of meters thus experience extreme hydrostatic pressures, causing compressibility to significantly affect circulation. Combined with windstorms and inverse thermal stratification, this compressibility is hypothesized to trigger thermobaric instability which ultimately results in hypolimnetic ventilation. In this study, we investigate deep ventilation in Quesnel Lake, with a maximum depth of 511 m. The lake has a Y-shaped morphology formed by three arms and a horizontal extent of approximately 100 km. Our focus is on the East Arm, where the maximum depth occurs, which is surrounded by mountainous terrain which channels and amplifies wind forces.To assess long-term trends in deep ventilation, we analyzed data from two moorings within the East Arm (M9 and M14, respectively in 500 and 400m water depth), including years when they were deployed independently or when meteorological stations were inactive. To better understand deep water renewal mechanisms that occur during individual events, we focused on two winters with the most comprehensive coverage of water temperature and meteorological data. In 2007, M9 and M14 were operational simultaneously, complemented by a third mooring (M11 in 175m of water) and a meteorological station both near the eastern end of the East Arm. In 2023, M14 and M9, as well as a weather station at Hurricane Point (the narrowest section of the East Arm) were all simultaneously operational.For M9 (2003–2012, 2024) and M14 (2007, 2016–2024), a significant series of events during inverse-thermal stratification occurred in each observational year in mid-January. These events were observed to consistently reset the bottom temperature, evident as a rapid cooling as expected from thermobaric instability. We observed two distinct cooling modes. The first is characterized by the sequential vertical descent of cool water plumes through each mooring from top to bottom, which is typically associated with thermobaric instability theory. The second mode involves a sudden horizontal intrusion of colder water at depths of 400 m and 500 m, while the shallower thermistors are less affected. In January 2007, these series of events led to a net cooling of around 0.25°C at the deepest point of the lake (M9) and 0.4°C at M14. In both 2007 and 2024, meteorological data showed that windstorms, necessary to trigger thermobaric instability, accompanied by severe sub-zero air temperatures (reaching -23°C) preceded the bottom water-cooling events. Whether the mechanism of deep-water renewal occurs vertically or horizontally, over two decades of records consistently reveal an interaction between the lake’s deepest regions and surface waters.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".