Internal waves pump waters in and out of a deep coastal embayment of a large lake
Bibliographic record
Abstract
Abstract Large internal waves are a ubiquitous feature of many thermally stratified lakes, and result in oscillating baroclinic flows that pump water into and out of deep coastal embayments. In the long, narrow, and deep Kempenfelt Bay of Lake Simcoe, we show that stratification and circulation were coupled, so that movements of the thermocline can effectively flush the embayment much faster than hydraulic residence time from river input alone. Internal currents were driven by long‐period internal waves and resulted in large horizontal excursion lengths of several kilometers, which could drive exchange of embayment waters with the main basin. If the embayments are long, wide, and deep, Coriolis forces also deflect the internal wave to follow the coastline on the right‐hand side in the direction of travel as a Kelvin‐type wave, resulting in a net cyclonic circulation in the embayment. This residual counterclockwise flow further facilitated flushing of Kempenfelt Bay. For the summer of 2015, we estimate that forced and free internal wave dynamics alone resulted in a seasonally averaged flushing timescale as short as 17 ± 6 d for the surface mixed layer, and of 13.5 ± 5 d for the hypolimnetic waters of Kempenfelt Bay. Kempenfelt Bay is representative of many long, deep, and narrow embayments found in the Laurentian Great Lakes and arctic fjords. The exchange processes investigated here are relevant for determining the dynamics of water quality parameters used as indicators to evaluate lake health and fish habitat.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".