Radiatively driven convection in ice‐covered lakes: Observations, scaling, and a mixed layer model
Bibliographic record
Abstract
Penetrative convection is discussed where the instability is driven by radiative heating of water below the temperature of maximum density. Convection of this type occurs in ice‐covered freshwater lakes in late spring, when the snow cover vanishes and solar radiation is absorbed beneath the ice cover. The vertical temperature structure, bulk mixed layer scaling, and mixed layer deepening are examined for a number of temperate and polar lakes. A bulk mixed layer scaling for this type of convection is based on energy arguments underlying the classical Deardorff convective scaling. The depth of the convective layer serves as an appropriate length scale. However, a modified scale that takes account of the energetics of a distributed radiation source term replaces the surface buoyancy flux velocity scale used by Deardorff. The scaling compares favorably with large‐eddy simulations of turbulence kinetic energy (TKE) and with both observations and large‐eddy simulations of the TKE dissipation rate. Mixed layer deepening is simulated with a model of convection beneath lake ice. The model describes the structure of the stably stratified layer just beneath the ice with a stationary solution to the heat transfer equation; the structure of the entrainment layer is parameterized with a zero‐order jump approach. The entrainment equation is derived from the mixed layer TKE budget and bulk mixed layer scaling. Entrainment regimes characteristic of convection beneath ice are analyzed. It is shown that if the Deardorff convective velocity scale is replaced with a scale incorporating the distributed buoyancy flux, the entrainment equation describing atmospheric and oceanic convective boundary layers also applies beneath the ice. Model predictions compare well with data from observations in a number of lakes. We propose and compare with observations an extension of the mixed layer model that allows for the inclusion of salinity. Although the salt concentration is low in most temperate and polar lakes, its dynamical effect can be significant close to the temperature of maximum density.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".