A Process-Oriented Small Lake Scheme for Coupled Climate Modeling Applications
Bibliographic record
Abstract
Abstract A one-dimensional dynamic lake model is presented as a candidate for simulating small unresolved lakes within the land surface scheme of a regional or global climate model. This model is based largely on well-established process algorithms with some exceptions. The complete nonlinear surface energy balance is computed in a skin layer of arbitrary thickness in order to ensure rapid response times with the atmosphere. Turbulent mixing in the surface mixed layer is achieved through stirring and buoyancy production as well as shear production along the diurnal thermocline. The net effect of Kelvin–Helmholtz instability on thermocline structure is grossly accounted for by computing a linear temperature profile within a thermocline layer. The energetics of billowing is not considered; however, a significant thermocline leakage term is included. The model has been incorporated into the Canadian Land Surface Scheme and used to estimate regional turbulent sensible and latent heat fluxes over the Experimental Lakes Area in the boreal forest of northwestern Ontario—an area about 30% lake covered. It is demonstrated that the presence of open water has a significant effect on the net flux exchange with the atmosphere in this region. Sensible heat flux to the atmosphere is suppressed during the summer stratified period but enhanced in the fall, resulting in an increased accumulation of about 5% by the end of the open water season due to the presence of lakes. Turbulent latent heat flux to the atmosphere is more enhanced during autumn, with a final accumulation about 24% larger.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 teacher head, 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".