On Adding Thermodynamic Damping Mechanisms to Refine Two Classical Models of Katabatic Winds
Bibliographic record
Abstract
Abstract The Prandtl and layer-averaged models of katabatic winds contain some nonphysical singularities in the analytical solutions, which give unbounded steady flow anomalies at zero slope angles or adiabatic lapse rates. This study presents some simple refinements of these two classical models, in which the aforementioned singularities are removed when Newtonian cooling and Rayleigh friction are included in the system. It is pointed out that, in the limit of zero slope angles or adiabatic lapse rates, the along-slope buoyancy force and the adiabatic heating caused by air descending approach zero. Under such circumstances, a bounded steady solution for the katabatic winds is impossible unless some damping mechanisms are included to retard the anomalies induced by the radiative cooling effect in the boundary layer. Newtonian cooling and Rayleigh friction are the two simplest thermodynamic damping mechanisms that can be included to balance the effects of eddy viscosity and eddy thermal conductivity in the katabatic-flow model. Physically speaking, the Newtonian cooling term represents a small partition of the radiative effect and the Rayleigh friction term represents an approximation of the bottom drag effect in a turbulent boundary layer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".