Turbulent Collapse and Recovery in the Stable Boundary Layer Using an Idealized Model of Pressure-Driven Flow with a Surface Energy Budget
Bibliographic record
Abstract
Abstract The evolution of the stable boundary layer is simulated using an idealized single-column model of pressure-driven flow coupled to a surface energy budget. Several commonly used parameterizations of turbulence are examined. The agreement between the simulated wind and temperature profiles and tower observations from the Cabauw tower is generally good given the simplicity of the model. The collapse and recovery of turbulence is explored in the presence of a large-scale pressure gradient, but excluding transient submesoscale atmospheric forcings such as internal waves and density-driven currents. The sensitivity tests presented here clarify the role of both rotation and the surface energy budget in the collapse and recovery of turbulence for the pressure-driven dry stable boundary layer (SBL). Conditions of stability are affected strongly by the geostrophic winds, the cloud cover, and the thermal conductivity of the surface. Inertial oscillations and the subsurface temperature have a weaker influence. Particularly noteworthy is the relationship between SBL regime and the relative importance of the terms in the surface energy budget.
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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) | 0.001 | 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".