Numerical modelling of internal gravity waves generated by a thermal forcing in an anelastic atmospheric flow with vertical shear
Bibliographic record
Abstract
A numerical model is presented for internal gravity waves generated by deep or shallow latent heating in the lower atmosphere. The configuration comprises a background fluid flow with vertical shear and vertical stratification in a two-dimensional computational domain. A thermal forcing term is included in the energy conservation equation for the fluid flow. This term is sinusoidal in the horizontal direction and localized in the vertical direction and it generates a perturbation in the form of an upward-propagating internal gravity wave with a horizontal wavelength corresponding to that of the thermal forcing oscillation. If there is no critical level where the background flow speed is equal to the wave phase speed, then the wave propagates to the upper boundary of the domain where a non-reflecting boundary condition or radiation condition is imposed numerically. With a vertically-sheared background flow, where a critical level is present, nonlinear wave-mean-flow interactions occur. Vertical fluxes of momentum and energy lead to the development of higher horizontal wavenumber and zero wavenumber components. There is a transfer of momentum and energy to the background flow which reduces the wave amplitude in the upper levels of the domain and results in changes in the background velocity and temperature and the development of regions of convective instability near the critical level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".