Sensitivity of Idealized Moist Baroclinic Waves to Environmental Temperature and Moisture Content
Bibliographic record
Abstract
Idealized simulations are used to examine the sensitivity of moist baroclinic wave growth to environmental temperature and moisture content. With relative humidity held fixed, the surface temperature at 45°N, denoted T 0 , is varied from 275 to 290 K. As T 0 increases, the atmospheric moisture content, moist instability, and moist available potential energy also increase. For the chosen initial configuration, moist waves develop larger eddy kinetic energy K e than corresponding dry waves, but enhanced diabatic heating at larger T 0 does not further increase K e . This finding is linked to a warm-frontal cyclonic potential vorticity (PV) anomaly that strengthens and shifts downstream at larger T 0 owing to increased diabatic heating along the frontal cloud band. This eastward shift feeds back negatively on the parent cyclone by increasing the downstream export of mechanical energy aloft and degrading the phasing between dry baroclinic vertical motion and buoyancy within the warm sector. The latter suppresses the conversion from eddy potential energy to K e [ C( P e , K e )], offsetting a direct enhancement of C( P e , K e ) by diabatic heating. Compared to their dry counterparts, isolated moist waves (initiated by a single finite-amplitude PV anomaly) display a similar sensitivity to T 0 , while periodic wave trains (initiated by multiple such anomalies) exhibit a stronger negative relationship. The latter stems from anticyclonic diabatic PV anomalies aloft that originate along the warm front and recirculate through the system to interact with the upper-level trough. This interaction leads to a horizontal forward wave tilt that enhances the conversion of wave K e into zonal-mean kinetic energy.
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 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".