Bibliographic record
Abstract
Abstract This work focuses on the seaward propagation of coastal precipitation with and without mountainous terrain nearby. Offshore of India, diurnal propagation of precipitation is observed over the Bay of Bengal. On the eastern side of the bay, a diurnal but nonpropagating signal is observed near the west coast of Burma. This asymmetry is consistent with the inertio-gravity wave mechanism. Perturbations generated by diurnal heating over the coastal mountains of India propagate offshore, amplify in the upwind direction, and dissipate in the downwind direction relative to the steering wind, owing to critical-level considerations. A linear model is applied to evaluate sensitivity to gravity waves, as these affect deep moist convection and propagation. Analyses are performed for various heating depths, mountain widths, stability, Coriolis effect, background mean wind, and friction. Calculations reveal how these factors affect the amplitude, dissipation, initiation phase, and propagation speed of the diurnal disturbance. The propagation of precipitation triggered by land–sea breezes is distinguishable from that triggered by a mountain–plains circulation. Convection resulting purely from mountain heating begins earlier, propagates slower, and damps faster than that of the land–sea breeze. For mountains near a coast, slower propagation and stronger earlier convection result from a resonance-like combination of two dynamical mechanisms. The propagation of precipitation is initially triggered by the mountain breeze near the coastal mountain. Over the open ocean, the dominant signal propagates as that of the land breeze but with stronger convection.
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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".