Simple Multicloud Models for the Diurnal Cycle of Tropical Precipitation. Part I: Formulation and the Case of the Tropical Oceans
Bibliographic record
Abstract
Abstract The variation of tropical precipitation due to the diurnal cycle of solar heating is examined here in the context of two simple models for tropical convection. The models utilize three cloud types—congestus, deep, and stratiform—that are believed to characterize organized tropical convection and are based on the two first baroclinic modes of vertical structure plus a boundary layer mode. The two models differ mainly in the way they treat the boundary layer dynamics. The first one is purely thermodynamical and is reduced to a single equation for the equivalent potential temperature θe connecting the boundary layer to the upper troposphere through downdrafts and to the surface through evaporation while the second uses full bulk boundary layer (FBBL) dynamics with a careful separation between sensible and latent heat fluxes and parameterization of nonprecipitating shallow cumulus. It turns out that in the case of the precipitation over the ocean where the Bowen ratio is small, both models yield a qualitatively similar solution, characterized by an overnight initiation and early morning peak in precipitation consistent with observations. The modeled diurnal cycle of precipitation over the ocean is divided into four cyclic phases: 1) a CAPE (re)generation phase characterized by the enhancement of the boundary layer θe and moisture fluxes during midday and early afternoon that is followed by 2) a (re)moistening phase dominated by congestus heating during the late afternoon and moistening from downdrafts (due to detrainment of shallow cumulus, specifically in the FBBL model) and radiative cooling that lasts until midnight. 3) Deep convection is initiated around midnight when the midtroposphere is sufficiently moist and cool and (re)establishes the precipitation level near its radiative convective equilibrium (1 K day−1) and then 4) peaks with sunrise at 0600 LST to yield a precipitation maximum of roughly 2 K day−1 at around 0900 LST that dries the troposphere and consumes CAPE and closes the cycle.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".