Convective Momentum Transport in a Simple Multicloud Model for Organized Convection
Bibliographic record
Abstract
Abstract Convective momentum transport (CMT) is the process of vertical transport of horizontal momentum by convection onto the environmental flow. The significance of CMT from mesoscale to synoptic- and planetary-scale organized cumulus convection has been established by various theoretical and observational studies. A new strategy mimicking the effect of unresolved mesoscale circulation based on the weak temperature gradient (WTG) approximation with a Gaussian profile to redistribute the heating due to parameterized cumulus convection at the subgrid scale is adopted here to construct a CMT parameterization for general circulation models (GCMs). Two main regimes of CMT are considered: an upscale squall-line regime and a downscale non-squall-line regime. An exponential probability distribution is used to select which of these two effects is active, conditional on the state of the large-scale shear. The shear itself is used as a measure of the persistence of mesoscale organized circulation due to the presence or not of tilted deep convective heating with lagged stratiform anvils. The CMT model is tested in the simple case of the multicloud model of Khouider and Majda, used here as a toy GCM. Numerical simulations are performed here for the simple case without rotation, in a parameter regime where the multicloud model exhibits packets of convectively coupled gravity waves moving in one direction, at 17 m s−1, and planetary-scale wave envelopes moving in the opposite direction, at 4–6 m s−1, reminiscent of the Madden–Julian oscillation (MJO) and the associated embedded synoptic-scale superclusters. The results herein show that the inclusion of CMT intensifies both the synoptic-scale convectively coupled waves and the manifestation of planetary-scale waves in the multicloud model. This provides evidence that the present CMT model captures the essence of the physical mechanism through which kinetic energy is transferred from the subgrid-scale mesoscale circulation to the large-scale/resolved motion. Sensitivity simulations showed that two key parameters for the CMT parameterization are the relative strength of the parameterized stratiform anvils and the dimensional threshold used in the exponential distribution for the cumulus friction and the upscale CMT forcing resulting from organized subgrid mesoscale circulation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".