A Numerical Study of a Mesoscale Convective System during TOGA COARE. Part I: Model Description and Verification
Bibliographic record
Abstract
A 16-h numerical simulation of the growing and mature stages of the 15 December 1992 Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) mesoscale convective system (MCS) is performed to demonstrate the predictability of tropical MCSs when initial conditions and model physical processes are improved.The MCS began with two entities S 1 and S 2 , which developed and eventually merged to form a large anvil cloud.To obtain a realistic simulation of the MCS, the initial moisture field in the operational European Centre for Medium-Range Weather Forecasts (ECMWF) analysis is improved, based on previous findings.The deep column ascent and surface potential temperature dropoff (SPTD) are implemented into the initiation mechanism of the Kain-Fritsch cumulus parameterization scheme (KF CPS).Other refinements to the KF CPS include the introduction of the accretion process in the formation of convective rain and the detrainment of rain and ice particles at the cloud top.With the improved initial conditions and model physics, the modeled MCS shows many features similar to the observations, including the evolution of the anvil cloud fraction, the three convective onsets at three different times during the growing stage, and the characteristics of two deep convective lines during the mature stage.A series of sensitivity tests indicates that the SPTD is largely responsible for the successful prediction of the life cycle of the MCS, while inclusion of the deep column ascent criterion yields a better timing for the onset of the mature stage.The effects of modifying the initial moisture field are also investigated.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".