Aerosol–Cloud Interactions in a Mesoscale Model. Part I: Sensitivity to Activation and Collision–Coalescence
Bibliographic record
Abstract
Abstract High-resolution numerical simulations of the aerosol–cloud feedbacks are performed with a mesoscale model. The multimodal aerosol species, added to the model, and the cloud species were represented by two spectral moments. The aerosol sources include particle activation, solute transfer between drops due to collision and coalescence of drops, and particle regeneration. A summertime case was simulated consisting of a cold frontal cloud system and a postfrontal stratus. Experiments with both simple and mechanistic activation parameterization of aerosol and with one and two aerosol modes were performed. Verification was made of the stratus properties against measurements taken during the Radiation Aerosol and Cloud Experiment (RACE). The results demonstrate a significant sensitivity of the stratus and of the frontal system to the aerosol and a moderate impact on the particle spectrum of drop collision–coalescence. The stratus simulation with mechanistic activation and unimodal aerosol showed the best agreement of droplet concentration with the observations, and the simulations with mechanistic activation and a bimodal aerosol and with simple activation underestimated the droplet concentration. A similar high sensitivity was found for the frontal precipitation intensity. Drop collision–coalescence in the frontal system was found to have an impact on the particle mean radius whose magnitude amounted to 10% and 15% for one and multiple cloud cycles, respectively. This impact was also found to be highly variable in space. The modified particle spectrum, following activation in clouds, was found to increase droplet concentration.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".