An investigation into the aerosol dispersion effect through the activation process in marine stratus clouds
Bibliographic record
Abstract
The aerosol dispersion effect (the influence of an increasing number of aerosol particles on the width of the cloud droplet size distribution) has been observed in maritime clouds [e.g., Liu and Daum , 2002 ]. Climate model simulations show that the dispersion effect at least partially compensates the first indirect aerosol effect. The application of observational data from maritime stratus/stratocumulus clouds into an adiabatic parcel model allows to analyze the role of the aerosol activation process for the dispersion effect in order to better understand the microphysical mechanism of the dispersion effect in the early stage of cloud formation. When the total aerosol number concentration is increased, the parcel model simulations show that the higher number of aerosol particles at cloud base reduces the supersaturation, which results in a slower particle growth rate, and thus more cloud droplets remain small. This extends the droplet spectra toward the smaller size end and increases the spectral width. The broadening effect partially offsets the reduction of droplet radius because of an enhanced number of aerosol particles, leading to a positive aerosol dispersion effect. Sensitivity studies show that the dispersion effect decreases for increasing updraft velocities. When the updraft velocity approaches 55 m s −1 , the dispersion effect almost vanishes for maritime stratus clouds. Aerosols composed of sulfate or of less soluble organics increase the dispersion effect as compared to sea‐salt aerosols, whereas condensation of gaseous nitric acid on aerosols decreases the dispersion effect in marine stratus clouds.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".