Cloud seeding as a technique for studying aerosol‐cloud interactions in marine stratocumulus
Bibliographic record
Abstract
Giant hygroscopic aerosols were introduced into a solid marine stratocumulus cloud (200 m thick) by burning hygroscopic flares mounted on an aircraft. The cloud microphysical response in two parallel seeding plumes was observed using an instrumented aircraft making 16 transects of the plumes. The cloud drop size distribution width increased in the plumes due to an increased number of small cloud drops (3–5 μ m) on the earlier transects and a 5‐fold increase in the number of large drops (20–40 μ m) relative to the background cloud 30 minutes later. The cloud effective diameter increased from about 11 μ m in the background to 13 μ m in the plumes. Although the giant nuclei were only a small fraction of the total aerosols produced by the flares, they dominated the cloud response. The merit of the seeding approach for controlled observational studies of aerosol‐cloud interactions in marine stratocumulus was demonstrated.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".