Why is the cloud albedo — Particle size relationship different in optically thick and optically thin clouds?
Bibliographic record
Abstract
Recent studies have analyzed satellite data in terms of the relationship of cloud albedo with droplet size for warm clouds. It was found that for optically thick marine clouds (τ > 15) the cloud albedo increases with decreasing cloud droplet effective radius (re). For optically thinner marine clouds (τ < 15) cloud albedo increases with increasing re as to be expected if the liquid water content is adiabatic. Hypotheses for the change in sign in the τ ‐ re relationship are deviations from an adiabatic liquid water content or the presence of single layer versus multi layer clouds. In this study, the ECHAM model, which exhibits this sign change in the τ ‐ re correlation for optically thin and thick marine clouds, is used to test these hypotheses. Probability density functions of τ ‐ re show that the change in sign of the correlation can be attributed to precipitating versus non‐precipitating clouds, but not to the difference in single layer versus multi‐layer clouds.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".