The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates
Bibliographic record
Abstract
Abstract. We examine the relationship between the number concentration of boundary-layer cloud condensation nuclei (CCN) and light extinction to investigate underlying aerosol processes and satellite-based CCN estimates. For a variety of airborne and ground-based observations not dominated by dust, regression identifies the CCN (cm−3) at 0.4 ± 0.1% supersaturation with 100.3α +1.3σ0.75 where σ (Mm−1) is the 500 nm extinction coefficient by dried particles and α is the Angstrom exponent. The deviation of 1 km horizontal average data from this approximation is typically within a factor of 2.0. ∂logCCN / ∂logσ is less than unity because, among other explanations, growth processes generally make aerosols scatter more light without increasing their number. This, barring special meteorology–aerosol connections, associates a doubling of aerosol optical depth with less than a doubling of CCN, contrary to previous studies based on heavily averaged measurements or a satellite algorithm.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".