Observations of the evolution of the aerosol, cloud and boundary-layer characteristics during the 1st ACE-2 Lagrangian experiment
Bibliographic record
Abstract
During the 1st Lagrangian experiment of the North Atlantic Regional Aerosol Characterisation Experiment (ACE-2), a parcel of air was tagged by releasing a smart, constant level balloon into it from the Research Vessel Vodyanitskiy. The Meteorological Research Flight’s C-130 aircraft then followed this parcel over a period of 30 h characterising the marine boundary layer (MBL), the cloud and the physical and chemical aerosol evolution. The air mass had originated over the northern North Atlantic and thus was clean and had low aerosol concentrations. At the beginning of the experiment the MBL was over 1500 m deep and made up of a surface mixed layer (SML) underlying a layer containing cloud beneath a subsidence inversion. Subsidence in the free troposphere caused the depth of the MBL to almost halve during the experiment and, after 26 h, the MBL became well mixed throughout its whole depth. Salt particle mass in the MBL increased as the surface wind speed increased from 8 m s-1 to 16 m s-1 and the accumulation mode (0.1μm to 3.0 μm) aerosol concentrations quadrupled from 50 cm-3 to 200 cm-3. However, at the same time the total condensation nuclei (>3 nm) decreased from over 1000 cm-3 to 750 cm-3. The changes in the accumulation mode aerosol concentrations had a significant effect on the observed cloud microphysics. Observational evidence suggests that the important processes in controlling the Aitken mode concentration which, dominated the total CN concentration, included, scavenging of interstitial aerosol by cloud droplets, enhanced coagulation of Aitken mode aerosol and accumulation mode aerosol due to the increased sea salt aerosol surface area, and dilution of the MBL by free tropospheric air.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".