Airborne observation of aerosol optical depth during ARCTAS: vertical profiles, inter-comparison and fine-mode fraction
Bibliographic record
Abstract
Abstract. We describe aerosol optical depth (AOD) measured during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment, focusing on vertical profiles, inter-comparison with correlative observations and fine-mode fraction. Arctic haze observed in <2 km and 2–4 km over Alaska in April 2008 originated mainly from anthropogenic emission and biomass burning, respectively, according to aerosol mass spectrometry and black carbon incandescence measurements. The Ångström exponent for these air masses is 1.4 ± 0.3 and 1.7 ± 0.1, respectively, when derived at 499 nm from a second-order polynomial fit to the AOD spectra measured with the 14-channel Ames Airborne Tracking Sunphotometer (AATS-14) over 354–2139 nm. We examine 55 vertical profiles selected from all phases of the experiment. For two thirds of them, the AOD spectra are within 3% + 0.02 of the vertical integral of local visible-light scattering and absorption. The horizontal structure of smoke plumes from local biomass burning observed in central Canada in June and July 2008 explains most outliers. The differences in mid-visible Ångström exponent are <0.10 for 63% of the profiles with 499-nm AOD > 0.1. The retrieved fine-mode fraction of AOD is mostly between 0.7 and 1.0, and its root mean square difference (in both directions) from column-integral submicron fraction (measured with nephelometers, absorption photometers and an impactor) is 0.12. These AOD measurements from the NASA P-3 aircraft, after compensation for below-aircraft light attenuation by vertical extrapolation, mostly fall within ±0.02 of AERONET ground-based measurements between 340–1640 nm for five overpass events.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".