Spatial and temporal variability of aerosol particles in Arctic spring
Bibliographic record
Abstract
Abstract The objective of this work is to investigate the variability in the aerosol particle number concentration in Arctic spring. The Indirect and Semi‐Direct Aerosol Campaign (ISDAC) was conducted during April 2008 in the vicinities of Fairbanks and Barrow, Alaska. Aircraft‐based measurements of total aerosol particle number concentration (Na) in the size range of 0.12–3 µm diameter were obtained using a passive cavity aerosol spectrometer probe (PCASP‐100X). The analysis considersNaduring cloud‐free periods in biomass burning (BB) and non‐BB aerosol loading scenarios, the latter including background cases and cases with elevated concentration in layers. The BB cases had air masses originating mainly from Russian and Asian forest and crop fires, whereas the non‐BB cases originated predominantly from Arctic or oceanic regions. The averageNafor all non‐BB cases was 127 cm−3, while that for all BB cases wasNa= 720 cm−3. These estimates do not, however, capture the details of aerosol particle layers encountered during most flights. Variability inNawas considered for constant altitude (horizontal) flight legs ranging from 50 to 650 km in length, as well as for vertical flight profiles up to 7 km above sea level. When aerosol particle layers were encountered,Narapidly increased from 20 to 550 cm−3, and reached up to 2200 cm−3within air masses dominated by BB plumes. The observed variability inNamay have important implications for estimating cloud microphysical properties as well as estimates of particle properties used in global climate model simulations, because averaging over large space‐ or time‐scales may not represent real atmospheric conditions. The analysis demonstrates the difficulty in interpreting average aerosol particle characteristics along longer flight legs, particularly during cases with higher particle loading that varies over shorter distance scales and time periods. Copyright © 2012 Royal Meteorological Society and Crown in the right of Canada.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".