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Record W2130698238 · doi:10.1002/qj.1940

Spatial and temporal variability of aerosol particles in Arctic spring

2012· article· en· W2130698238 on OpenAlexaffabout
N. C. Shantz, Ismail Gültepe, P. S. K. Liu, Michael E. Earle, Alla Zelenyuk

Bibliographic record

VenueQuarterly Journal of the Royal Meteorological Society · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsAerosolAtmospheric sciencesEnvironmental scienceAltitude (triangle)Range (aeronautics)Particle (ecology)Biomass burningArcticClimatologyMeteorologyGeographyGeologyOceanographyMaterials science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.212
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2012
Admission routes2
Has abstractyes

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