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Record W2102153636 · doi:10.5194/acp-15-12487-2015

A multi-year study of lower tropospheric aerosol variability and systematic relationships from four North American regions

2015· article· en· W2102153636 on OpenAlexaffabout
James P. Sherman, Patrick J. Sheridan, J. A. Ogren, Elisabeth Andrews, Derek Hageman, Lauren Schmeisser, Anne Jefferson, Sangeeta Sharma

Bibliographic record

VenueAtmospheric chemistry and physics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersClimate Program OfficeScience and Technology DirectorateNational Oceanic and Atmospheric AdministrationAppalachian State UniversityU.S. Department of Energy
KeywordsAerosolSingle-scattering albedoEnvironmental scienceAtmospheric sciencesContext (archaeology)Albedo (alchemy)ClimatologyTroposphereMineral dustParticulatesMeteorologyGeographyChemistryGeology

Abstract

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Abstract. Hourly averaged aerosol optical properties (AOPs) measured over the years 2010–2013 at four continental North American NOAA Earth System Research Laboratory (NOAA/ESRL) cooperative aerosol network sites – Southern Great Plains near Lamont, OK (SGP), Bondville, IL (BND), Appalachian State University in Boone, NC (APP), and Egbert, Ontario, Canada (EGB) are analyzed. Aerosol optical properties measured over 1996–2009 at BND and 1997–2009 at SGP are also presented. The aerosol sources and types in the four regions differ enough so as to collectively represent rural, anthropogenically perturbed air conditions over much of eastern continental North America. Temporal AOP variability on monthly, weekly, and diurnal timescales is presented for each site. Differences in annually averaged AOPs and those for individual months at the four sites are used to examine regional AOP variability. Temporal and regional variability are placed in the context of reported aerosol chemistry at the sites, meteorological measurements (wind direction, temperature), and reported regional mixing layer heights. Basic trend analysis is conducted for selected AOPs at the long-term sites (BND and SGP). Systematic relationships among AOPs are also presented. Seasonal variability in PM1 (sub-1 μm particulate matter) scattering and absorption coefficients at 550 nm (σsp and σap, respectively) and most of the other PM1 AOPs is much larger than day of week and diurnal variability at all sites. All sites demonstrate summer σsp and σap peaks. Scattering coefficient decreases by a factor of 2–4 in September–October and coincides with minimum single-scattering albedo (ω0) and maximum hemispheric backscatter fraction (b). The co-variation of ω0 and b lead to insignificant annual cycles in top-of-atmosphere direct radiative forcing efficiency (DRFE) at APP and SGP. Much larger annual DRFE cycle amplitudes are observed at EGB (~ 40 %) and BND (~ 25 %), with least negative DRFE in September–October at both sites. Secondary winter peaks in σsp are observed at all sites except APP. Amplitudes of diurnal and weekly cycles in σap at the sites are larger for all seasons than those of σsp, with the largest differences occurring in summer. The weekly and diurnal cycle amplitudes of most intensive AOPs (e.g., those derived from ratios of measured σsp and σap) are minimal in most cases, especially those related to parameterizations of aerosol size distribution. Statistically significant trends in σsp (decreasing), PM1 scattering fraction (decreasing), and b (increasing) are found at BND from 1996 to 2013 and at SGP from 1997 to 2013. A statistically significant decreasing trend in PM10 scattering Ångström exponent is also observed for SGP but not BND. Most systematic relationships among AOPs are similar for the four sites and are adequately described for individual seasons by annually averaged relationships, although relationships involving absorption Ångström exponent vary with site and season.

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 score0.154
Threshold uncertainty score0.307

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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.217
Teacher spread0.190 · 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

Citations97
Published2015
Admission routes2
Has abstractyes

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