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Record W4242423234 · doi:10.5194/acpd-14-26971-2014

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

2014· preprint· en· W4242423234 on OpenAlexaffabout
James P. Sherman, Patrick J. Sheridan, J. A. Ogren, Elisabeth Andrews, Lauren Schmeisser, Anne Jefferson, Sangeeta Sharma

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersClimate Program OfficeNational Oceanic and Atmospheric AdministrationAppalachian State UniversityU.S. Department of Energy
KeywordsAerosolSingle-scattering albedoRadiative forcingAtmospheric sciencesEnvironmental scienceSeasonalityClimatologyAlbedo (alchemy)Radiative transferTroposphereForcing (mathematics)Annual cycleAbsorption (acoustics)Mineral dustDiurnal temperature variationGeographyPhysicsMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract. Hourly-averaged aerosol radiative properties measured over the years 2010–2013 at four continental North American NOAA/ESRL Federated Aerosol Network sites – Southern Great Plains in Lamont, OK (SGP), Bondville, IL (BND), Appalachian State University in Boone, NC (APP), and Egbert, Ontario, Canada (EGB) were analyzed to determine regional variability and temporal variability on several timescales, how this variability has changed over time at the long-term sites (SGP and BND), and whether systematic relationships exist for key aerosol properties relevant to radiative forcing calculations. The aerosol source types influencing the four sites differ enough so as to collectively represent rural, anthropogenically-perturbed air conditions over much of continental North America. Seasonal variability in scattering and absorption coefficients at 550 nm (σsp and σap, respectively) and most aerosol intensive properties was much larger than day of week and diurnal variability at all sites for both the sub-10 μm and sub-1 μm aerosols. Pronounced summer peaks in scattering were observed at all sites, accompanied by broader peaks in absorption, higher single-scattering albedo (ω0), and lower hemispheric backscatter fraction (b). Amplitudes of diurnal and weekly cycles in absorption at the sites were larger for all seasons than those of scattering. The cycle amplitudes of intensive optical properties on these shorter timescales were minimal in most cases. In spite of the high seasonality in ω0 and b, the co-variation of these two intensive properties cause the corresponding seasonal cycle in monthly median direct radiative forcing efficiency to be small, with changes of only a few percent at all sites. Median sub-10 μm aerosol σsp values for SGP and BND for the 2010–2013 time period were ~25% lower for all months than during the late 1990s period studied by Delene and Ogren (2002), consistent with the trends reported in other North American studies. There were even larger reductions in sub-1 μm aerosol σsp, leading to a larger coarse-mode influence at both sites. Similar reductions in median σap were observed at BND but median σsp changed little at SGP relative to the earlier observations of D&O2002, leading to lower ω0 at SGP. Most intensive properties and their variability were similar for both periods but median b was larger for all months of the 2010–2013 period at BND and nearly all months at SGP, indicating a shift toward smaller accumulation-mode particles. Systematic relationships between aerosol radiative properties were developed and applied to provide information on aerosol source types and processes at the four sites but some key relationships varied noticeably with season, indicating that the use of such relationships for model evaluation and inversion of remote sensing data must consider their seasonality.

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 score0.165
Threshold uncertainty score0.328

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 head0.031
GPT teacher head0.225
Teacher spread0.195 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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