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Record W1967775291 · doi:10.1029/2004jd005157

Robust optical features of fine mode size distributions: Application to the Québec smoke event of 2002

2005· article· en· W1967775291 on OpenAlexafffundabout
Norman T. O’Neill, S. Thulasiraman, T. F. Eck, Jeffrey S. Reid

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric SciencesUniversity of Maryland, Baltimore CountyCarnegie Corporation of New YorkSmithsonian Environmental Research CenterNational Aeronautics and Space AdministrationGoddard Space Flight CenterSmithsonian Institution
KeywordsPhysicsStatistical physicsMonotonic functionAERONETMode (computer interface)Extinction (optical mineralogy)Angstrom exponentComputational physicsAerosolMathematicsOpticsMathematical analysisMeteorology

Abstract

fetched live from OpenAlex

Simple relationships involving the fundamental parameters of fine mode aerosol optical depth (τ f ), Angstrom exponent (α f ) and its derivative (α f ′) as near‐monotonic functions of the effective van de Hulst parameter (ρ eff,f = 2 (2 π r eff,f /λ) ∣m − 1∣) were derived for the conceptual case of a log‐translatable particle size distribution (LTPSD). This notion is useful in the interpretation of real sunphotometer data; the fine mode size distribution often approximates a LTPSD while departures from this behavior become more readily understood once one understands the first order optics. The near dependency of the fine mode optical parameters on ρ eff,f was also exploited to obtain an explicit expression for ρ eff,f as a function of α f and α f ′. The relationships were applied to a representative case study to demonstrate their general applicability and then to the specific case of the July 2002 Québec smoke event. A number of illustrations were given where the coherency of the derived relations indicated that the LTPSD concept was often a good approximation to reality. The analysis of the Québec‐smoke extinction data showed the existence of a weak but systematic dependence of the Angstrom exponents on smoke trajectory time and by inference a steady growth in particle size with time. The variation of r eff,f (derived from AERONET inversions) was however observed to be inconsistent with this dependence unless one redefined this parameter in terms of the clearly delineated peak of the asymmetric fine mode particle size distribution (PSD). This definition led to a re‐computed temporal rate of increase in r eff,f which was coherent with the variation of the Angstrom parameters and which was coherent with a simple coagulative model based on conservation of volume. It was demonstrated that trajectory time was essentially a proxy variable for r eff,f and more fundamentally ρ eff,f (as predicted by the LTPSD relations). A similar proxy argument could be applied to the dependence of the Angstrom exponent on optical depth but such arguments are tempered by the relative variations of fine‐mode abundance (A f ) and particle size (by the value of the parameter γ = dlogA f /dlogr eff,f ).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.306
Teacher spread0.286 · 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 teacher head, not a consensus.

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

Citations39
Published2005
Admission routes3
Has abstractyes

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