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Record W958285566 · doi:10.4401/ag-6626

WRF-Chem modeling of sulfur dioxide emissions from the 2008 Kasatochi Volcano

2015· article· en· W958285566 on OpenAlexaboutno aff
Sean Egan, Martin Stuefer, P. W. Webley, C. F. Cahill

Bibliographic record

VenueAnnals of Geophysics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
Fundersnot available
KeywordsPlumeVolcanoWeather Research and Forecasting ModelSulfur dioxideAtmospheric sciencesOzoneEnvironmental scienceAtmosphere (unit)MeteorologyOzone Monitoring InstrumentAtmospheric chemistryAtmospheric dispersion modelingClimatologyAir pollutionChemistryGeologyGeography

Abstract

fetched live from OpenAlex

We simulate the dispersion and chemical evolution of the sulfur dioxide (SO2) plume following the eruption of Kasatochi Volcano in Alaska, USA, on August 7th, 2008 with the Weather Research Forecasting with Chemistry (WRF-Chem) model. The model was initialized with the observed three distinct plumes, which were characterized by a total estimated SO2 mass of 0.5 to 2.7 Tg. WRF-Chem modeled output was compared to remote sensing retrievals from the Ozone Monitoring Instrument (OMI), and the modeled plumes agreed well in shape and location with the OMI retrievals. The calculated SO2 column densities showed comparable Dobson Unit values with higher densities especially in the center of the distal plume over northern Canada. We concluded from our analysis that WRF-Chem derived a 9.1-day lifetime of the SO2 when initialized with a 12km eruption height. Sensitivity tests with varying eruption plume heights revealed significantly in- creased lifetimes of SO2 up to 17.1 days for higher plumes.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.074
GPT teacher head0.261
Teacher spread0.187 · 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 designSimulation or modeling
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

Citations3
Published2015
Admission routes1
Has abstractyes

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