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Record W2051899641 · doi:10.5194/acp-15-6721-2015

The POLARCAT Model Intercomparison Project (POLMIP): overview and evaluation with observations

2015· article· en· W2051899641 on OpenAlexaffabout
L. K. Emmons, S. R. Arnold, S. A. Monks, Vincent Huijnen, Simone Tilmes, Kathy S. Law, Jennie L. Thomas, Jean‐Christophe Raut, I. Bouarar, Solène Turquéty, Y. Long, B. N. Duncan, Stephen D. Steenrod, Sarah A. Strode, Johannes Flemming, Jingqiu Mao, Joakim Langner, Anne M. Thompson, D. W. Tarasick, Eric C. Apel, D. R. Blake, R. C. Cohen, Jack E. Dibb, Glenn S. Diskin, Alan Fried, Samuel R. Hall, L. G. Huey, A. J. Weinheimer, Armin Wisthaler, Tomáš Mikoviny, J. B. Nowak, Jeff Peischl, J. M. Roberts, Thomas B. Ryerson, C. Warneke, Detlev Helmig

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 OfficeNatural Environment Research CouncilScience Mission DirectorateGoddard Space Flight CenterOffice of ScienceGrand Équipement National De Calcul IntensifCentre National de la Recherche ScientifiqueU.S. Department of EnergyCalifornia Institute of TechnologyEuropean CommissionNational Oceanic and Atmospheric AdministrationSight Research UKAgence Nationale de la RechercheNaturvårdsverketNational Aeronautics and Space AdministrationBundesministerium für Verkehr, Innovation und TechnologieCentre National d’Etudes SpatialesNational Center for Atmospheric ResearchNational Science Foundation
KeywordsEnvironmental scienceAtmospheric sciencesChemical transport modelClimatologyOzone depletionArcticMeteorologyOzoneStratosphereGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract. A model intercomparison activity was inspired by the large suite of observations of atmospheric composition made during the International Polar Year (2008) in the Arctic. Nine global and two regional chemical transport models participated in this intercomparison and performed simulations for 2008 using a common emissions inventory to assess the differences in model chemistry and transport schemes. This paper summarizes the models and compares their simulations of ozone and its precursors and presents an evaluation of the simulations using a variety of surface, balloon, aircraft and satellite observations. Each type of measurement has some limitations in spatial or temporal coverage or in composition, but together they assist in quantifying the limitations of the models in the Arctic and surrounding regions. Despite using the same emissions, large differences are seen among the models. The cloud fields and photolysis rates are shown to vary greatly among the models, indicating one source of the differences in the simulated chemical species. The largest differences among models, and between models and observations, are in NOy partitioning (PAN vs. HNO3) and in oxygenated volatile organic compounds (VOCs) such as acetaldehyde and acetone. Comparisons to surface site measurements of ethane and propane indicate that the emissions of these species are significantly underestimated. Satellite observations of NO2 from the OMI (Ozone Monitoring Instrument) have been used to evaluate the models over source regions, indicating anthropogenic emissions are underestimated in East Asia, but fire emissions are generally overestimated. The emission factors for wildfires in Canada are evaluated using the correlations of VOCs to CO in the model output in comparison to enhancement factors derived from aircraft observations, showing reasonable agreement for methanol and acetaldehyde but underestimate ethanol, propane and acetone, while overestimating ethane emission factors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.073
GPT teacher head0.273
Teacher spread0.200 · 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.

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

Citations104
Published2015
Admission routes2
Has abstractyes

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