MétaCan
Menu
Back to cohort
Record W2136953437 · doi:10.1080/07055900.2014.1000260

The Canadian Meteorological Centre's Atmospheric Transport and Dispersion Modelling Suite

2015· article· en· W2136953437 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueATMOSPHERE-OCEAN · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of AlbertaEnvironment and Climate Change Canada
FundersPacific Northwest National LaboratoryAtomic Energy of Canada Limited
KeywordsMeteorologyDispersion (optics)Environmental scienceSuiteLagrangianMode (computer interface)Atmospheric dispersion modelingGaussianTurbulent diffusionStochastic modellingTurbulenceGeographyPhysicsComputer scienceMathematicsStatisticsApplied mathematicsAir pollution

Abstract

fetched live from OpenAlex

This paper describes the integrated suite of Lagrangian transport and dispersion models in operation at the Canadian Meteorological Centre.These models have been in use for several years and are applied to many types of environmental emergencies covering spatial scales from the very local to the global.The Modle Lagrangien Courte Distance (MLCD) is used for atmospheric spills of the order of a few kilometres.The Modle Lagrangien de dispersion de particules d'ordre 1 (MLDP1) is normally used for events affecting areas less than 100 km; Modle Lagrangien dispersion de particules d'ordre zro (MLDP0) is used for events of continental and global consequences.The Modle Lagrangien dispersion de particules mode mixte (MLDPmm) alternates between first-order and zeroth-order depending on criteria specified by the user.The theoretical bases of the models are presented, and the main algorithms used in their implementation are discussed.Modelling of the diffusion processes is based on a stochastic differential equation with the assumption of quasi-stationary Gaussian turbulence, locally homogeneous in the horizontal.The practical aspects of the operational implementation are also described.Using these models, results from simulations of real cases on scales ranging from the very local, to a few kilometres, to regional (approximately 100 km) to continental (approximately 1000 km) and to global (approximately 10,000 km) are compared and validated with available observational data.RSUM Cet article dcrit l'ensemble des modles lagrangiens de transport et dispersion en exploitation au Centre mtorologique canadien.Ces modles sont employs depuis plusieurs annes pour rpondre diffrents types d'urgences environnementales se produisant de l'chelle trs locale jusqu' l'chelle globale.Le MLCD (Modle Lagrangien courte distance) est utilis lors de dversements atmosphriques s'tendant sur quelques kilomtres.Le MLDP1 (Modle Lagrangien de dispersion de particules d'ordre 1) est habituellement utilis pour des vnements pouvant affecter des rgions de dimensions infrieures 100 km.Le MLDP0 (Modle Lagrangien de dispersion de particules d'ordre 0) est utilis pour des vnements ayant des consquences continentales ou globales.Dans le MLDPmm (Modle Lagrangien de dispersion de particules mode mixte), il y a alternance entre l'ordre zro et l'ordre 1, selon des critres spcifis par l'utilisateur.Les bases thoriques de ces modles sont prsentes, et les principaux algorithmes employs pour leur application sont examins.La diffusion y est modlise l'aide d'une quation diffrentielle stochastique qui suppose une turbulence quasistationnaire, gaussienne, et localement homogne dans l'horizontale.Les aspects pratiques de l'implmentation oprationnelle sont dcrits.Des rsultats de simulations pour des incidents rels ayant des chelles trs locales, quelques kilomtres, rgionales, 100 km, continentales, 1000 km, et globales, 10000 km, sont montrs et compars aux observations disponibles.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.935

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 studies0.0010.000
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 head0.014
GPT teacher head0.195
Teacher spread0.181 · 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