MétaCan
Menu
Back to cohort
Record W2148536828 · doi:10.1002/joc.851

Linking global circulation model synoptics and precipitation for western North America

2002· article· en· W2148536828 on OpenAlexaffabout
Suzan Lapp, James Byrne, S. W. Kienzle, Ivan Townshend

Bibliographic record

VenueInternational Journal of Climatology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsClimatologyDownscalingPrecipitationGeopotential heightEnvironmental scienceGeopotentialAtmospheric circulationGeneral Circulation ModelClimate modelClimate changeMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Synoptic downscaling from global circulation models (GCMs) has been widely used to develop local and regional‐scale future precipitation scenarios under global warming. This paper presents an analysis of the linkages between the Canadian Centre for Climate Modelling and Analysis first version of the Canadian Global Coupled Model (CCCma CGCM1) 2000 model output and local/regional precipitation time series. The GCM 500 hPa geopotential heights were visually classified for synoptic patterns using a geographical information system. The pattern frequencies were statistically compared with historical data from Changnon et al. (1993. Monthly Weather Review 121 : 633–647) for the winter period 1961–85. The CGCM1 synoptic frequencies compare favourably with the historical data, and they represent a substantial improvement over the 1992 Canadian Climate Centre Global Circulation Model synoptic climatology output. The CGCM1 output was used to forecast future winter precipitation scenarios for five geographically diverse climate stations in western North America. Copyright © 2002 Royal Meteorological Society.

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 score0.721
Threshold uncertainty score0.215

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 head0.033
GPT teacher head0.290
Teacher spread0.257 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of ClimatologySame topicClimate variability and modelsFrench-language works237,207