MétaCan
Menu
Back to cohort

Regional Climate Change: Trend Analysis of Temperature and Precipitation Series at Selected Canadian Sites

2000· article· en· W1974484507 on OpenAlexaffvenueabout
J. Stephen Clark, Emmanuel K. Yiridoe, Nigel D. Burns, Tess Astatkie

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsNova Scotia Department of Agriculture
Fundersnot available
KeywordsClimate changePrecipitationClimatologyEnvironmental scienceGlobal warmingGeographyForestryMeteorologyEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Global climate change does not necessarily imply that temperature or precipitation is increasing at specific locations. The hypothesis of increasing temperature and precipitation trends associated with global climate change is tested using actual annual temperature and precipitation data for nine selected weather stations, spatially distributed across Canada. Vogelsang's (1998) partial sum and Woodward et al's (1997) bootstrap methods are used for testing for trend. Both methods suggest no warming in the Canadian temperature series except for Toronto, Ontario, which had significant increase over time, along with Moncton, New Brunswick, and Indian Head, Saskatchewan, which had marginal increases. There is no evidence of increasing trend in precipitation except for Moncton, New Brunswick, which had a significantly increasing trend. Thus, public policies designed to address the regional effects of climate change need to be adapted for a particular ecological zone, based on knowledge of the climate trends for that region, rather than on general global climate change patterns. Les changements climatiques à l'échelle planétaire ne signifient pas nécessairement que la température et les précipitations sont en augmentation dans des emplacements donnés. Nous avons testé I'hypothèse d'une assoviation de la tendance à la hausse de la température et des précipitations avec les changements climatiques planétaires à partir des données réelles de température et de précipitations obtenues à 9 stations d'observation climatique réparties dans les diverses régions du Canada. Nous utilisons, pour cefaire, la méthode des sommes partielles de Vogelsang (1998) et celle de rééchantillonnage bootstrap de Woodward et al (1997). Les deux méthodes ne révèlent aucun réchauffement de la température dans les séries chronologiques, sauf pour Toronto, en Ontario, où l'on constate une hausse significative en fonction du temps, ainsi que pour Moncton au Nouveau‐Brunswick et Indian Head en Saskatchewan qui marquent de très légères augmentations. Rien n'indique une tendance à la hausse des précipitations, sauf à Moncton où se dessine une tendance significative dans ce sens. Les programmes publics destinés à faire face aux effets régionaux du changement climatique doivent donc être adaptés à chaque zone écologique particulière, à partir d”observations faites dans la région même, plutôt que de la configuration du changement climatique à l'échelle planétaire.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.011
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.170
Teacher spread0.150 · 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 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

Citations21
Published2000
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomieSame topicClimate variability and modelsFrench-language works237,207