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Record W2108334686 · doi:10.1080/07055900.2014.902803

Evidence from the Historical Record to Support Projection of Future Wind Regimes: An Application to Canada

2014· article· en· W2108334686 on OpenAlexaffvenueabout
Chad Shouquan Cheng

Bibliographic record

VenueATMOSPHERE-OCEAN · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsAnomaly (physics)ClimatologyEnvironmental scienceWind speedClimate changeMeteorologyGeographyGeologyOceanographyPhysics

Abstract

fetched live from OpenAlex

In the field of climate change impact analysis, bidirectional changes in projections of future wind regimes varying among studies, locations, and models have been described in the literature, which is understandable from a global perspective. However, we should attempt to find evidence in the historical record to support these projections. This paper attempts to address this issue by analyzing historical wind gust observations for up to 57 years (1953–2009) over Canada. Two wind gust analysis techniques were used: the speed of daily wind gust events ≥50 km h−1 was compared with (1) the climatological daily temperature anomaly and (2) the climatological daily sea level air pressure anomaly. In addition, the frequency of daily wind gust events ≥90 km h−1 was compared with both daily temperature and pressure anomalies. The results indicate that during the past five decades gust wind speed over Canada increased significantly as the daily temperature anomaly increased and the daily pressure anomaly decreased. About 50–60% of daily wind gust events ≥90 km h−1 occurred with positive daily temperature anomalies and negative daily pressure anomalies. One major conclusion is that the methods used in and results derived from this study might be applied to climate change impact analysis to support projections of future wind regimes.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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

Citations12
Published2014
Admission routes3
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicClimate variability and modelsFrench-language works237,207