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Record W2972880786

Fire weather of a Canterbury Northwester on 6 February 2011 in South Island, New Zealand

2013· article· en· W2972880786 on OpenAlexaboutno aff
Colin C. Simpson, Andrew Sturman, Payman Zawar-Reza, H. Grant Pearce

Bibliographic record

VenueUniversity of Canterbury Research Repository (University of Canterbury) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersBushfire Cooperative Research CentreUniversity of Canterbury
KeywordsMeteorologyGeographyClimatologyHistoryGeology
DOInot available

Abstract

fetched live from OpenAlex

Foehn winds, known locally as the "Canterbury Northwester", occurred on 6 February 2011
\nand were associated with extreme fire weather in the lee of the Southern Alps and across
\nthe eastern South Island of New Zealand. A peak air temperature of 40.7˚C was recorded at
\nTimaru, which compares with the national record of 42.4˚C set at Rangiora in 1973 during
\nanother Northwester. The primary objective of this study was to investigate the fire weather
\nand the synoptic and mesoscale atmospheric processes associated with the Northwester.
\nThis was achieved through analysis of weather station data and a high-resolution Weather
\nResearch and Forecasting (WRF) model simulation. The fire weather was assessed through
\nconsideration of observable weather variables and New Zealand's version of the Fire
\nWeather Index (FWI) in the Canadian Forest Fire Danger Rating System. The WRF model
\nresults suggest that internal gravity waves were present in the lee of the Southern Alps and
\nconsiderably affected fire weather across the eastern South Island. The FWI was recorded
\nat extreme values, due to a combination of high air temperatures and wind speeds, and low
\nrelative humidity. This study provides a better understanding of the mesoscale atmospheric
\ndynamics and fire weather associated with the Canterbury Northwester.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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Same venueUniversity of Canterbury Research Repository (University of Canterbury)Same topicFire effects on ecosystemsFrench-language works237,207