Behaviour of fire weather indices in the 2009–10 New Zealand wildland fire season
Bibliographic record
Abstract
The Weather Research and Forecasting mesoscale atmospheric model was used to investigate fire weather conditions during the 2009–10 New Zealand wildland fire season. The analysis considered New Zealand's version of the Fire Weather Index used in the Canadian Forest Fire Danger Rating System, the Haines Index (HI) and the Continuous Haines Index (CHI). This represents the first investigation in New Zealand of the HI and CHI, which rate the potential for extreme fire behaviour or large fire growth based on the lower tropospheric atmospheric stability and humidity. The wildland fire activity during the 2009–10 fire season was typical of New Zealand, and there was considerable spatial and temporal variability in the fire weather conditions. The most frequent severe fire weather conditions as quantified by the fire weather indices occurred to the east of the dividing mountain ranges in both the North Island and South Island, and were associated with the hot, dry and windy north-westerly foehn winds that commonly affect New Zealand. The 36 wildland fires greater in area than 5 ha during the 2009–10 fire season occurred under a range of fire weather conditions, and no correlation was found between the wildland fire size and each individual weather variable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".