Canadian Fire Weather System - WRF/NOA
Bibliographic record
Abstract
The Canadian FWI System (Van Wagner, 1987) is a sub-system of the Canadian Fire Danger Rating System (Stocks et al., 1989), comprised of five components that consider the effects of fuel moisture and wind on fire behavior. The first three components, called fuel moisture codes, are numeric ratings of (1) the moisture content of surface litter and other fine fuels (fine fuel moisture code; FFMC), (2) the average moisture content of loosely compacted organic material (duff moisture code; DMC), and (3) the average moisture content of deep layers of organic material (drought code; DC). The remaining two components are related to fire behavior and spread: (1) the initial spread index (ISI), which represents the rate of spread, and (2) the build-up index (BUI), which represents the potential fuel availability. The above five parameters are finally combined for computing the fire weather index (hereafter referred to as the FWI), which represents the intensity of a spreading fire per unit length of fire front and is used as an indicator of fire danger. Computation of the Canadian Fire Weather System components was carried out using 12 UTC meteorological data extracted from high-resolution (~12 km) WRF simulations, focussing on the Euro-Mediterranean region. These data include the 24 h accumulated precipitation (mm), 2 m air temperature (oC) and relative humidity (%), and 10 m wind speed (km h-1). It should be noted that normally, FWI is computed using meteorological data at 12 local time. The use of the 12 UTC data in our study is dictated by the fact that the Euro-Mediterranean encompasses different time zones (e.g. Bedia et al., 2012, 2018; Herrera et al., 2013). Details: File format: netcdf4 Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326) Longitude range: [-9.91, +36.4] Latitude range: [+32.1, +48.93] Temporal resolution: 1 day (at 12 UTC) Spatial resolution: 0.12 degrees (~12 Km) Spatial coverage: Euro-Mediterranean Time span: May 1 to September 30, for the years 1987-2016 Stream: Regional climate simulations (driven by the WRF model)
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.069 | 0.033 |
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".