Numerical Simulation of the Dynamics and Microphysics of Prescribed Forest Burns
Bibliographic record
Abstract
The OCTET modeling system has been designed to simulate the atmospheric dynamics, microphysics and scavenging above hypothetical large city fires with energy release rates on the order of 10-100 kW/m2 over areas of tens to hundreds of square kilometers. It simulates the three-dimensional, moist, nonhydrostatic circulations of natural and fire-driven convective clouds and the microphysical interactions among hydrometeors and aerosols in these clouds. In order to validate the model, simulations of planned forest and slash burns have been performed and results compared with available observations. In this paper the authors briefly describe the OCTET modeling system and present simulations for two planned forest burns in Ontario, Canada. The Hardiman fire was fairly well observed and includes microphysical data taken from aircraft; it involved only liquid hydrometeors. The Battersby fire penetrated well above the freezing level, and there is evidence of frozen hydrometeors. Comparisons of the numerical results with the observations of cloud dynamics and microphysics confirm the ability of the model to simulate these clouds and suggest that the model can provide insight into the dynamical, microphysical and scavenging processes that occur in clouds.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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".