Californian forest fire plumes over Southwestern British Columbia: lidar, sunphotometry, and mountaintop chemistry observations
Bibliographic record
Abstract
Abstract. Forest fires in Northern California and Oregon were responsible for two significant regional scale aerosol transport events observed in southern British Columbia during summer 2008. A combination of ground based (CORALNet) and satellite (CALIPSO) lidar, sunphotometry and high altitude chemistry observations permitted unprecedented characterization of forest fire plume height and mixing as well as description of optical properties and physicochemistry of the aerosol. In southwestern BC, lidar observations show the smoke to be mixed through a layer extending to 5–6 km a.g.l. where the aerosol was confined by an elevated inversion in both cases. Depolarization ratios for a trans-Pacific dust event (providing a basis for comparison) and the two smoke events were consistent with observations of dust and smoke events elsewhere and permit discrimination of aerosol events in the region. Based on sunphotometry, the Aerosol Optical Thicknesses (AOT) reached maxima of ~0.7 and ~0.4 for the two events respectively. Dubovik-retrieval values of reff, f during both the June/July and August events varied between about 0.13 and 0.15 μm and confirm the dominance of accumulation mode size particles in the forest fire plumes. Both Whistler Peak and Mount Bachelor Observatory data show that smoke events are accompanied by elevated CO and O3 concentrations as well as elevated K+/SO4 ratios. In addition to documenting the meteorology and physic-chemical characteristics of two regional scale biomass burning plumes, this study demonstrates the positive analytical synergies arising from the suite of measurements now in place in the Pacific Northwest, and complemented by satellite borne instruments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".