Microwave Limb Sounder (MLS) observations of biomass burning products in the stratosphere from Canadian forest fires in August 2017
Bibliographic record
Abstract
Forest fires in British Columbia in August 2017 caused a pyrocumulonimbus event that injected a polluted air mass into the lower stratosphere. The Microwave Limb Sounder (MLS) on the Aura satellite first observed the polluted air mass on 14 August 2017 and continued to observe it for 60 d (100 d in water vapour). We estimate the mass of CO injected into the stratosphere to be 2400 Gg. Events in which a fire injects its burning products directly into the stratosphere are rare: this is the third of four such events in the 16 years since the launch of Aura, the second largest of the four events, and the only one in the Northern Hemisphere. The other three events occurred in Australia in December 2006, February 2009 and from December 2019 to January 2020. Unlike the 2006 and 2009 events, but like the 2019–2020 event, the polluted air mass described here had a clearly elevated water vapour content: between 2.5 and 5 times greater than that in the surrounding atmosphere. We describe the evolution of the polluted air mass, showing that it rose to an altitude of about 24 km (31 hPa) and divided into several identifiable parts. In addition to CO and H 2 O, we observe enhanced amounts of HCN, CH 3 CN, CH 3 Cl and CH 3 OH with mixing ratios in the range to be expected from a variety of measurements in other biomass burning plumes. We use back trajectories and plume-dispersion modelling to demonstrate that the pollutants observed by MLS originated in the British Columbia fires, the likeliest source being at 53.2 ∘ N, 121.8 ∘ W at 05:20 UTC on 13 August 2017.
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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 | 0.002 | 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".