Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe – Part 1: AERONET, MODIS and lidar observations
Bibliographic record
Abstract
Abstract. Light extinction coefficients of 500 Mm−1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed with lidar in the stratosphere over Leipzig, Germany, on 22 August 2017. A pronounced smoke layer extended from 14–16 km height and was 3–4 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after injection into the lower stratosphere caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) was close to 1.0 at 532 nm over Leipzig during the noon hours. We present detailed observations of this record-breaking smoke event in a series of two articles. In part 1, we provide an overview of Aerosol Robotic Network (AERONET) sun photometer observations and Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of AOT and show lidar measurements documenting the aerosol layering and the very high particle extinction coefficients. In part 2 (Haarig et al., 2018), observations with three polarization/Raman lidars are presented, performed at Leipzig after sunset on 22 August to elucidate the optical and microphysical properties of the aged smoke. As shown in this part 1, smoke particles were found throughout the free troposphere (532 nm AOT of 0.3). A pronounced 2-km thick stratospheric smoke layer occurred from 14–16 km height (AOT of 0.6). AERONET and lidar observations indicate peak mass concentrations of 70–100 μg m−3 in the stratosphere around noon and a well-defined (accumulation mode) smoke particle size distribution characterized by a large effective radius of 0.3–0.4 μm and the absence of a particle coarse mode.
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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".