Transport of the 2017 Canadian wildfire plume to the tropics via the Asian monsoon circulation
Bibliographic record
Abstract
We show that a fire plume injected into the lower stratosphere at high northern latitudes during the Canadian wildfire event in August 2017 partly reached the tropics. The transport to the tropics was mediated by the anticyclonic flow of the Asian monsoon circulation. The fire plume reached the Asian monsoon area in late August/early September, when the Asian monsoon anticyclone (AMA) was still in place. While there is no evidence of mixing into the center of the AMA, we show that a substantial part of the fire plume is entrained into the anticyclonic flow at the AMA edge and is transported from the extratropics to the tropics, and possibly the Southern Hemisphere particularly following the north–south flow on the eastern side of the AMA. In the tropics the fire plume is lifted by ∼5 km in 7 months. Inside the AMA we find evidence of the Asian tropopause aerosol layer (ATAL) in August, doubling background aerosol conditions with a calculated top of the atmosphere shortwave radiative forcing of −0.05 W m −2 . The regional climate impact of the fire signal in the wider Asian monsoon area in September exceeds the impact of the ATAL by a factor of 2–4 and compares to that of a plume coming from an advected moderate volcanic eruption. The stratospheric, trans-continental transport of this plume to the tropics and the related regional climate impact point to the importance of long-range dynamical interconnections of pollution sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".