A case study of pyro-convection using transport model and remote sensing data
Bibliographic record
Abstract
Abstract. Summer 2004 saw severe forest fires in Alaska and the Yukon Territory that were mostly triggered by lightning strikes. The area burned (>2.7×106 ha) in the year 2004 was the highest on record to date in Alaska. Pollutant emissions from the fires lead to violation of federal standards for air quality in Fairbanks. This paper studies deep convection events that occurred in the burning regions at the end of June 2004. The convection was likely enhanced by the strong forest fire activity (so-called pyro-convection) and penetrated into the lower stratosphere, up to about 3 km above the tropopause. Emissions from the fires did not only perturb the UT/LS locally, but also regionally. POAM data at the approximate location of Edmonton (53.5° N, 113.5° W) show that the UT/LS aerosol extinction was enhanced by a factor of 4 relative to unperturbed conditions. Simulations with the particle dispersion model FLEXPART with the deep convective transport scheme turned on showed transport of forest fire emissions into the stratosphere, in qualitatively good agreement with the enhancements seen in the POAM data. A corresponding simulation with the deep convection scheme turned off did not result in such deep vertical transport. Lidar measurements at Wisconsin on 30 June also show the presence of substantial aerosol loading in the UT/LS, up to about 13 km. In fact, the FLEXPART results suggest that this aerosol plume originated from the Yukon Territory on 25 June.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".