On the Radiative Impact of Biomass-Burning Aerosols in the Arctic: The August 2017 Case Study
Bibliographic record
Abstract
Boreal fires have increased during the last years and are projected to become more intense and frequent as a consequence of climate change. Wildfires produce a wide range of effects on the Arctic climate and ecosystem, and understanding these effects is crucial for predicting the future evolution of the Arctic region. This study focuses on the impact of the long-range transport of biomass-burning aerosol into the atmosphere and the corresponding radiative perturbation in the shortwave frequency range. As a case study, we investigate an intense biomass-burning (BB) event which took place in summer 2017 in Canada and subsequent northeastward transport of gases and particles in the plume leading to exceptionally high values (0.86) of Aerosol Optical Depth (AOD) at 500 nm measured in northwestern Greenland on 21 August 2017. This work characterizes the BB plume measured at the Thule High Arctic Atmospheric Observatory (THAAO; 76.53∘N, 68.74∘W) in August 2017 by assessing the associated shortwave aerosol direct radiative impact over the THAAO and extending this evaluation over the broader region (60∘N–80∘N, 110∘W–0∘E). The radiative transfer simulations with MODTRAN6.0 estimated an aerosol heating rate of up to 0.5 K/day in the upper aerosol layer (8–12 km). The direct aerosol radiative effect (ARE) vertical profile shows a maximum negative value of −45.4 Wm−2 for a 78∘ solar zenith angle above THAAO at 3 km altitude. A cumulative surface ARE of −127.5 TW is estimated to have occurred on 21 August 2017 over a portion (∼3.1×106 km2) of the considered domain (60∘N–80∘N, 110∘W–0∘E). ARE regional mean daily values over the same portion of the domain vary between −65 and −25 Wm−2. Although this is a limited temporal event, this effect can have significant influence on the Arctic radiative budget, especially in the anticipated scenario of increasing wildfires.
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 | 0.001 | 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 | 0.000 | 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".