Direct Measurements and Implications of the Aerosol Asymmetry Parameter in Wildfire Smoke During FIREX‐AQ
Bibliographic record
Abstract
Abstract We present direct measurements of the asymmetry parameter (g) from biomass burning aerosol at two wavelengths using the Laser Imaging Nephelometer. We compare the measurements with Mie theory calculations based on optically measured size distributions and with g values derived from hemispheric backscatter (b) measurements using both an integrating and an imaging nephelometer. During the FIREX‐AQ field mission, we measured the optical and microphysical properties of smoke plumes that had been emitted between 0.5 and 8.5 hr earlier. We find that the measured g can only be reproduced from particle size distribution measurements using a higher refractive index than is typically retrieved from remote measurements and assumed in some models. Retrievals performed using the GRASP algorithm suggest the refractive index is wavelength‐dependent with n = 1.55 ± 0.03 at λ = 660 nm and (1.63 ± 0.04) at λ = 405 nm. Using a simple radiative transfer equation, we show that the instantaneous aerosol cooling of the planet by fresh smoke is increased by 20% when evaluated using the measured g values instead of assuming n = 1.52. Besides improving model representations of radiative cooling by fresh smoke, using a more accurate aerosol optical model can improve retrievals of aerosol microphysical properties from remote sensing techniques. Better retrievals will provide a more accurate constraint on the emissions inventories used in global and regional models. This will ultimately reduce the uncertainty in radiative forcing associated with the increasing frequency and magnitude of wildfires.
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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 | 0.001 |
| 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 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".