Bibliographic record
Abstract
Abstract. Polarization properties of the fluorescence induced by polarized laser radiation are widely considered in laboratory studies. In lidar observations, however, only the total scattered power of fluorescence is analyzed. In this paper we present results obtained with a modified Mie-Raman-Fluorescence lidar operated at the ATOLL observatory, Laboratoire d’Optique Atmosphérique, University of Lille, France, allowing to measure depolarization ratios of fluorescence at 466 nm (δF) and of water vapor Raman backscatter. Measurements were performed in May–June 2023 during Alberta forest fires season when smoke plumes were almost continuously transported over the Atlantic Ocean towards Europe. During the same period, smoke plumes from the same sources were also detected and analyzed in Moscow, at General Physics Institute (GPI), with a 5-channel fluorescence lidar able to measure fluorescence backscattering at 438, 472, 513, 560 and 614 nm. Results demonstrate that, inside the boundary layer (BL), urban aerosol fluorescence is maximal at 438 nm, then it gradually decreases with wavelength. Results also show that the maximum of the smoke fluorescence spectrum shifted towards longer wavelengths. The smoke layers observed within 4–6 km present a maximum of fluorescence at 513 nm while, in the upper troposphere (UT), the maximum shifts to 560 nm. Regarding fluorescence depolarization, its value typically varies inside the 45–55 % range, however several smoke plume layers detected above 10 km were characterized by a δF increasing up to 70 %. Inside the BL, the fluorescence depolarization ratio was higher than that of smoke and varied inside the 50–70 % range. Moreover, in the BL, δF appears to vary with atmospheric relative humidity (RH) and, in contrast to the elastic scattering, fluorescence depolarization increases with RH. The depolarization ratio of the water vapor Raman backscattering is shown to be quite low (2±0.5 %) in the absence of fluorescence, because the narrowband interference filter in the water vapor channel selects only strongest vibrational lines of the Raman spectrum. As a result, depolarization of the water vapor Raman backscattering is sensitive to the presence of strongly depolarized fluorescence backscattering. The fluorescence contamination into the water vapor Raman channel can be calculated from the water vapor Raman depolarization ratio with the only assumption that δF remains constant within the 408–466 nm range.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.025 | 0.013 |
| Insufficient payload (model declined to judge) | 0.137 | 0.124 |
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".