Optical Properties of North Atlantic Aerosols Through a compact dual-wavelength depolarization Lidar Observations
Bibliographic record
Abstract
Abstract. We present a characterization of the optical properties of different aerosol types based on data collected using a compact dual-wavelength depolarization elastic lidar (532 and 808 nm, CIMEL CE376). We evaluate the vertical distribution and temporal evolution of a variety of aerosols observed in the subtropical North Atlantic region, covering from Saharan dust outbreaks and volcanic aerosols to fresh and aged wildfires, observed between August 2021 and August 2023, using a modified two-wavelength Klett inversion method to derive the aerosol backscatter and extinction coefficients from CE376 lidar observations. We assessed the performance of the CE376 lidar during an intercomparison campaign with an MPL-4B lidar (MPLNET) while collocated at the facilities of the Izaña Atmospheric Research Centre (Canary Islands, Spain). Both instruments depicted the vertical aerosol structure similarly. The main differences were attributed to errors arising from the determination of the overlap function and the depolarization calibration in each instrument and the larger effect of the solar background on the CE376 system during daylight. Absolute differences in the volume depolarization ratio (δv) were 0.3 % reduced to 0.2 % when only nighttime data was used. The measurements of particle linear depolarization (δP), extinction Ångström exponent (EAE (532/808)) and attenuated colour ratio (ACR (808-532)), provided by the combination of the two channels of the CE376, allow us to describe the composition and size of the studied aerosols. Fresh Saharan dust particles were the largest particles found in this study with non-spherical morphology and traveling in a well-mixed layer, exhibiting the lowest EAE (532/808) and highest ACR (808-532) and δP (532) > 0.15. The smaller particles with quasi homogeneous morphology were attributed to sulphate aerosol from the initial stage of the Cumbre Vieja volcano eruption and aged Canadian wildfires traveling across the Atlantic, showing the lowest δP (< 0.08) and the highest EAE (532/808) (>1). Middle values of these retrieved parameters were associated with the heterogenous mixture of ash, soot, and charred vegetation from fresh local forest wildfires. The retrieved properties demonstrate the excellent performance of the CE376 micro-lidar as a tool for continuous monitoring and characterisation of the temporal and vertical distribution of atmospheric aerosols.
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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 | 0.000 |
| 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 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".