An Aerosol Model of the Marine and Coastal Atmospheric Surface Layer
Bibliographic record
Abstract
We present a microphysical model for the surface layer marine and coastal atmospheric aerosols that is based on long-term observations of size distributions for 0.01–100 µm particles. The fundamental feature of the model is a parameterization of amplitudes and widths for aerosol modes of the aerosol size distribution function (ASDF) as functions of fetch and wind speed. The shape of ASDF and its dependence on meteorological parameters, height above sea level (H), fetch (X), wind speed (U) and relative humidity (RH), are investigated. At present, the model covers the ranges H = 0–25 m, U = 3–18 km s−1, X ≤ 120 km and RH = 40–98%. The latest version of the Marine Aerosol Extinction Profiles model (MaexPro) is described and applied to the computation and analysis of the spectral profiles of aerosol extinction coefficients α(λ) in the wavelength band λ = 0.2–12 µm. MaexPro is based on the aforementioned aerosol model assuming spherically shaped aerosol particles and the well-known Mie theory. The spectral profiles of α(λ) calculated by MaexPro are in good agreement with observational data and the numerical results obtained from the Navy Aerosol Model (NAM) and the Advanced Navy Aerosol Model (ANAM). Moreover, MaexPro was found to be an accurate and reliable tool for investigating the optical properties 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".