Global retrieval of columnar aerosol single scattering albedo from space‐based observations
Bibliographic record
Abstract
We retrieve the global distribution of columnar single scattering albedo (ω0) by taking advantage of the high sensitivity of satellite measurements at ultraviolet channels by the Total Ozone Mapping Spectrometer (TOMS) to both aerosol optical depth and ω0 and the high sensitivity of satellite measurements at visible channels by the Moderate Resolution Imaging Spectroradiometer (MODIS) to aerosol optical depth. A radiative transfer model (LIDORT) is used to calculate the local ω0 that reproduces the TOMS aerosol index, when constrained by MODIS aerosol optical depth and by relative vertical profiles from a global chemical transport model (GEOS‐CHEM). The simulated aerosol profiles are evaluated with lidar measurements of aerosol extinction. The retrieved ω0 at 360 nm is near 1 over the remote ocean, in contrast with values of 0.75 to 0.9 over regions dominated by biomass burning and mineral dust aerosol. The retrieval uncertainty is 15%. We validate our retrieval with measurements from the Aerosol Robotic Network (AERONET); the correlation coefficient, slope, and intercept are 0.75, 0.99, and 0.02 respectively.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".