Development and validation of a size-resolved particle dry deposition scheme for applications in aerosol transport models
Bibliographic record
Abstract
Abstract. A size-resolved particle dry deposition scheme is developed, which has been designed for inclusion in large-scale air quality and climate models, where the size distribution and fate of the atmospheric aerosol is of concern. The "resistance" structure is similar to what is proposed by Zhang et al. (2001, 2003), while a new "surface" deposition velocity (or surface resistance) is derived by simplification of a one-dimensional aerosol transport model (Petroff et al., 2008b, 2009). Collection efficiencies are given for the 26 Land Use Categories that decribe the earth surface. Validation of this model with existing measurements is performed on desert, grass, coniferous forest and liquid water surfaces. A comparison of this model with measurements on snow and ice is also given. Even though a qualitative agreement is reached, further size-segegated measurements are needed in order to confirm the model accuracy on this surface. The present analytical model provides more accurate predictions of the aerosol deposition on these surfaces than previous models.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".