An assessment of dust emission schemes in modeling east Asian dust storms
Bibliographic record
Abstract
By implementing dust emission schemes developed by Marticorena and Bergametti (1995), Alfaro et al. (1997), Alfaro and Gomes (2001) (hereinafter referred to as MBA) and Shao (2001, 2004) into a regional climate model with a size‐distributed active aerosol algorithm, NARCM (Northern Aerosol Regional Climate Model), an assessment of dust emission schemes in the simulation of east Asian dust storms for March 2002 was carried out. Sensitivity of the parameters used for both the MBA and Shao schemes is first analyzed with a box version of the NARCM, where the wind erosion threshold friction velocities for both schemes are in good agreement for soil grain size range in diameter from 40 μm to 400 μm but differ for other size ranges. Although the impacts of clay, silt, loam and sand contents on vertical dust fluxes show a similar trend, their dependences on friction velocity vary substantially as the correction factors in each scheme to the threshold friction velocity, soil moisture and vegetation cover present a different degree of impact on vertical dust fluxes with wind friction velocity. One specific parameter, soil plastic pressure p, required by the Shao scheme varies between 103 Pa for loose surfaces and 105 Pa for hard crusted surfaces, which controls significantly emission flux. On the basis of the comparison of dust emission with the MBA scheme in the box model, the soil plastic pressure p applicable to Asian deserts for the Shao scheme is set to be 1000 Pa for sandy, 5000 Pa for loamy and silty and 10,000 Pa for clay soil in March 2002. In 3‐D simulations, both schemes captured the dust mobilization episodes during this period in east Asia and produced the similar spatial distributions of Asian dust column loading. Compared with the MBA scheme, the Shao scheme predicted much lower dust emission and surface concentration in eastern Mongolia and eastern and central north China and slightly higher with some additional dust emission sources in north western China, eastern Kazakhstan and western Mongolia. The key parameters responsible for the differences between the MBA and Shao emission schemes are the surface and soil‐related factors including soil moisture and vegetation coverage.
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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 | 0.003 |
| 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) | 0.000 | 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".