Modeled Downward Transport of a Passive Tracer over Western North America during an Asian Dust Event in April 1998
Bibliographic record
Abstract
An intense Gobi Desert dust storm in April 1998 loaded the midtroposphere with dust that was transported across the Pacific to western North America. The Mesoscale Compressible Community (MC2) model was used to investigate mechanisms causing downward transport of the midtropospheric dust and to explain the high concentrations of particulate matter of less than 10-μm diameter measured in the coastal urban areas of Washington and southern British Columbia. The MC2 was initialized with a thin, horizontally homogeneous layer of passive tracer centered at 650 hPa for a simulation from 0000 UTC 26 April to 0000 UTC 30 April 1998. Model results were in qualitative agreement with observed spatial and temporal patterns of particulate matter, indicating that it captured the important meteorological processes responsible for the horizontal and vertical transport over the last few days of the dust event. A second simulation was performed without topography to isolate the effects of topography on downward transport. Results show that the dust was advected well east of the North American coast in southwesterly midtropospheric flow, with negligible dust concentration reaching the surface initially. Vertically propagating mountain waves formed during this stage, and differences between downward and upward velocities in these waves could account for a rapid descent of dust to terrain height, where the dust was entrained into the turbulent planetary boundary layer. A deepening outflow (easterly) layer near the surface transported the tracer westward and created a zonal-shear layer that further controlled the tracer advection. Later, the shear layer lifted, leading to a downward hydraulic acceleration along the western slopes, as waves generated in the easterly flow amplified below the shear layer that was just above mountain-crest height. Examination of 10 yr of National Centers for Environmental Prediction–National Center for Atmospheric Research reanalyses suggests that such events are rare.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".