Mesoscale simulations of atmospheric flow and tracer transport in Phoenix, Arizona
Bibliographic record
Abstract
Abstract Large urban centres located within confining rugged or complex terrain can frequently experience episodes of high concentrations of lower atmospheric pollution. Metropolitan Phoenix, Arizona (United States), is a good example, as the general population is occasionally subjected to high levels of lower atmospheric ozone, carbon monoxide and suspended particulate matter. As a result of dramatic but continuous increase in population, the accompanying environmental stresses and the local atmospheric circulation that dominates the background flow, an accurate simulation of the mesoscale pollutant transport across Phoenix and similar urban areas is becoming increasingly important. This is particularly the case in an airshed, such as that of Phoenix, where the local atmospheric circulation is complicated by the complex terrain of the area. Within the study presented here, a three‐dimensional time‐dependent mesoscale meteorological model (HOTMAC) is employed for simulation of lower‐atmospheric flow in Phoenix, for both winter and summer case‐study periods in 1998. The specific purpose of the work is to test the model's ability to replicate the atmospheric flow based on the actual observations of the lower‐atmospheric wind profile and known physical principles. While a reasonable general agreement is found between the model‐produced flow and the observed one, the simulation of near‐surface wind direction produces a much less accurate representation of actual conditions, as does the simulation of wind speed over 1,000 metres above the surface. Using the wind and turbulence output from the mesoscale model, likely particle plume trajectories are simulated for the case‐study periods using a puff dispersion model (RAPTAD). Overall, the results provide encouragement for the efforts towards accurately simulating the mesoscale transport of lower‐atmospheric pollutants in environments of complex terrain. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".