Evaluation of a regional air quality forecast model for tropospheric NO <sub>2</sub> columns using the OMI/Aura satellite tropospheric NO <sub>2</sub> product
Bibliographic record
Abstract
Abstract. Results from a regional air quality forecast model, AIRPACT-3, are compared to OMI tropospheric NO2 integrated column densities for an 18 month period over the Pacific Northwest. AIRPACT column densities are well correlated (r=0.75) to cloud-free (<35%) retrievals of tropospheric NO2 for monthly averages without wildfires, but are poorly correlated (r=0.21) with significant model over-predictions for months with wildfires when OMI and AIRPACT are compared over the entire domain. AIRPACT predicts higher NO2 in some northwestern US urban areas, and lower NO2 in the Vancouver, BC urban area, when compared to OMI. Model results are spatially averaged to the daily OMI swath. The Dutch KNMI (DOMINO) and NASA (Standard Product) retrievals of tropospheric NO2 from OMI (Collection-3) are compared. The NASA product is shown to be significantly different than the KNMI tropospheric NO2 product. The average difference in tropospheric columns, after applying the averaging kernels of the respective products to the model results, is shown to be larger in the summer (±50%) than winter (±20%).
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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 | 0.002 |
| 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 | 0.000 |
| 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".