Comparison of Canadian air quality forecast models with tropospheric ozone profile measurements above midlatitude North America during the IONS/ICARTT campaign: Evidence for stratospheric input
Bibliographic record
Abstract
During July and August, 2004, balloon‐borne ozonesondes were released daily at 12 sites in the eastern USA and Canada, producing the largest single set of free tropospheric ozone measurements ever compiled for this region. At the same time, a number of air quality forecast models were run daily as part of a larger field experiment. In this paper, we compare these ozonesonde profiles with predicted ozone profiles from several versions of two of these forecast models, the Environment Canada CHRONOS and AURAMS models. We find that the models show considerable skill at predicting ozone in the planetary boundary layer and immediately above. Individual station biases are variable, but often small. Standard deviations of observation‐forecast differences are large, however. Ozone variability in the models is somewhat higher than observed. Most strikingly, none of the model versions is able to reproduce the typical tropospheric ozone profile of increasing mixing ratio with altitude. Results from a sensitivity test suggest that the form of the ozone lateral boundary condition used by all model versions contributes significantly to the large ozone underpredictions in the middle and upper troposphere. The discrepancy could be reduced further by adding a downward flux of ozone from the model lid and by accounting for in situ production of ozone from lightning‐generated NOx.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".