Formation and transport of photooxidants over Europe during the July 2006 heat wave – observations and GEM-AQ model simulations
Bibliographic record
Abstract
Abstract. The European heat wave of July 2006 was caused by advection of very hot and dry air from North Africa. Air masses were transported on the western edge of the high pressure system, centred over Eastern Europe, resulting in exceptionally high air temperatures over large areas of the continent. In the first two weeks of July 2006 a severe heat wave affected Central and North-Eastern Europe. We present a synoptic analysis of the July 2006 European heat wave, resulting formation and transport of photooxidants over Europe as simulated by the on-line tropospheric chemistry model GEM-AQ. The model was executed on a global variable grid with ~15 km resolution over the entire European continent. Modelling results have been compared with surface observations and vertical soundings of meteorological and air quality parameters. We find that the calculated error measures, as well as analysis of time series and trends for selected quantities, indicate good model performance over the simulation period. The spatial pattern of two exposure indicators – SOMO35 and AOT40 – showed similarities with the high temperatures distribution. The zone of highest exposure was located over Central Europe along the advection path of the hot African air mass. The exposure to high ozone concentrations in higher latitudes was reduced by the dilution and aging of polluted air masses advected from over Central Europe.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".