Transport pathways of peroxyacetyl nitrate in the upper troposphere and lower stratosphere from different monsoon systems during the summer monsoon season
Bibliographic record
Abstract
Abstract. The Asian summer monsoon involves complex transport patterns with large scale redistribution of trace gases in the upper troposphere and lower stratosphere (UTLS). We employ the global chemistry–climate model ECHAM5-HAMMOZ in order to evaluate the transport pathways and the contributions of nitrogen oxide reservoir species PAN, NOx, and HNO3 from various monsoon regions, to the UTLS over Southern Asia and vice versa. The model is evaluated with trace gas retrievals from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS-E) and aircraft campaigns during the monsoon season (June–September). There are three regions which contribute substantial pollution to the UTLS during the monsoon: the Asian summer monsoon (ASM), the North American Monsoon (NAM) and the West African monsoon (WAM). However, penetration due to ASM convection is deeper into the UTLS as compared to NAM and WAM outflow. The circulation in these monsoon regions distributes PAN into the tropical latitude belt in the upper troposphere. Remote transport also occurs in the extratropical upper troposphere where westerly winds drive North American and European pollutants eastward to partly merge with the ASM plume. Strong ASM convection transports these remote and regional pollutants into the lower stratosphere. In the lower stratosphere the injected pollutants are transported westward by easterly winds. The intense convective activity in the monsoon regions is associated with lightning generation and thereby the emission of NOy species. This will affect the distribution of PAN in the UTLS. The estimates of lightning produced PAN, HNO3, NOx and ozone obtained from control and lightning-off simulations shows high percentage changes over the regions of convective transport especially equatorial Africa and America and comparatively less over the ASM. This indicates higher anthropogenic pollution transport from the ASM region into the UTLS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".