Chemical perturbations from Asian summer monsoon in the extratropical UTLS during PHILEAS
Bibliographic record
Abstract
The Asian monsoon anticyclone (AMA) during northern summer is a major contributor to the transport of tropospheric air masses, rich in water vapour, aerosol precursors and surface emissions , into the UTLS. During previous HALO missions TACTS/ESMVal and WISE a significant impact of the monsoon export on the background composition of the lowermost stratosphere (LMS) could be observed. Recent observations during the research missions StratoClim and ACCLIP show evidence for a strong contribution of ammonium nitrate by the AMA to the UTLS aerosol budget and the Asian Tropopause Aerosol Layer (ATAL), likely relevant for cirrus cloud formation. These missions revealed that the northern central Pacific is a key region for the transition of air masses originating from the AMA and emissions from East Asia and China to cross the tropopause. Particularly, over the northern Pacific dynamical and diabatic forcings lead to a subsequent erosion of these eddies and to mixing into the background lower stratosphere. We will present first results from the PHILEAS mission, which took place between August and October 2023 over Anchorage/Alaska and Europe. We found strong perturbations of the gas phase and chemical composition in the UTLS region. These perturbations can be linked to the Asian monsoon and east Asian pollution sources as well as to Canadian wild fires, which occurred prior and during the measurements. Based on selected cases we will present clear evidence for cross tropopause transport and mixing of pollution from East Asian pollution and the AMA over the eastern Mediterranean as well as over the northern Pacific. We will show that these sources affected the aerosol as well as the gas phase composition of the lowermost stratosphere.
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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".