Transport of aerosols into the UTLS and their impact on the Asian monsoon region as seen in a global model simulation
Bibliographic record
Abstract
Abstract. An eight-member ensemble of ECHAM5-HAMMOZ simulations for a boreal summer season is analysed to study the transport of aerosols in the upper troposphere and lower stratosphere (UTLS) during the Asian summer monsoon (ASM). The simulations show persistent maxima in black carbon, organic carbon, sulfate, and mineral dust aerosols within the anticyclone in the UTLS throughout the ASM (period from July to September), when convective activity over the Indian subcontinent is highest, indicating that boundary layer aerosol pollution is the source of this UTLS aerosol layer. The simulations identify deep convection and the associated heat-driven circulation over the southern flanks of the Himalayas as the dominant transport pathway of aerosols and water vapour into the tropical tropopause layer (TTL). Comparison of model simulations with and without aerosols indicates that anthropogenic aerosols are central to the formation of this transport pathway. Aerosols act to increase cloud ice, water vapour, and temperature in the model UTLS. Evidence of ASM transport of aerosols into the stratosphere is also found, in agreement with aerosol extinction measurements from the Halogen Occultation Experiment (HALOE) and Stratospheric Aerosol and Gas Experiment (SAGE) II. As suggested by the observations, aerosols are transported into the Southern Hemisphere around the tropical tropopause by large-scale mixing processes. Aerosol-induced circulation changes also include a weakening of the main branch of the Hadley circulation and a reduction of monsoon precipitation over India.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".