A note on the potential impact of aviation emissions on jet stream propagation over the northern hemisphere
Bibliographic record
Abstract
Abstract The goal of the study was to investigate if aviation emissions could influence the climate and weather by modifying the chemical composition of the atmosphere and subsequently, the radiative balance. To carry out the set objective, we used the global environmental multiscale atmospheric chemistry model with comprehensive tropospheric and stratospheric chemistry that is interactive with the radiation calculations. The model was run for two current climate scenarios, with and without aviation emissions. The results of the study indicate that the most significant difference in the jet stream propagation occurred during the winter season, and the smallest was observed during summer. Changes in the jet stream propagation vary by season and region. During the colder time of the year, the eddy-driven jet stream tends to shift poleward, while during the spring season the equatorward shift was observed in a scenario with aviation emissions. Analysis of regional changes shows that the most noticeable differences occurred over the Pacific Ocean, Atlantic Ocean and Asia. The changes over the oceans changed the occurrence of the North Pacific and Bermuda–Azores Highs. Over Asia (Siberia), a stronger and more poleward drift of the eddy-driven jet stream was observed in a scenario without aviation emission. Dissimilarity in the jet stream velocity was found only during the winter seasons when in a scenario with aviation emission, the jet stream velocity was 10 m/s smaller as compared to the scenario without aviation emission.
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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 | 0.001 |
| 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 | 0.001 | 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".