Ozone source attribution and its modulation by the Arctic oscillation during the spring months
Bibliographic record
Abstract
We use the Model of Ozone and Related Tracers (MOZART‐2) driven by National Center for Environmental Prediction (NCEP) meteorology between 1980 and 2001 to examine the signature of the Arctic oscillation (AO) on tropospheric ozone during February and March. Regionally, the AO can modulate ozone by up to 5 parts per billion by volume (ppbv). We examine the modulation of ozone produced from Asian, American, and European emissions separately, the modulation of ozone produced from all tropospheric emissions, and the modulation of ozone transported from the stratosphere. During the positive phase of the AO, the simulations show a statistically significant decrease in zonally averaged ozone throughout the depth of the troposphere north of approximately 50°N. This decrease is attributed to a decrease in the stratospheric component of ozone. The longitudinal response of ozone to the AO in the upper troposphere is dictated by the changes in tropopause height associated with the AO, such that lower (higher) heights imply increased (decreased) ozone. Locally, the modulation of stratospheric ozone dominates the ozone signal throughout the depth of the troposphere over Northern Canada and the Arctic, where the AO is correlated with ozone decreases. In other locations, the local response to the AO is governed by changes in the transport of ozone produced in the troposphere. These locations include the lower troposphere over the Atlantic basin, where ozone is negatively correlated with the AO, and the lower troposphere over Europe and Eastern Siberia, where ozone is positively correlated with the AO.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".