Transport timescales and tracer properties in the extratropical UTLS
Bibliographic record
Abstract
Abstract. A comprehensive evaluation of seasonal backward trajectories initialized in the Northern Hemisphere lowermost stratosphere (LMS) has been performed to investigate the origin of air parcels and the main mechanisms determining characteristic structures in H2O and CO within the LMS. In particular we explain the fundamental role of the transit time since last tropopause crossing (tTST) for the chemical structure of the LMS as well as the feature of the extra-tropical tropopause transition layer (ExTL) as identified from CO profiles. The distribution of H2O in the background LMS above Θ=320 K and 340 K in northern winter and summer, respectively, is found to be governed mainly by the saturation mixing ratio, which in turn is determined by the Lagrangian Cold Point (LCP) encountered by each trajectory. Most of the backward trajectories from this region in the LMS experienced their LCP in the tropics and sub-tropics. The transit time since crossing the tropopause from the troposphere to the stratosphere (tTST) is independent of the H2O value of the air parcel. TST often occurs 20 days after trajectories have encountered their LCP. CO, on the other hand, depends strongly on tTST due to its finite lifetime. The ExTL as identified from CO measurements is then explained as a layer of air just above the tropopause, which on average encountered TST fairly recently.
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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 | 0.000 | 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".