Stratosphere-troposphere exchange from the Lagrangian perspective: a case study and method sensitivities
Bibliographic record
Abstract
Abstract. An important part of extra-tropical stratosphere-to-troposphere transport occurs in association with baroclinic wave breaking and cut-off decay at the tropopause. In the last decade many studies have attempted to estimate stratosphere-troposphere exchange (STE) in such synoptic events with various methods, and more recently efforts have been made to inter-compare these methods. These inter-comparisons show large variations between estimates from different methods. This large uncertainty points to a need to thoroughly evaluate such methods, assess the realism of the resulting STE estimates and determine the sensitivities to intrinsic parameters of the methods. The present study focuses on a trajectory-based Lagrangian method which has been applied in the past to climatological studies. This method is applied here to the quantification of STE in the context of a typical baroclinic wave breaking event. The analysis sheds light on (i) the complex three-dimensional temporal and spatial structures that are associated with the rapid inflow of stratospheric air into the troposphere, (ii) the variation of STE mass flux with the choice of the dynamical tropopause definition within 1.5 to 5 PVU, (iii) the sensitivity of the results to resolution, and in particular the minimum spatial resolution of 1°×1° required to reasonably capture STE fluxes in this wave breaking event, (iv) the effective removal of spurious exchange events using a threshold residence time larger than 8 h.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".