A new one-year global lagrangian climatology of mass transport in the lowermost stratosphere
Bibliographic record
Abstract
We present the first year-long climatology of a new real-time global Lagrangian diagnostic system for stratosphere-troposphere exchange. This Environment Canada data set has been producing and archiving daily data since July 20th, 2010. A set of trajectories are calculated every day starting at 00:00UTC using the operational global forecast. They are seeded every 5 hPa between 600 and 10 hPa over the entire globe with even horizontal spacing of 55 km. We examine the mass fluxes across i) the dynamical tropopause,which is taken to be the 2 PVU iso-surface, and ii) the 380K temperature surface. Pole-ward of approximately 20o these two surfaces form a wedge called the Lowermost Stratosphere (LMS). The dynamics responsible for the transport across these two surfaces are very different. Mass flux across 380K, the upper surface, is driven by diabatic effects associated with the Brewer-Dobson circulation. Transport across the dynamical tropopause is dominated by quasi-isentropic mixing associated with baroclinic wave activity. The details of the transport across these two surfaces is known to determine the rate of injection of stratospheric ozone into the troposphere. This transport process is still today one of the major causes of uncertainty concerning the tropospheric ozone budget. Here we present the first one-year climatology of high-resolution global mass transport in the LMS, including geographical distributions and the Northern Hemispheric mass budgets, and will compare our results with previous studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".