Bibliographic record
Abstract
Abstract. The instability of the Northern Hemisphere polar vortex is mainly caused by the breaking of planetary-scale (Rossby) waves (RWs). However, gravity waves (GWs) may also play an important role in polar vortex preconditioning before breakdown events. Moreover, GWs affect dynamics in the stratosphere by altering the upward propagation of RWs at short time scales and therefore indirectly influence polar vortex stability. Due to the coarse spatial resolution of global chemistry-climate models, current efforts in climate research rely on simulations where the majority of the GW spectrum is parameterized. In the present study, we apply a recently developed method for detecting strong orographic gravity wave (OGW) drag events in the lower stratosphere above the Himalayas. For this, we use a specified dynamics simulation of the chemistry-climate model CMAM (Canadian Middle Atmosphere Model) spanning the period 1979–2010. We show that strong OGW drag events above the Himalayas are associated with anomalously increased upward RW propagation in the stratosphere. This, in turn, is associated with an increase of the refractive index in the mid-latitude lower stratosphere, a region where the OGW drag dominates. Our results also illustrate that OGW strong events have the potential to alter ozone variability via changes of mixing in the surf zone and advection from lower latitudes. Altogether, we detail a preconditioning process of the polar vortex morphology by GWs above the Himalayas and how this relates to the proximity to polar vortex breakdown.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.925 | 0.903 |
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".