Relationships between interannual variations in stratospheric warmings, tropospheric circulation, and sea surface temperature in the Northern Hemisphere
Bibliographic record
Abstract
The leading modes of interannual and long-term variations in the stratospheric and tropospheric circulation and total ozone (TOMS data) and their relations to Northern Hemisphere sea surface temperature (SST) anomalies are investigated using the monthly mean NCEP/NCAR reanalysis data for the winter months of 1958–2003. Strong correlations are indicated between the interannual total ozone variations over Labrador and the North Atlantic and changes in the stratospheric polar vortex. The onset of major stratospheric warmings is connected not only with the strengthening of westerlies at the 500-hPa level in the midlatitude Atlantic, but also with the weakening of tropospheric winds over the north of eastern Siberia and strengthening over the Far East. In years with major stratospheric warmings, abnormally cold winters are observed in Eurasia, especially in eastern Siberia and northeastern China. The calculated simultaneous (with no time lags) correlations of the stratospheric circulation changes with El Niño/La Niña events give evidence of low correlations between the tropical Pacific SST anomalies and the stratospheric dynamics in the Arctic. However, there are high correlations of the extratropical Pacific and Atlantic SST anomalies with interannual tropospheric and stratospheric circulation variations, the stratospheric dynamics being more strongly connected with Pacific SST than with Atlantic SST anomalies. The interannual changes in tropospheric circulation are coupled to SST anomalies in both the Pacific and the Atlantic. Mechanisms of long-term changes in the interactive ocean-atmosphere-ozone layer system are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".