A climatology of frozen‐in anticyclones in the spring arctic stratosphere over the period 1960–2011
Bibliographic record
Abstract
During springtime, following the stratospheric final warming, intrusions from low latitudes can become trapped at polar latitudes in long‐lived anticyclones. Such “frozen‐in” anticyclones (FrIACs) have occasionally been observed to persist as late as August, advected by summer easterlies. In this study, the high‐resolution advection contour model MIMOSA is used to advect a pseudo‐potential vorticity tracer. The model is driven by ERA‐40 and the ERA‐Interim reanalyses over the period 1960–2011. We first identify a remarkable FrIAC event in spring 2011. In addition, we developed a method to detect the characteristic size of low‐latitude intrusions into the polar region at the time of the spring transition, over the period 1960–2011. Years are classified as either Type‐A when the intrusions are small or as Type‐B when intrusions are large, potentially evolving into FrIACs. For a FrIAC to occur, we require an additional criterion based on the in‐phase character of the core of the intrusions and the anticyclone. During the 52 analyzed years, 9 events have been identified: 1 in the 1960s, 1 in the 1980s, 2 in the 1990s, and 5 from 2002. FrIAC are predominantly long‐lived intrusions, which occur in association with abrupt and early reversal to summer easterlies with a large heat flux pulse around the date of this wind reversal. Finally, the results are discussed in a climatological context.
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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 | 0.000 | 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".