Comparing Trends in the Southern Annular Mode and Surface Westerly Jet
Bibliographic record
Abstract
Abstract This paper examines trends in the southern annular mode (SAM) and the strength, position, and width of the Southern Hemisphere surface westerly wind jet in observations, reanalyses, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). First the period over 1951–2011 is considered, and it is shown that there are differences in the SAM and jet trends between the CMIP5 models, the Hadley Centre gridded SLP (HadSLP2r) dataset, and the Twentieth Century Reanalysis. The relationships between these trends demonstrate that the SAM index cannot be used to directly infer changes in any one kinematic property of the jet. The spatial structure of the observed trends in SLP and zonal winds is shown to be largest, but also most uncertain, in the southeastern Pacific. To constrain this uncertainty six reanalyses are included and compared with station-based observations of SLP. The CMIP5 mean SLP trends generally agree well with the direct observations, despite some climatological biases, while some reanalyses exhibit spuriously large SLP trends. Similarly, over the more reliable satellite era the spatial pattern of CMIP5 SLP trends is in excellent agreement with HadSLP2r, whereas several reanalyses are not. Then surface winds are compared with a satellite-based product, and it is shown that the CMIP5 mean trend is similar to observations in the core region of the westerlies, but that several reanalyses overestimate recent trends. The authors caution that studies examining the impact of wind changes on the Southern Ocean could be biased by these spuriously large trends in reanalysis products.
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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 | 0.001 |
| 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 | 0.001 | 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".