Storskaliga atmosfärsmönster som bildar extrema temperaturavvikelser under våren i Arktis
Bibliographic record
Abstract
In this project warm extreme temperature events in the Arctic region during the spring months March, April and May were identified and analysed. In the analysis daily average NCEP reanalysis data from NOAA/OAR/ESRL PSL format was used. The extreme events were retrieved as the highest positive temperature anomalies from the climatological mean, and the synoptic scale plots for the 50 most extreme events were created to identify what patterns caused the extreme warming over the Polar region. By contouring the areas of statistical significance, the regions with a reoccuring pattern were identified. The results conclude that cyclonic activity over the high Arctic extending down over Greenland and northern Canada combined with anomalously high geopotential height over the north Pacific ocean, over the Arctic, and towards Siberia cause the high temperatures over the pole. A weaker Polar Vortex causes perturbations in the jet stream, ridges in these Rossby waves can act as a pathway for warm and moist air from the oceanic regions which has a warming effect in the Arctic. Further analysis can be done to investigate what teleconnections these spring-time extreme events have on a global scale.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 0.017 |
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".