The development of a warm-season blocking index for the Northern Hemisphere /
Bibliographic record
Abstract
Considerable research has been performed on persistent-anomaly structures for the Northern Hemisphere winter. However, atmospheric blocking structures during the warm season also have a considerable impact on weather and climate, as manifested through heat waves, floods, and droughts. In particular, atmospheric blocked flow has a profound impact on anomalously-dry regimes over the central North American continent. In order to provide a better understanding of the life cycle of the atmospheric blocking events and their relation to fast-climate phenomena, we analyse persistent height-anomaly structures derived from the National Centers for Environmental Prediction (NCEP) global reanalyses. We devise an objective criterion for the characterization of blocked flow by relating it to persistent positive height anomalies. Individual warm-season events over the North American continent are then identified and examined in case studies. This reveals a type of blocking regime, differing in structure from the Rex and Omega type blocks described in the literature, as being important in the region during summer. Moreover, changes in the statistical distribution of the event frequencies are analysed in order to detect climatic trends. We find a pronounced westward displacement of the North American anomaly event frequency maximum to be associated with the 1999-2004 drought in the Canadian Prairies.
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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 | 0.002 |
| 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".