The spatiotemporal variations of winter severity over North America
Bibliographic record
Abstract
Abstract Winter severity affects many aspects of life, including traffic, public health, and the behaviour of animals and plants. The newly developed accumulated winter season severity index (AWSSI) is used in this study to examine the changes of winter severity across North America (NA) during recent decades. The results indicated that the winter severity experienced a notable interdecadal transition in 1965, characterized by increasing AWSSI before 1965, and decreasing AWSSI after 1965. This study also investigates the relationship between the winter severity and the atmospheric circulations over NA. The variations of winter severity are mainly controlled by temperature, while the large‐scale forcings (i.e., ENSO, PDO, and NAO) also play an important role. In particular, PDO is mainly associated with the opposite variation of winter severity between the Southeastern United States and Northwestern NA, while the NAO leads to the opposite variation of winter severity between the Eastern United States and Eastern Canada. Under the influence of ENSO, the variations of winter severity over Southern and Interior Alaska, the Pacific Northwest, and the Northern Great Plains are opposed to that over the Southern United States and Northern Canada.
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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".