and Teleconnections with Large-Scale Modes of Climate Variability*
Bibliographic record
Abstract
The relationship between winter climate extremes across the northeasternUnited States and adjacent parts of Canada and some important modes of climate variability are examined to determine how these circulation patterns are related to extreme events. Linear correlations between 15 extreme climate indices related to winter daily precipitation, maximum and minimum temperature, and three dominant large-scale patterns of climate variability [the North Atlantic Oscillation (NAO), Pacific–North American (PNA) pattern, and El Niño–Southern Oscillation (ENSO)] were analyzed for the period 1950–99. The mechanisms behind these teleconnections are analyzed by applying composite analysis to the geopotential height, sea level pressure (SLP), moisture flux, and wind fields. Pressure anomalies and associated airflow patterns related with the different modes of climate variability explain the patterns of temperature and precipitation extremes across the region. The responses of the daily scale climate extremes to the seasonally averaged large-scale circulation patterns are achieved through shifts in the probability distributions. 1.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".