Comparison of two distinct leading modes in the variability of summer humidex and temperature heatwaves over North America
Bibliographic record
Abstract
Abstract Continuous hot and humid conditions pose greater health risks than heat alone, making it crucial to distinguish between temperature-driven and humidity-amplified heat stress. The variability of monthly humidex and temperature heatwaves over North America (NA) is compared for extended summers (June-September) from 1951 to 2022. Two distinct leading modes are identified for both humidex and temperature heatwaves over NA using empirical orthogonal function (EOF) analysis, collectively explaining 31% and 27% of total variance, respectively. These two leading modes, exhibiting a phase shift due to their orthogonality, are associated with large-scale atmospheric wave trains extending from the North Pacific to NA. This results in atmospheric pressure anomalies across the continent, driving notable differences in the variability of both heatwaves over NA. Atmospheric moisture transported from the North Pacific to NA also affects the development of both heatwaves, with more pronounced moisture anomalies observed for humidex heatwaves, highlighting a key distinction in the large-scale atmospheric circulation between humidex and temperature heatwaves. Positive phases of both heatwaves are associated with an anticyclonic anomaly, which leads to anomalous descent, reduced total cloud cover, above-normal surface radiation heating, and below-normal surface relative humidity over NA. Atmospheric moisture acts as a greenhouse gas to absorb longwave radiation, leading to increased downward longwave radiation. However, these physical processes exhibit weaker feedback with humidex heatwave variability across the two distinct modes, indicating the complexity of these interactions involving intensified cloud cover, surface humidity, and latent heat release due to significant atmospheric moisture injected into the regions of NA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".