A Storyline Approach to the June 2021 Northwestern North American Heatwave
Bibliographic record
Abstract
Abstract Northwestern North America has experienced an exceptional heatwave in late June 2021 with many new temperature records across western Canada, Oregon and Washington states. Here we use a recent atmospheric reanalysis and a conditional approach based on dynamical adjustment to assess and quantify the influence of atmospheric circulation and other driving factors to the heatwave magnitude during the June 28–30 period. A blocking anticyclone, enhanced low‐level moisture and clear‐sky downward long‐wave radiation are shown to be the main factors of the heatwave persistence and magnitude. The heatwave magnitude is mainly attributable to internal variability with climate change being an additional factor (10%). Consequences of a similar atmospheric circulation anomaly in different phases of the Pacific Decadal Oscillation s and in a warmer world at different global warming levels (1, 2, 3, and 4°C) are explored based on a single model initial‐condition large ensemble.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".