The Unprecedented Pacific Northwest Heatwave of June 2021: Causes and Impacts
Bibliographic record
Abstract
In late June 2021 a heatwave of unprecedented magnitude impacted the Pacific Northwest (PNW) region of Canada and the United States. Many locations broke all-time maximum temperature records by more than 5°C, and the Canadian national temperature record was broken by 4.6°C, with the highest recorded temperature 49.6°C. Local records were broken by large margins, even when compared to local records broken during the infamous heatwaves in Europe 2003, and Russian in 2010. A region of high pressure that became stationary over the region (an atmospheric block) was the dominant cause of this heatwave; however, trajectory analysis finds that upstream diabatic heating played a key role in the magnitude of the temperature anomalies. Weather forecasts provided advanced notice of the event, while sub-seasonal forecasts showed an increased likelihood of a heat extreme with 10-20 day lead times, with an increased likelihood of a blocking event seen in forecasts initialized 3 weeks prior to the heatwave peak. The impacts of this event were catastrophic. We provide a summary of some of these impacts, including estimates of hundreds of attributable deaths across the PNW, mass-mortalities of marine life, reduced crop and fruit yields, river flooding from rapid snow and glacier melt, and a substantial increase in wildfires—the latter contributing to devastating landslides in the months following. These impacts provide examples we can learn from, and a vivid depiction of how climate change can be so devastating.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".