The 2021 Pacific Northwest heat wave and associated blocking: meteorology and the role of an upstream cyclone as a diabatic source of wave activity
Bibliographic record
Abstract
The heat wave that enveloped the Pacific Northwest from late June through early July 2021 delivered unprecedented temperatures to the normally cool region --- 108°F (42°C) in Seattle, 116°F (47°C) in Portland --- and claimed over 1000 lives mostly in British Columbia. We investigate the meteorological and dynamical conditions that led to this extreme heat event. The extreme surface temperatures (29-30 June) were preceded by the formation of an upper-level atmospheric blocking that snatched a warm pool of air from lower latitudes (25-27 June). A heat-trapping stable stratification ensued within the block, raising the surface temperatures significantly. The block itself was initiated by an upper-tropospheric wave breaking and the concomitant surface cyclogenesis off the coast of Alaska a few days prior (22-24 June). The regional local wave activity budget reveals that a localized diabatic source associated with this storm critically contributed to the zonal wave activity flux downstream, whose convergence over Canada drove the blocking. A simple wave activity-based reconstruction predicts a 41 percent reduction in strength and a 10-degree eastward displacement of the block when the upstream diabatic source is reduced by just 30 percent. Our work complements previous trajectory-based studies to gain insight on the role of diabatic heating in blocking episodes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".