Meteorological Analysis of the Pacific Northwest June 2021 Heatwave
Bibliographic record
Abstract
Abstract During the last week of June 2021, the Pacific Northwest region of North America experienced a record-breaking heatwave of historic proportions. All-time high temperature records were shattered, often by several degrees, across many locations, with Canada setting a new national record, the state of Washington setting a new record, and the state of Oregon tying its previous record. Here we diagnose key meteorology that contributed to this heatwave. The event was associated with a highly anomalous midtropospheric ridge, with peak 500-hPa geopotential height anomalies centered over central British Columbia. This ridge developed over several days as part of a large-scale wave train. Back trajectory analysis indicates that synoptic-scale subsidence and associated adiabatic warming played a key role in enhancing the magnitude of the heat to the south of the ridge peak, while diabatic heating was dominant closer to the ridge center. Easterly/offshore flow inhibited marine cooling and contributed additional downslope warming along the western portions of the region. A notable surface thermally induced trough was evident throughout the event over western Oregon and Washington. An eastward shift of the thermal trough, following the eastward migration of the 500-hPa ridge, allowed an inland surge of cooler marine air and dramatic 24-h cooling, especially along the western periphery of the region. Large-scale horizontal warm-air advection played a minimal role. When compared with past highly amplified ridges over the region, this event was characterized by much higher 500-hPa geopotential heights, a stronger thermal trough, and stronger offshore flow.
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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 | 0.001 | 0.001 |
| 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".