The Influence of Soil Moisture on the Historic 2021 Pacific Northwest Heatwave
Bibliographic record
Abstract
Abstract During late June 2021, a record-breaking heatwave impacted western North America, with all-time high temperatures reported across Washington, Oregon, British Columbia, and Alberta. The heatwave was forced by a highly anomalous upper-level ridge, strong synoptic-scale subsidence, and downslope flow resulting in lower-tropospheric adiabatic warming. This study examines the impact of antecedent soil moisture on this extreme heat event. During the cool season of 2020/21, precipitation over the Pacific Northwest was above or near normal, followed by a dry spring that desiccated soils to 50%–75% of normal moisture content by early June. Low surface soil moisture affects the surface energy balance by altering the partitioning between sensible and latent heat fluxes, resulting in warmer temperatures. Using numerical model simulations of the heatwave, this study demonstrates that surface air temperatures were warmed by an average of 0.48°C as a result of dry soil moisture conditions, compared to a high-temperature anomaly of 10°–20°C during the event. Air temperatures over eastern Washington and southern British Columbia were most sensitive to soil moisture anomalies, with 0000 UTC temperature anomalies ranging from 1.2° to 2.2°C. Trajectory analysis indicated that rapid subsidence of elevated parcels prevented air parcels from being affected by surface heat fluxes over a prolonged period of time, resulting in a relatively small temperature sensitivity to soil moisture. Changes to soil moisture also altered regional pressure, low-level wind, and geopotential heights, as well as modified the marine air intrusion along the Pacific coast of Washington and Oregon. Significance Statement The record-breaking western North American heatwave of late June 2021 was preceded by below-normal soil moisture over the region. This study evaluates the role of soil moisture on the 2021 heatwave, demonstrating that the anomalous temperatures during this extreme event were not significantly increased by below-normal soil moisture.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".