Projected Changes in Heat Extremes and Associated Synoptic- and Mesoscale Conditions over the Northwest United States
Bibliographic record
Abstract
Abstract A number of studies have suggested that heat waves will increase in frequency, intensity, and duration under anthropogenic global warming. However, changes to heat extremes and temperature distributions in general are less understood in regions of complex terrain and substantial land–water contrasts. Such surface variations are important in the northwest United States, where synoptic- and mesoscale circulations interact with local topography and land–water interfaces to produce heat waves that have substantial impacts on fire weather, air quality, wind energy, and the population in general. Thus it is crucial to identify how the synoptic- and mesoscale circulations that drive such local extremes will change in a warming world. This paper analyzes changes to the conditions associated with heat extremes over the northwest United States by utilizing global and regional climate models. A maximum in 700-hPa warming is projected over the northwest United States and southwest Canada, with low-level warming attenuated near the coast. Soil moisture declines are projected over the region, which further enhances future extremes. It is found that low-level zonal wind distributions over the northwest United States become narrower, leading to fewer days with strong offshore flow. This is important since extreme warming events are associated with the strongest offshore/downslope flow. Historical and future regional temperature distributions are described and it is shown that although CMIP5 models predict increases in heat extremes for west Oregon and Washington, these increases are less than for inland areas.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".