Large Wildfires in the Western United States Exacerbated by Tropospheric Drying Linked to a Multi‐Decadal Trend in the Expansion of the Hadley Circulation
Bibliographic record
Abstract
Abstract Analyses of wildfire‐climate relationships in North America were conducted using diverse independent observation and reanalysis data sets for the period 1984–2014. Results show that the western United States (WUS) has experienced the most robust increase in burned area, even though Alaska and western‐central Canada have comparable warming trends. In addition to warming, the WUS has been under the influence of multi‐decadal trends in tropospheric relative humidity deficit, reduced cloudiness, increased surface net insolation, and enhanced adiabatic warming and drying from increased tropospheric subsidence, as well as drying from enhanced offshore low‐level flow. These trends are found to be associated with a widening of the descending branch of the Hadley circulation, consistent with climate model projections under greenhouse gases warming. Due to the relative short (~30 years) data record, the aforementioned trend signals are likely also be affected by phase changes of natural interdecadal variability during the data period.
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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 | 0.001 |
| 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".