Quantifying the contribution of major carbon producers to increases in vapor pressure deficit and burned area in western US and southwestern Canadian forests
Bibliographic record
Abstract
Abstract Increases in burned forest area across the western United States and southwestern Canada over the last several decades have been partially driven by a rise in vapor pressure deficit (VPD), a measure of the atmosphere’s drying power that is significantly influenced by human-caused climate change. Previous research has quantified the contribution of carbon emissions traced back to a set of 88 major fossil fuel producers and cement manufacturers to historical global mean temperature rise. In this study, we extend that research into the domain of forest fires. We use a global energy balance carbon-cycle model, a suite of climate models, and a burned area (BA) model to determine the contribution of emissions traced to the major carbon producers to the long-term increase in VPD during 1901–2021 and to cumulative forest fire area during 1986–2021 in the western US and southwestern Canada. Based on climate model data, we find that emissions traced to these carbon producers contributed 48% (interquartile range (IQR) 38%–63%) of the long-term rise in VPD between 1901 and 2021. BA modeling indicates that these emissions also contributed 37% (IQR 26%–47%) of the cumulative area burned by forest fires between 1986 and 2021 in the western US and southwestern Canada. The increase in VPD in this region is linked to both increased fire activity and the region’s current and prolonged megadrought. As loss and damage from these hazards mounts, this research can inform public and legal dialogues regarding the responsibility carbon producers bear for addressing past, present, and future climate risks associated with fires and drought in the western US and southwestern Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".