Avoided impacts of climate change on compound hot-dry events under sustainable development versus fossil-fueled development
Bibliographic record
Abstract
Climate change is expected to increase the frequency and intensity of compound hot-dry events, which can have significant impacts on human life, economic systems, and agriculture. The extent of this impact depends on the socioeconomic pathway we adopt in the future. While sustainable development aspires to reconcile economic growth, environmental protection, and social equity, thereby ensuring a more sustainable future for all, fossil-fueled development may drive economic growth at the expense of exacerbating climate change, pollution, and resource depletion. This study employs a CMIP6 multi-model ensemble to scrutinize the global-scale potential for mitigating climate change impacts on compound hot-dry events under sustainable development versus fossil-fueled development. These events are quantified by analyzing the joint distribution probability between temperature and soil moisture extremes through bivariate copula functions. The results show that although the likelihood of compound hot-dry events is expected to increase under both scenarios, the increase under fossil-fueled development is anticipated to be twice larger than that under sustainable development. The results show that although the likelihood of compound hot-dry events is expected to increase under both scenarios, the increase under fossil-fueled development is anticipated to be twice as large as that under sustainable development. The mitigated impact through sustainable development is not regionally uniform, with the largest mitigation, up to one-third, expected in the Mediterranean region.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".