Global aridity changes due to differences in surface energy and water balance between 1.5 °C and 2 °C warming
Bibliographic record
Abstract
Abstract Increased aridity and drought risks are significant global concerns. However, there are few comprehensive studies on the related risks with regard to the differences between relatively weak levels of warming, including the recent targets of the United Nations Framework Convention on Climate Change (UNFCCC) of 1.5 °C or 2 °C. The present study investigates the impacts of 1.5 °C and 2 °C warming on aridification and their non-linearity based on the relationship between available water and energy at the Earth’s terrestrial surface. Large multi-model ensembles with a 4000-model-year in total are sourced from the Half a degree Additional warming, Prognosis, and Projected Impacts (HAPPI) project. Results demonstrate that 2 °C warming results in more frequent dry states in the Amazon Basin, western Europe, and southern Africa, and a limited warming to 1.5 °C will mitigate aridification and increase the frequency of extreme dry-year in these regions. In the Mediterranean region, a significant acceleration of aridification is found from the 1.5 °C to 2 °C warming projections, which indicates a need to limit the warming by 1.5 °C. A substantial portion of Asia is projected to become increasingly humid under both 1.5 °C and 2 °C warming scenarios. In some geographic regions, such as Australia, a strong nonlinear shift of aridification is found as 2 °C warming results in shift to wetter state contrast to significant increases in aridity and dry-year frequency at the weaker level of warming. The results suggest that the responses of regional precipitation to global warming cause the aridity changes, but their nonlinear behaviors along with different warming levels should be assessed carefully, in particular, to incorporate the additional 0.5 °C warming.
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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 | 0.001 | 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 | 0.001 |
| 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".