Regional temperature extremes and vulnerability under net zero CO<sub>2</sub> emissions
Bibliographic record
Abstract
Abstract Signatories to the Paris Agreement have pledged to keep global warming to well below 2 °C above pre-industrial levels and preferably below 1.5 °C above pre-industrial levels. Beyond over-shooting Paris Agreement warming levels followed by net negative emissions, achieving a state of net zero carbon dioxide emissions is required to satisfy Paris Agreement warming goals. Research on climate changes under net zero CO 2 emissions is very limited to date with no comprehensive analysis of changes in extremes. In this study, we use results from Earth System Models in the zero emissions commitment model intercomparison project to understand regional mean-state climate change patterns during a 100 year period following carbon dioxide emissions cessation. We also perform an initial study of the evolution of hot and cold monthly temperature extremes after net zero CO 2 emissions, including an assessment of how the change in frequency of temperature extremes affects areas of different levels of socioeconomic development based on regional Human Development Index (HDI). The results show that most land regions experience a fast and continuous cooling response following emissions cessation, with large areas of significant model agreement. In contrast, the Southern Ocean continues warming over the century after emissions cessation. The frequency of land-based local monthly high temperature extremes generally stays constant or decreases during the century after emissions cessation, however, decreases in heat extreme frequencies are generally less for locations with lower modern HDI than areas with higher HDI which suggests that inequality of climate change will remain an issue even after net zero CO 2 emissions. There is an evident emergence of local monthly cold extremes following emissions cessation with most significant impact over high HDI mid- and high-latitude land regions.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".