ArticleProceedings of the National Academy of Sciences of the United States of America2023
Data-driven predictions of the time remaining until critical global warming thresholds are reached.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
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- Interplay between auxin and abiotic stresses in maize.Journal of experimental botany · 2025Review
- Transferring climate change physical knowledge.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Global warming and obesity: External heat exposure as a modulator of energy balance.FASEB bioAdvances · 2025Review
- Machine learning-based extreme event attribution.Science advances · 2024Article
- Optimal decision-making in relieving global high temperature-related disease burden by data-driven simulation.Infectious Disease Modelling · 2024Article
- Speed of environmental change frames relative ecological risk in climate change and climate intervention scenarios.Nature communications · 2024Article
- Soybean-Phakopsora pachyrhizi interactions: towards the development of next-generation disease-resistant plants.Plant biotechnology journal · 2024Review
- Marginal effects of economical development and university education on China's regular exercise population.Frontiers in public health · 2024Article
- When and where can coastal wetland restoration increase carbon sequestration as a natural climate solution?Cambridge prisms. Coastal futures · 2024Review
- Life cycle assessment of a direct air capture and storage plant in Ireland.Scientific reports · 2023Article
- Ambient temperatures associated with reduced cognitive function in older adults in China.Scientific reports · 2023Article
- Multi-hazard exposure mapping under climate crisis using random forest algorithm for the Kalimantan Islands, Indonesia.Scientific reports · 2023Article
- Data-driven predictions of the time remaining until critical global warming thresholds are reached.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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2 authors.
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Abstract
Leveraging artificial neural networks (ANNs) trained on climate model output, we use the spatial pattern of historical temperature observations to predict the time until critical global warming thresholds are reached. Although no observations are used during the training, validation, or testing, the ANNs accurately predict the timing of historical global warming from maps of historical annual temperature. The central estimate for the 1.5 °C global warming threshold is between 2033 and 2035, including a ±1σ range of 2028 to 2039 in the Intermediate (SSP2-4.5) climate forcing scenario, consistent with previous assessments. However, our data-driven approach also suggests a substantial probability of exceeding the 2 °C threshold even in the Low (SSP1-2.6) climate forcing scenario. While there are limitations to our approach, our results suggest a higher likelihood of reaching 2 °C in the Low scenario than indicated in some previous assessments-though the possibility that 2 °C could be avoided is not ruled out. Explainable AI methods reveal that the ANNs focus on particular geographic regions to predict the time until the global threshold is reached. Our framework provides a unique, data-driven approach for quantifying the signal of climate change in historical observations and for constraining the uncertainty in climate model projections. Given the substantial existing evidence of accelerating risks to natural and human systems at 1.5 °C and 2 °C, our results provide further evidence for high-impact climate change over the next three decades.
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