2024 Climate Risk Landscape Report
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AI & Environment Resource HubCentre for AI and Climate/Climate Change AI · 2021-11-01
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Source identity and required public metadata were editorially reviewed on 2026-09-15.
Source identity and required public metadata were editorially reviewed on 2026-09-15.
Centre for AI and Climate/Climate Change AI. 2021-11-01. Climate Change and AI: Recommendations for Government Action. https://gpai.ai/projects/responsible-ai/environment/climate-change-and-ai.pdf (AI & Environment Resource Hub; record report-006; collection snapshot 2026-10-04).
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Source sheet: Policy Document · Row 10 · Original ID: report-006.
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Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
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Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
Self-supervised learning enhances 3D cloud reconstruction, improving climate predictions by reducing uncertainties in climate models.
Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
Aurora is a large-scale AI foundation model that significantly outperforms traditional forecasting systems across multiple Earth system domains, like air quality and cyclone tracking, while using far less computational power, marking a major advancement in accessible, efficient environmental prediction.
Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
This study showcases a machine learning hackathon in France where a CNN-based model accurately predicted flood risk evolution using geospatial and climate data, even without streamflow input, emphasizing trustworthy AI in data-scarce regions.