2024 Climate Risk Landscape Report
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AI & Environment Resource HubAuthor or publisher unknown · Publication date unknown
CoastalDEM® v3.0 is Climate Central’s newest, most precise, and best-trained digital elevation model ever.
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Author unknown. Date unknown. CoastalDEM. https://go.climatecentral.org/coastaldem (AI & Environment Resource Hub; record atlas-c5c5e51a5c49; collection snapshot 2026-10-04).
Included in the original Tool collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
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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.