Policy Document · 2024-12-01
2024 Climate Risk Landscape Report
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Podcast
AI Unveils Hidden Climate Extremes
Spotify for Creators · 2024-12-02
What it covers
Researchers have developed an AI model called ClimateNet to analyze historical weather data.
Who it helps
Intended audience has not been documented.
Limitations
Source-specific limitations have not been reviewed. Inclusion and topic labels do not establish effectiveness or reliability.
Show citation
Spotify for Creators. 2024-12-02. AI Unveils Hidden Climate Extremes. https://creators.spotify.com/pod/show/aionair/episodes/AI-Unveils-Hidden-Climate-Extremes-e2rnhv5 (AI & Environment Resource Hub; record pod-0003; collection snapshot 2026-10-04).
Classification and context
Included in the original Podcast collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
lifecycle
orientation
Unclassified
Available source metadata
- Author or creator
- Unknown or not supplied
- Publisher
- Spotify for Creators
- Publication date
- 2024-12-02
- Date precision
- day
- Geographic scope
- Unknown
- Language
- unknown
- Peer review
- unknown
- Source access
- Reachable at last check
- Metadata confidence
- Required metadata corroborated
- Last verified
- 2026-09-28T20:11:03.965Z
- Snapshot import
- 2026-09-06
- Legacy domain
- Climate & Weather
- Legacy subdomain
- Extreme Weather Prediction
Provenance and review
- Source access
- Reachable at last check
- Metadata confidence
- Required metadata corroborated
- Editorial relevance
- Relevance has not been separately reviewed.
- Evidence quality
- Evidence quality has not been separately assessed.
Source sheet: Podcast · Row 8 · Original ID: pod-0003.
Commentary and interviews should not be treated as independently verified findings. Source link reachable · checked 2026-09-28. Source identity and required metadata verified. The import date is not the original date added.
Suggest a correction for this record →Newsletter appearances
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Related through shared environmental topics
Ordered by the number of shared provisional topic labels. This indicates a browsing connection, not agreement between sources.
Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
Scientific Paper · 2025-01-19
3D Cloud Reconstruction Through Geospatially-Aware Masked Autoencoders
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
Scientific Paper · 2025-05-21
A Foundation Model for the Earth System
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
Scientific Paper · 2025-04-23
A Hackathon for Flood Map Prediction From Geospatial Data With Parsimonious Machine Learning Models
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.