Policy Document · 2024-12-01
2024 Climate Risk Landscape Report
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Scientific Paper
The First Ice-Free Day in the Arctic Ocean Could Occur Before 2030
Céline Heuzé, Alexandra Jahn · 2024-12-03
What it covers
New projections suggest the Arctic's first ice-free day could occur before 2030, driven by rapid ice loss and strong seasonal warming.
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
Céline Heuzé, Alexandra Jahn. 2024-12-03. The First Ice-Free Day in the Arctic Ocean Could Occur Before 2030. https://www.nature.com/articles/s41467-024-54508-3 (AI & Environment Resource Hub; record paper-015; collection snapshot 2026-10-04).
Classification and context
Included in the original Scientific Paper collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
lifecycle
Unclassified
orientation
Unclassified
Available source metadata
- Author or creator
- Céline Heuzé, Alexandra Jahn
- Publisher
- Nature Communications
- Publication date
- 2024-12-03
- Date precision
- day
- Geographic scope
- Unknown
- Language
- unknown
- Peer review
- unknown
- Source access
- Reachable at last check
- Metadata confidence
- Metadata unconfirmed
- Last verified
- Not yet verified
- Snapshot import
- 2026-09-06
- Legacy domain
- Climate & Weather
- Legacy subdomain
- AI for Arctic Climate Projections
- journal
- Nature Communications
Provenance and review
- Source access
- Reachable at last check
- Metadata confidence
- Metadata unconfirmed
- Editorial relevance
- Relevance has not been separately reviewed.
- Evidence quality
- Evidence quality has not been separately assessed.
Source sheet: Scientific Paper · Row 19 · Original ID: paper-015.
A paper listing is not a quality assessment. Peer review and findings require source-level confirmation. Source link reachable · checked 2026-09-28. Metadata not yet corroborated. The import date is not the original date added.
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Related through shared environmental topics
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Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
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Shared topics: Climate and greenhouse gases; Weather, hazards, and adaptation
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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.