Policy Document · 2024-12-01
2024 Climate Risk Landscape Report
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Course
Policy Impact for Emerging Climate Leaders
Aspen Policy Academy · Publication date unknown
What it covers
To support emerging climate leaders in their efforts to move climate policy, the Aspen Policy Academy is hosting a part-time, unpaid policy impact bootcamp for climate leaders between the ages of 21 and 30.
Who it helps
Intended audience has not been documented.
Limitations
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.
Show citation
Aspen Policy Academy. Date unknown. Policy Impact for Emerging Climate Leaders. https://aspenpolicyacademy.org/short-courses/#policyforclimate (AI & Environment Resource Hub; record atlas-7aaa0b073347; collection snapshot 2026-10-04).
Classification and context
Included in the original Course collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
lifecycle
Unclassified
Available source metadata
- Author or creator
- Unknown or not supplied
- Publisher
- Aspen Policy Academy
- Publication date
- Unknown or not supplied
- Date precision
- unknown
- Geographic scope
- Unknown
- Language
- unknown
- Peer review
- unknown
- Source access
- Reachable at last check
- Metadata confidence
- Required metadata corroborated
- Last verified
- 2026-09-15T00:00:00.000Z
- Snapshot import
- 2026-09-06
- Legacy domain
- Climate & Weather
- Legacy subdomain
- Unknown or not supplied
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.
Selected fields checked: · 2026-09-06. Editorial review confirmed this record against its current source page/file; limited or generic machine-readable metadata prevented automatic corroboration. Verification source ↗
Source sheet: Course · Row 8 · Original ID: Not supplied.
Availability, fees, and enrollment dates may have changed since collection. 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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No issue-specific evidence recorded.
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
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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.