Policy Document · 2024-12-01
2024 Climate Risk Landscape Report
Open the record to view the available source metadata.
Podcast · source-verified
Can AI Help Save the Planet?
Author or publisher unknown · 2024-11-21
Pierre Gentine, a Columbia University professor, joins Vis A Vis to discuss how AI enhances climate models and helps scientists tackle global warming.
Show citation
Author unknown. 2024-11-21. Can AI Help Save the Planet?. https://visavis.podcasts.library.columbia.edu/podcast/can-ai-help-save-the-planet/ (AI & Environment Resource Hub; record pod-0001; collection snapshot 2026-09-15).
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
Unclassified
orientation
Available source metadata
- Author or creator
- Unknown or not supplied
- Publisher
- Unknown or not supplied
- Publication date
- 2024-11-21
- Date precision
- day
- Geographic scope
- Unknown
- Language
- unknown
- Peer review
- unknown
- Source status
- verified
- Last verified
- 2026-09-15T16:43:54.945Z
- Snapshot import
- 2026-09-06
- Legacy domain
- Climate & Weather
- Legacy subdomain
- Climate Modeling & AI
Provenance and review
Source sheet: Podcast · Row 5 · Original ID: pod-0001.
Commentary and interviews should not be treated as independently verified findings. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
Suggest a correction for this record →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
Policy Document · 2026-05-01
24/7 Carbon-Free Energy for All: Towards a Resilient Energy System
Open the record to view the available source metadata.
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 · 2023-12-01
A Case Study Of An Extreme Flooding Episode In Charikar, Eastern Afghanistan
Severe flash floods in Charikar, Afghanistan, on August 26, 2020, were driven by extreme atmospheric instability, deep low-level convergence, and local topography, with climate change intensifying frontal activity and baroclinicity in the region.