Exploring climate futures with deep learning

Alaa Al Khourdajie ()
Additional contact information
Alaa Al Khourdajie: Imperial College London

Nature Climate Change, 2025, vol. 15, issue 7, 692-693

Abstract: Glancing forward to view alternative futures for limiting global warming requires understanding complex societal–environmental systems that drive future emissions. Now a study explores the potential, and limits, of deep learning to generate core characteristics of these futures.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41558-025-02350-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcli:v:15:y:2025:i:7:d:10.1038_s41558-025-02350-w

Ordering information: This journal article can be ordered from
https://www.nature.com/nclimate/

DOI: 10.1038/s41558-025-02350-w

Access Statistics for this article

Nature Climate Change is currently edited by Bronwyn Wake

More articles in Nature Climate Change from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().