Weather and climate predicted accurately — without using a supercomputer
Oliver Watt-Meyer ()
Nature, 2024, vol. 632, issue 8027, 991-992
Abstract:
A cutting-edge global model of the atmosphere combines machine learning with a numerical model based on the laws of physics. This ‘hybrid’ system accurately predicts the weather — and even shows promise for climate simulations.
Keywords: Atmospheric science; Climate sciences; Machine learning (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/d41586-024-02558-4 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:nature:v:632:y:2024:i:8027:d:10.1038_d41586-024-02558-4
Ordering information: This journal article can be ordered from
https://www.nature.com/
DOI: 10.1038/d41586-024-02558-4
Access Statistics for this article
Nature is currently edited by Magdalena Skipper
More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().