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ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks.

Authors :
Lyu, Pumeng
Tang, Tao
Ling, Fenghua
Luo, Jing-Jia
Boers, Niklas
Ouyang, Wanli
Bai, Lei
Source :
Advances in Atmospheric Sciences; Jul2024, Vol. 41 Issue 7, p1289-1298, 10p
Publication Year :
2024

Abstract

<i>Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)

Details

Language :
English
ISSN :
02561530
Volume :
41
Issue :
7
Database :
Complementary Index
Journal :
Advances in Atmospheric Sciences
Publication Type :
Academic Journal
Accession number :
178027408
Full Text :
https://doi.org/10.1007/s00376-024-3316-6