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

Lyu, Pumeng; Tang, Tao; Ling, Fenghua; Luo, Jing-Jia; Boers, Niklas; Ouyang, Wanli; Bai, Lei

doi:10.1007/s00376-024-3316-6

Item

ITEM ACTIONSEXPORT

DownloadE-Mail

Please note that a newer version of this item is available:
https://publications.pik-potsdam.de/pubman/item/item_29933_2

DetailsSummary

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

Lyu, P., Tang, T., Ling, F., Luo, J.-J., Boers, N., Ouyang, W., Bai, L. (in press): ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks. - Advances in Atmospheric Sciences.
https://doi.org/10.1007/s00376-024-3316-6

Item is Released

show all hide all

Basic

show hide

Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_29933 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_29933_1

Genre: Journal Article

Files

show Files

hide Files

Lyu_2024_2312.10429 (Preprint), 18MB

File Permalink:
-

Name:
Lyu_2024_2312.10429

Description:
-

Visibility:
Private

MIME-Type / Checksum:
application/pdf

Technical Metadata:

Copyright Date:
-

Copyright Info:
-

License:
-

Locators

show

Creators

show

hide

Creators:
Lyu, Pumeng¹, Author
Tang, Tao¹, Author
Ling, Fenghua¹, Author
Luo, Jing-Jia¹, Author
Boers, Niklas², Author
Ouyang, Wanli¹, Author
Bai, Lei¹, Author

Affiliations:
1External Organizations, ou_persistent22
2Potsdam Institute for Climate Impact Research, ou_persistent13

Content

show

Details

show

hide

Language(s):

Dates: Accepted: 2024-05-24

Publication Status: Accepted / In Press

Pages: -

Publishing info: -

Table of Contents: -

Rev. Type: Peer

Identifiers: DOI: 10.1007/s00376-024-3316-6
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Organisational keyword: FutureLab - Artificial Intelligence in the Anthropocene
Model / method: Machine Learning
Research topic keyword: Climate impacts

Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show

hide

Title: Advances in Atmospheric Sciences

Source Genre: Journal, SCI, Scopus

Creator(s):

Affiliations:

Publ. Info: -

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1861-9533
Publisher: Springer