ML4WX

Sub-seasonal to seasonal

Superiority of a Convolutional Neural Network Model over Dynamical Models in Predicting Central Pacific ENSO

Tingyu Wang, Ping Huang

Advances in Atmospheric Sciences · · Nanjing University of Information Science & Technology (NUIST), Institute of Atmospheric Physics, Chinese Academy of Sciences

Paper

In one sentence. A convolutional neural network is reported to outperform dynamical models in predicting Central Pacific ENSO events.

Labels

Topic
Sub-seasonal to seasonal
Type
New model or method
Method
CNN / U-Net
Time scale
Seasonal to annual
Domain
Global
Data
Other
Status
Research
Identifiers
DOI:10.1007/s00376-023-3001-1 OpenAlex:W4384408321
Added
2026-10-22

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