paper
2020
Sub-seasonal to seasonal
New model or method
RNN / LSTM / ConvLSTMCNN / U-NetSeasonal to annual Journal
2020-10-29
012
Oct 2020
Mayuna Gupta, Hariprasad Kodamana, S. Sandeep
IEEE Geoscience and Remote Sensing Letters
ConvLSTM predicts the Niño3.4 index up to one year ahead, overcoming the spring predictability barrier and capturing strong El Niño events.
Prediction of ENSO Beyond Spring Predictability Barrier Using Deep Convolutional LSTM Networks
In one sentence. ConvLSTM predicts the Niño3.4 index up to one year ahead, overcoming the spring predictability barrier and capturing strong El Niño events.
Labels
- Topic
- Sub-seasonal to seasonal
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, CNN / U-Net
- Time scale
- Seasonal to annual
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1109/lgrs.2020.3032353 OpenAlex:W3097124628
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.