paper
2018
Sub-seasonal to seasonal
Evaluation or intercomparison of existing models
RNN / LSTM / ConvLSTMSeasonal to annual Preprint
2018-04-18
012
Apr 2018
Andrew Huang
Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)
LSTM networks compared with linear regression for ENSO prediction across 11 leads; LSTM gains skill over regression only with daily SST predictors at longer leads.
Analyzing el nino southern oscillation predictions from long-short-merm-memory models
In one sentence. LSTM networks compared with linear regression for ENSO prediction across 11 leads; LSTM gains skill over regression only with daily SST predictors at longer leads.
Labels
- Topic
- Sub-seasonal to seasonal
- Type
- Evaluation or intercomparison of existing models
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- Seasonal to annual
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- OpenAlex:W2906246796
- Added
- 2026-10-22
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