paper
2023
Extremes & hazards
Sub-seasonal to seasonal New model or method
RNN / LSTM / ConvLSTMSeasonal to annual Journal
2023-01-03
008
Jan 2023
Tuong Quang Vo, Seon‐Ho Kim, Duc Hai Nguyen et al.
Stochastic Environmental Research and Risk Assessment
Hybrid LSTM driven by climate model outputs to predict natural drought; the abstract is missing, so details are limited.
LSTM-CM: a hybrid approach for natural drought prediction based on deep learning and climate models
In one sentence. Hybrid LSTM driven by climate model outputs to predict natural drought; the abstract is missing, so details are limited.
Labels
- Topic
- Extremes & hazards, Sub-seasonal to seasonal
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- Seasonal to annual
- Data
- CMIP / climate model output
- Status
- Research
- Identifiers
- DOI:10.1007/s00477-022-02378-w OpenAlex:W4313531911
- Added
- 2026-10-22
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