paper
2023
Sub-seasonal to seasonal
Climate analysis & attribution New model or method
RNN / LSTM / ConvLSTMOther2 weeks–2 monthsOak Ridge National Laboratory Journal
2023-07-17
026
Jul 2023
Linsey Sara Passarella, Salil Mahajan
Artificial Intelligence for the Earth Systems
Oak Ridge National Laboratory
Multi-input autoencoder index from tropical Pacific SST gives Southern California precipitation predictability up to 4 months, beating Niño-3.4.
Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder
In one sentence. Multi-input autoencoder index from tropical Pacific SST gives Southern California precipitation predictability up to 4 months, beating Niño-3.4.
Labels
- Topic
- Sub-seasonal to seasonal, Climate analysis & attribution
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, Other
- Time scale
- 2 weeks–2 months
- Domain
- Regional
- Data
- CMIP / climate model output, Other
- Status
- Research
- Identifiers
- DOI:10.1175/aies-d-23-0003.1 OpenAlex:W4384524047
- Added
- 2026-10-22
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