paper
2023
Post-processing & calibration
New model or method
RNN / LSTM / ConvLSTMCNN / U-NetClimate projections / centennial Journal
2023-03-02
012
Mar 2023
T. Kesavavarthini, A. Naga Rajesh, Challa Venkata Srinivas et al.
International Journal of Climatology
Compares CNN1D and LSTM encoder-decoder deep learning for bias correcting CMIP6 monsoon precipitation over India, with LSTM-ED performing best against IMD observations.
Bias correction of CMIP6 simulations of precipitation over Indian monsoon core region using deep learning algorithms
In one sentence. Compares CNN1D and LSTM encoder-decoder deep learning for bias correcting CMIP6 monsoon precipitation over India, with LSTM-ED performing best against IMD observations.
Labels
- Topic
- Post-processing & calibration
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, CNN / U-Net
- Time scale
- Climate projections / centennial
- Domain
- Regional
- Data
- CMIP / climate model output, Other
- Status
- Research
- Identifiers
- DOI:10.1002/joc.8056 OpenAlex:W4322721694
- Added
- 2026-10-22
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