Enhancing Indian summer monsoon prediction: Deep learning approach for skillful long-lead forecasts of rainfall
The prediction of the Indian summer monsoon rainfall (ISMR) in the June–September (JJAS) season at long-lead times is challenging. The state-of-the-art dynamical models often fail to capture the sign and amplitude of the rainfall anomalies in the extreme rainfall seasons, limiting the overall skill...
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| Main Authors: | Kalpesh R. Patil, Takeshi Doi, J.V. Ratnam, Swadhin K. Behera |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Applied Computing and Geosciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590197425000394 |
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