Explainable deep learning for insights in El Niño and river flows
Here, explainable deep learning and climate networks give insight into the dependencies between El Niño and river flow, with implications for machine learning-based earth system model coupling and climate-informed projections of water resources.
| Published in: | Nature Communications |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-01-01
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| Online Access: | https://doi.org/10.1038/s41467-023-35968-5 |
| _version_ | 1852667283777781760 |
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| author | Yumin Liu Kate Duffy Jennifer G. Dy Auroop R. Ganguly |
| author_facet | Yumin Liu Kate Duffy Jennifer G. Dy Auroop R. Ganguly |
| author_sort | Yumin Liu |
| collection | DOAJ |
| container_title | Nature Communications |
| description | Here, explainable deep learning and climate networks give insight into the dependencies between El Niño and river flow, with implications for machine learning-based earth system model coupling and climate-informed projections of water resources. |
| format | Article |
| id | doaj-art-37dedbbcd8db45fab159b3d962e6efbc |
| institution | Directory of Open Access Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| spelling | doaj-art-37dedbbcd8db45fab159b3d962e6efbc2025-08-19T21:34:42ZengNature PortfolioNature Communications2041-17232023-01-011411810.1038/s41467-023-35968-5Explainable deep learning for insights in El Niño and river flowsYumin Liu0Kate Duffy1Jennifer G. Dy2Auroop R. Ganguly3SPIRAL Center, Department of Electrical and Computer Engineering, Northeastern UniversitySustainability and Data Sciences Laboratory, Department of Civil and Environmental Engineering, Northeastern UniversitySPIRAL Center, Department of Electrical and Computer Engineering, Northeastern UniversityThe Institute for Experiential AI (EAI), Northeastern UniversityHere, explainable deep learning and climate networks give insight into the dependencies between El Niño and river flow, with implications for machine learning-based earth system model coupling and climate-informed projections of water resources.https://doi.org/10.1038/s41467-023-35968-5 |
| spellingShingle | Yumin Liu Kate Duffy Jennifer G. Dy Auroop R. Ganguly Explainable deep learning for insights in El Niño and river flows |
| title | Explainable deep learning for insights in El Niño and river flows |
| title_full | Explainable deep learning for insights in El Niño and river flows |
| title_fullStr | Explainable deep learning for insights in El Niño and river flows |
| title_full_unstemmed | Explainable deep learning for insights in El Niño and river flows |
| title_short | Explainable deep learning for insights in El Niño and river flows |
| title_sort | explainable deep learning for insights in el nino and river flows |
| url | https://doi.org/10.1038/s41467-023-35968-5 |
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