Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel
This Info Note describes AGRHYMET's efforts to integrate Artificial Intelligence into seasonal and sub-seasonal forecasting systems. It discusses how AI can contribute to improve the accuracy and reliability of forecasts, and the outcomes of the Regional Climate Outlook Forum (RCOF). The report also...
| Autores principales: | , , , , , |
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| Formato: | Brief |
| Lenguaje: | Inglés |
| Publicado: |
Accelerating Impacts of CGIAR Climate Research for Africa
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/172966 |
| _version_ | 1855522508306907136 |
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| author | Houngnibo, Mandela C. Ali, Abdou Assoumana, Boubacar Toukal Minoungou, Bernard Segnon, Alcade Christel Zougmore, Robert Bellarmin |
| author_browse | Ali, Abdou Assoumana, Boubacar Toukal Houngnibo, Mandela C. Minoungou, Bernard Segnon, Alcade Christel Zougmore, Robert Bellarmin |
| author_facet | Houngnibo, Mandela C. Ali, Abdou Assoumana, Boubacar Toukal Minoungou, Bernard Segnon, Alcade Christel Zougmore, Robert Bellarmin |
| author_sort | Houngnibo, Mandela C. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This Info Note describes AGRHYMET's efforts to integrate Artificial Intelligence into seasonal and sub-seasonal forecasting systems. It discusses how AI can contribute to improve the accuracy and reliability of forecasts, and the outcomes of the Regional Climate Outlook Forum (RCOF). The report also highlights the different initiatives by AGRHYMET to integrate AI in forecasting systems and articulates AICCRA contributions. By integrating AI into its operations, AGRHYMET aims to address the unique challenges of forecasting in West Africa and the Sahel, regions characterized by complex and highly variable climatic conditions in addition to a poor ground-based data availability. |
| format | Brief |
| id | CGSpace172966 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Accelerating Impacts of CGIAR Climate Research for Africa |
| publisherStr | Accelerating Impacts of CGIAR Climate Research for Africa |
| record_format | dspace |
| spelling | CGSpace1729662025-11-11T16:34:52Z Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel Houngnibo, Mandela C. Ali, Abdou Assoumana, Boubacar Toukal Minoungou, Bernard Segnon, Alcade Christel Zougmore, Robert Bellarmin climate change artificial intelligence climate services-climate information services forecasting climatic data-climate data extreme weather events-climate extremes This Info Note describes AGRHYMET's efforts to integrate Artificial Intelligence into seasonal and sub-seasonal forecasting systems. It discusses how AI can contribute to improve the accuracy and reliability of forecasts, and the outcomes of the Regional Climate Outlook Forum (RCOF). The report also highlights the different initiatives by AGRHYMET to integrate AI in forecasting systems and articulates AICCRA contributions. By integrating AI into its operations, AGRHYMET aims to address the unique challenges of forecasting in West Africa and the Sahel, regions characterized by complex and highly variable climatic conditions in addition to a poor ground-based data availability. 2024-12 2025-02-11T22:13:29Z 2025-02-11T22:13:29Z Brief https://hdl.handle.net/10568/172966 en Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Houngnibo M. Ali A. Assoumana B. Minoungou B. Segnon A. Zougmore R. 2024. Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel. AICCRA InfoNote. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA). |
| spellingShingle | climate change artificial intelligence climate services-climate information services forecasting climatic data-climate data extreme weather events-climate extremes Houngnibo, Mandela C. Ali, Abdou Assoumana, Boubacar Toukal Minoungou, Bernard Segnon, Alcade Christel Zougmore, Robert Bellarmin Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title | Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title_full | Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title_fullStr | Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title_full_unstemmed | Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title_short | Integration of Artificial Intelligence in Seasonal to Sub‑Seasonal Forecasting Systems in West Africa and the Sahel |
| title_sort | integration of artificial intelligence in seasonal to sub seasonal forecasting systems in west africa and the sahel |
| topic | climate change artificial intelligence climate services-climate information services forecasting climatic data-climate data extreme weather events-climate extremes |
| url | https://hdl.handle.net/10568/172966 |
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