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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...

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Autores principales: Houngnibo, Mandela C., Ali, Abdou, Assoumana, Boubacar Toukal, Minoungou, Bernard, Segnon, Alcade Christel, Zougmore, Robert Bellarmin
Formato: Brief
Lenguaje:Inglés
Publicado: Accelerating Impacts of CGIAR Climate Research for Africa 2024
Materias:
climate change
artificial intelligence
climate services-climate information services
forecasting
climatic data-climate data
extreme weather events-climate extremes
Acceso en línea:https://hdl.handle.net/10568/172966
Sumario: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.

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