NiMet Partners with AIM for Scale to Deploy AI-Powered Weather Forecasting for Nigerian Farmers

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The Nigerian Meteorological Agency (NiMet) has announced plans to integrate artificial intelligence (AI) into its weather forecasting systems to enhance the accuracy, accessibility, and timeliness of climate information for Nigerian farmers.

The initiative aims to strengthen agricultural resilience and productivity by providing smallholder farmers with more precise forecasts that support planting, harvesting, and risk-management decisions.

Speaking during a courtesy visit by representatives of AIM for Scale, a global consortium dedicated to expanding access to weather and climate services, NiMet’s Director-General and Chief Executive Officer, Prof. Charles Anosike, reaffirmed the agency’s commitment to innovation in climate service delivery.

“AI has the potential to revolutionize how we generate and deliver weather information. By leveraging technology, we can provide localized, real-time forecasts that help farmers make smarter decisions and reduce losses due to extreme weather events,” Prof. Anosike said.

The AIM for Scale delegation, led by Imara Salas and Mohammad Farrae, discussed opportunities for collaboration with NiMet in co-developing strategies, mobilizing investments, and deploying AI-driven solutions tailored to the needs of Nigeria’s agricultural sector.

Prof. Anosike highlighted current challenges, including limited ground weather-station coverage and the need for expanded radar infrastructure across the country. He emphasized that adopting AI technologies would help bridge these gaps and significantly improve the precision of NiMet’s forecasts.

The partnership is expected to be formalized through a Memorandum of Understanding (MoU) between NiMet and AIM for Scale, focusing on joint research, capacity development, and long-term operational sustainability.

By adopting AI-powered forecasting, NiMet hopes to strengthen its role as a regional leader in climate services and empower farmers with the actionable data they need to adapt to changing weather patterns.

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