NiMet advances AI-powered weather forecasting, deepens partnership with China

The Nigerian Meteorological Agency (NiMet) has stepped up efforts to integrate artificial intelligence (AI) into weather forecasting and climate services while deepening its partnership with China to enhance early warning systems and strengthen meteorological cooperation.

Charles Anosike, director-general and chief executive officer of NiMet, disclosed this during the World Meteorological Organization (WMO) Executive Council side event on “Scaling AI-Powered Weather Services for Farmers” held at the WMO headquarters.

According to a statement signed by the agency on Friday, the event brought together global leaders, meteorological experts and development partners to explore how artificial intelligence can improve weather forecasting, strengthen climate services for agriculture and boost food security through innovation and collaboration.

Speaking during the session, Anosike stressed that the success of AI-powered weather forecasting depends on the availability of quality observational data, noting that addressing observation and data gaps across Africa remains critical to unlocking the full potential of AI in meteorology.

He said investment in observation systems is fundamental to improving weather prediction and delivering accurate climate information to farmers and vulnerable communities.

The NiMet boss highlighted the agency’s structured roadmap for integrating AI into its operations, revealing that the agency inaugurated an AI Research Team in January 2026 to identify, evaluate and deploy artificial intelligence and machine learning technologies across its forecasting systems.

“As part of these efforts, NiMet is evaluating leading AI weather prediction models and developing the MeteoAI platform to enhance weather forecasting, climate prediction, forecast verification, and early warning services. The Agency is also assessing the most cost-effective computing infrastructure to support operational AI deployment,” the statement read 

According to him, NiMet has since developed Artificial Intelligence Terms of Reference (TOR), Standard Operating Procedures (SOP), an AI Operational Framework with phased implementation milestones and documented AI use cases to guide the deployment process.

Anosike also disclosed that the agency is currently evaluating leading AI weather prediction models while developing the MeteoAI platform to improve weather forecasting, climate prediction, forecast verification and early warning services.

He added that NiMet is assessing the most cost-effective computing infrastructure required to support operational AI deployment.

The Director-General reaffirmed the agency’s commitment to leveraging artificial intelligence and modern geospatial technologies to strengthen operational meteorology and advance the Early Warnings for All initiative across Africa.

He said the initiative would ensure that farmers and vulnerable communities receive more timely, accurate and actionable weather and climate information to support decision-making and reduce climate-related risks.

On the sidelines of the 80th Session of the WMO Executive Council, Anosike also held a bilateral meeting with the Chen Zhenlin, Administrator and Director-General of the China Meteorological Administration (CMA), to reaffirm the long-standing partnership between Nigeria and China in meteorology.

During the meeting, both countries agreed to expand collaboration through the adoption and customisation of the MAZU AI Early Warning Platform for Nigeria while leveraging emerging AI technologies to strengthen weather and climate services.

The two sides also agreed to adopt a Memorandum of Understanding covering the MAZU platform, staff exchanges, joint research, data sharing, remote sensing, aviation research, knowledge exchange and scholarship programmes.

According to NiMet, the partnership is expected to strengthen technical cooperation between both countries while enhancing Nigeria’s capacity to deploy cutting-edge technologies for weather forecasting, climate monitoring and disaster risk reduction.