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NiMet Boss, Other Stakeholders Attend AATF Meeting On Flood Preparedness

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NIMET AATF
A cross section of participants at the Anticipatory Action Task Force on Floods meeting held in Abuja.

The director-general of the Nigerian Meteorological Agency (NiMet), Prof. Charles Anosike participated in the Anticipatory Action Task Force on Floods (AATF) meeting on Tuesday, March 18, 2025.

The meeting, hosted by Vice President Kashim Shettima, focused on shifting Nigeria’s flood response from reactive disaster relief to proactive preparedness. 

AATF aligns with global frameworks such as the Sendai Framework for Disaster Risk Reduction, the Sustainable Development Goals (SDGs) and the Paris Agreement on Climate Change, all of which emphasise proactive disaster preparedness to mitigate the impact of natural disasters and protect vulnerable communities. 

During the meeting, members of the AATF briefed the vice-president on their respective agencies’ preparedness and ongoing activities aimed at mitigating the impact of flooding in Nigeria. Shettima expressed concern over the increasing human and economic toll of floods in the country. He stressed the urgency of taking action before disasters strike, emphasising the need to leverage science, technology, and collaboration to safeguard lives and livelihoods.

Anosike commended the vice-president for his proactive leadership in advancing anticipatory action, which he said would ensure adequate preparedness and response to climate-related disasters. He highlighted NiMet’s role in providing impact-based forecasts that enable early warning and timely responses before extreme weather events occur. He explained that integrating NiMet’s forecasts with other early warning systems could significantly enhance risk awareness and response capabilities.

He further outlined key priority areas for improving NiMet’s forecasting capabilities, including enhancing weather models, investing in forecast systems, expanding the network of observation stations, improving in-situ data collection and leveraging machine learning techniques to refine predictions.

Oluchi Okorafor
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