Upgrading Nigerian Meteorological Agency (NiMet) Maproom

The project aims to upgrade the maproom of Nigerian Meteorological Agency (NiMet) to a modern, Python-based system by improving its functionality, usability, and climate data products while building staff capacity to manage and use it effectively.

NiMet’s climate historical data sets are currently hosted on Ingrid platform, which often results in slow system performance when processing large volumes of data. With the ENACTS Maproom transitioning to a Python-based system, this upgrade will ensure NiMet maintains uninterrupted access to a modern, fully functioning climate services platform while preserving existing investments and institutional knowledge.

For end users, the improved NiMet Maproom will provide access to downscaled climate data information, enabling them to visualize historical trends, monitor current conditions and assess climate-related risks at district and community levels. This will strengthen informed decision-making across sectors like agriculture, where estimating planting dates and crop selection will be effective. The Maproom will also enhance flood and drought early warning systems, improve public health preparedness and provide a stronger evidence base for policymaking.

Objectives:

• To ensure the continuity, usability, and long-term sustainability of NiMet’s national Maproom platform.
• To transition NiMet’s existing Maproom from the IRI Ingrid platform to a fully functional Python-based system without loss of data, functionality, or services.
• To strengthen NiMet’s internal technical capacity to independently manage and expand the Maproom.
• To establish a training-of-trainers (ToT) framework that enables NiMet to deliver sectoral and subnational training for end users across climate-sensitive sectors.
• To position NiMet, in collaboration with AGRHYMET, as a regional knowledge hub and technical reference point for Python-based Maproom implementation, scaling, and innovation across the region.