Climate Risk and Early Warning Systems (CREWS) Artificial Intelligence (AI) for Early Warnings for All (EW4ALL) Malawi Project

Project
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Ongoing
Total Funding:
CHF 245,000
WMO Long-Term Goal(s):
  • Climate Resilience and Adaptation
  • Disaster Risk Reduction
  • Global Framework for Climate Services
  • Capacity Development
  • Governance
Focus Area(s):
  • Observations
  • Data Management
  • Forecasting
  • Early Warnings
  • Service Delivery

Project background

The CREWS-funded Artificial Intelligence (AI) for Early Warnings for All (EW4ALL) Malawi Project, supported through a USD 245,775 single-donor award, aims to strengthen Malawi’s early warning capabilities by piloting the use of AI to enhance weather prediction and improve the timeliness and effectiveness of warnings. The initiative contributes to climate-resilient development by improving the systems and processes that enable anticipatory action and better preparedness for weather- and climate-related hazards. Through this investment, the project supports national efforts to enhance risk information, strengthen decision-making, and improve warning dissemination for communities vulnerable to climate shocks.

As the Executing Agency, the World Meteorological Organization (WMO), through its services Department, oversees project implementation and ensures alignment with WMO technical cooperation standards. The project is implemented in partnership with the Department of Climate Change and Meteorological Services (DCCMS) in Malawi, along with technical engagement from Met Norway. WMO’s role includes financial administration, oversight, and the provision of technical support to strengthen forecasting, service delivery, and data-driven early warning capabilities. Through this support, WMO enables national institutions to actively participate in the climate services value chain, coordinate implementation partners, and enhance national capacity to operate improved early warning systems. By fostering collaboration between global, regional, and national experts, and ensuring strong financial and operational oversight, the project lays the foundation for a scalable and sustainable AI-enabled early warning framework for Malawi.

Objective(s)

•    Pilot the use of Artificial Intelligence (AI) to enhance weather prediction capabilities in Malawi.
•    Strengthen early warning systems for improved preparedness and response.
•    Integrating the AI-WP system into DCCMS’s forecasting workflow
•    Providing targeted training and technical support to DCCMS staff
•    Evaluating improvements in forecast accuracy, lead time, and usability
•    Gathering feedback on operational integration through forecaster interviews, focus groups, and participatory workshops
•    Producing actionable insights and a roadmap for potential scale-up in other regions

Outputs

•    Tested AI-based weather prediction systems ; Bris Model and “forecast-in-a-box”.

Expected outcomes

•    Integrated AI-WP system into DCCMS’s forecasting workflow.
•    Improved forecast accuracy, lead time, and usability.
 

Achievements

•    Provided targeted training and technical support to DCCMS staff.
•    Gathered feedback on operational integration through forecaster interviews, focus groups, and participatory workshops.
•    Produced actionable insights and a roadmap for potential scale-up in other regions.
•   Ensured close collaborations between all partners for continuous improvements of technical solutions and forecast quality, and usability.
 

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