WMO and UAE Lead Global Push to Harness AI for Weather and Climate Prediction

Early sessions focused on Earth system forecasting, data requirements, and AI integration into meteorological operations.

Artificial intelligence is rapidly reshaping the global response to climate and environmental risks, with the World Meteorological Organization (WMO) and the National Centre of Meteorology (NCM) of the United Arab Emirates spearheading efforts to accelerate its use in forecasting and early warning systems. This week, the two institutions are co-hosting a landmark workshop in Abu Dhabi that brings together more than 50 international experts from governments, academia, and the private sector to explore the transformative role of AI in weather and climate services.

A Turning Point for Meteorology

The WMO AI Conference: AI for Weather Prediction, Advances, Challenges & Future Outlook, held from 9–11 September 2025 at the NCM’s headquarters, is convening stakeholders from organizations including the European Centre for Medium-Range Weather Forecasts, major National Meteorological and Hydrological Services (NMHSs), universities, and technology companies such as Google, IBM, Microsoft, and Nvidia.

In opening remarks, WMO Deputy Secretary-General Ko Barrett stressed the urgency of adopting AI in forecasting:

“We must harness the power of prediction. We must adopt AI-powered weather and climate intelligence into every early warning and decision-making system—because lives depend on it.”

WMO President and NCM Director Abdulla Al Mandous underscored the scale of change in recent years, noting that AI has moved “from research labs into our living rooms, classrooms, and Parliaments,” and that AI-driven forecasts are emerging at unprecedented speed thanks to collaboration between governments, academia, and the private sector.

Closing the Global Forecasting Gap

The conference is framed around three guiding questions:

1. How can AI enhance prediction and service capabilities for those who need them most?

2. How do we ensure developing countries are empowered to use and shape these technologies?

3. What commitments are we prepared to ensure sustained collaboration?

Early sessions focused on Earth system forecasting, data requirements, and AI integration into meteorological operations. One pilot project highlighted was a collaboration between MET Norway and Malawi’s Department of Climate Change and Meteorological Services, which aims to close critical capacity gaps in Malawi and other Least Developed Countries (LDCs) and Small Island Developing States (SIDS).

Key issues under discussion include:

• Improving the availability and quality of training data for AI models.

• Integrating AI into observational and forecasting systems.

• Ensuring service reliability and consistency.

• Establishing frameworks for open-source collaboration and evaluation of AI models.

From Pilots to Global Action

The WMO is already experimenting with AI applications that directly impact lives and livelihoods. Current pilot projects include:

• AI-based flood forecasting in Nigeria, Viet Nam, Uruguay, and the Czech Republic.

• Supporting Regional Climate Centres in Africa, the Caribbean, and the Pacific with sub-seasonal AI forecasting.

• Developing AI-powered nowcasting tools for localized short-term forecasts across Asia, Africa, and Latin America.

In June, WMO’s Executive Council approved an AI action plan, which includes the creation of a Joint Advisory Group to guide the safe and effective integration of AI in meteorology.

Despite progress, experts acknowledge challenges. Barrett cautioned that AI still struggles with localized, high-impact weather events, such as flash floods and severe storms. These limitations, she said, make international collaboration essential to building trust in AI-based early warning systems.

A Call for Global Collaboration

The conference will conclude with a “WMO Call to the Industry”, urging governments, private companies, and research institutions to work together on AI model development to strengthen weather, climate, water, and environmental services worldwide.

This roadmap will also feed into deliberations at the WMO Extraordinary Congress from 20–24 October 2025, where Member States will define long-term strategies for integrating AI into global forecasting systems.

Towards a Safer, Smarter Future

As climate-related disasters become more frequent and severe, AI offers the potential to revolutionize early warnings, improve decision-making, and protect vulnerable communities. For developing countries, in particular, AI-driven solutions could bridge long-standing capacity gaps in forecasting and resilience-building.

The Abu Dhabi conference represents an important step toward a shared global vision for AI in meteorology, one rooted in innovation, equity, and collaboration.