Global AI Conference Charts Future of Weather Prediction and Climate Resilience

Artificial intelligence (AI) is rapidly reshaping how the world predicts weather and manages environmental risks. Recognizing both the opportunities and challenges, the World Meteorological Organization (WMO) and the National Center of Meteorology (NCM) of the United Arab Emirates convened the first global conference dedicated to the role of AI in weather forecasting and climate services.

Held from 9–11 September in Abu Dhabi, the WMO AI Conference: AI for Weather Prediction, Advances, Challenges & Future Outlook brought together more than 50 international experts. Participants included representatives from leading meteorological and climate institutions such as the European Centre for Medium-Range Weather Forecasts, National Meteorological and Hydrological Services (NMHSs), academia, and major technology firms including Google, IBM, Microsoft, NVIDIA, Tomorrow.io, Brightband, and other innovators from the hydro-meteorological and environmental industries.

Harnessing AI for Early Warning Systems

The core message of the conference was the urgent need to integrate AI-driven forecasting into global early warning and decision-making systems. WMO Deputy Secretary-General Ko Barrett emphasized, “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.”

AI’s ability to analyze massive datasets in real time promises more accurate and faster predictions of weather extremes, including floods, heatwaves, and cyclones. These improvements could be life-saving, especially for communities that are currently underserved by traditional early warning systems.

Shared Benefits and Common Principles

A key outcome of the conference was a joint statement underlining the need for shared benefit and equitable access to AI tools. The statement stressed investment in open data, standardized benchmarks, human-centered service design, and training. It also called for AI systems to remain transparent, trusted, interoperable, and inclusive of the needs of diverse populations.

The concluding document outlined several core priorities:

• Investment in capacity building, training, and regional AI pilot projects to bridge the digital divide.

• Respecting the authoritative role of NMHSs in issuing official warnings, to preserve public trust.

• Expanding access to public and private datasets to maximize AI’s predictive capabilities.

• Continued reliance on robust observational infrastructure and physics-based models.

• Establishing guiding principles for responsible AI integration grounded in ethics, collaboration, transparency, and sustainability.

• Expanding dialogue between the public sector, academia, and private technology providers.

WMO President Abdulla Al Mandous noted, “The world has seen a fundamental shift in the past three years. Artificial intelligence has moved out of the research laboratories and into our living rooms, classrooms, and Parliaments. Forecasts powered by AI are emerging at remarkable speed, driven in part by collaboration between the private sector, academia, and our NMHSs.”

Pilot Projects Already Underway

AI in meteorology is no longer a theoretical concept. The WMO and its partners are already deploying pilot projects across continents:

• Flood forecasting: AI-based models are being tested in Nigeria, Viet Nam, Uruguay, and the Czech Republic.

• Climate resilience in Malawi: A partnership between MET Norway and Malawi’s Department of Climate Change and Meteorological Service is addressing critical capacity gaps in Least Developed Countries and Small Island Developing States.

• Regional Climate Centres: AI-driven forecasting is being implemented in Africa, the Caribbean, and the Pacific for sub-seasonal climate prediction.

• Nowcasting tools: In collaboration with private firms, WMO is piloting short-term forecasting tools in Asia and beyond to better predict immediate, high-impact events.

While these projects show promise, experts acknowledged that AI still faces limitations, particularly in predicting localized extreme events. “These challenges must be resolved before large-scale deployment,” said Barrett, emphasizing the need for trust in AI-based early warning systems.

Looking Ahead: A Shared Global Vision

The conference outcomes will feed into broader policy discussions, including the upcoming WMO Extraordinary Congress in October, where AI’s role in meteorology will be formally debated. In June, WMO’s Executive Council already adopted an action plan on AI, including the creation of a Joint Advisory Group to guide future developments.

The Abu Dhabi conference marked an important milestone in aligning global stakeholders toward a common vision: using AI responsibly to enhance resilience, protect lives, and build trust in the forecasts that communities depend on. With technology advancing rapidly, the challenge now is ensuring equitable access, capacity development, and ethical implementation so that no region is left behind in the age of AI-powered prediction.