Short Introduction
The World Meteorological Organization (WMO) has unveiled a comprehensive Artificial Intelligence (AI) Action Plan at its 19th Congress in Geneva. Designed to accelerate the use of AI across weather forecasting, climate services, hydrology and disaster risk reduction, the Plan sets out policy guidance, governance frameworks, capacity-building measures and research priorities. By harnessing AI responsibly and inclusively, the WMO aims to improve prediction accuracy, strengthen early warnings and support resilient, climate-smart decision-making worldwide.
1. The AI Imperative in Weather and Climate Science
Advances in high-performance computing and machine learning are transforming meteorology and hydrology. Automated pattern recognition, data assimilation from satellites and sensors, and AI-driven ensemble forecasting can deliver more accurate short-term forecasts and longer-term climate projections. Faced with rising costs of extreme weather events and the urgent need to adapt to climate change, the WMO recognizes that AI offers an unprecedented opportunity to:
• Enhance the skill and lead time of weather warnings for storms, floods and heatwaves.
• Integrate heterogeneous data—radar, satellite, Internet of Things (IoT) networks and citizen observations—into unified analytical frameworks.
• Support climate adaptation planning by delivering high-resolution projections and impact assessments.
• Optimize water-resource management, agriculture and disaster-relief logistics through predictive modeling.
2. Pillars of the WMO AI Action Plan
The Action Plan is structured around four interlocking pillars designed to ensure that AI is deployed in a robust, ethical and equitable manner.
2.1 Policy and Normative Instruments
• Update the WMO Data Policy to address AI-specific challenges such as data provenance, interoperability and model reproducibility.
• Develop Technical Regulations that guide the application of AI in official forecasts and warnings.
• Promote open data standards and encourage Member States to adopt shared repositories for machine-readable meteorological and hydrological data.
2.2 Governance and Ethics
• Establish an AI Governance Framework that defines roles, responsibilities and accountability for AI systems across national meteorological and hydrological services.
• Adopt ethical guidelines to ensure transparency, fairness and explainability of AI models, minimizing unintended biases and safeguarding public trust.
• Launch an Expert Panel on AI to monitor emerging risks—such as adversarial attacks on forecasting systems—and advise on corrective measures.
2.3 Capacity Development and Knowledge Sharing
• Roll out a global training programme on AI, data science and digital technologies for meteorologists, hydrologists and policy-makers.
• Create e-learning courses, technical workshops and mentorship schemes in collaboration with universities and research institutes.
• Facilitate South–South cooperation and twinning arrangements to help Least Developed Countries build local AI expertise.
2.4 Research, Innovation and Operations
• Fund targeted research on AI techniques—deep learning, reinforcement learning and ensemble methods—for applications like storm-track prediction and climate downscaling.
• Support pilot projects that integrate AI into operational workflows at Regional Specialized Meteorological Centers and national forecasting services.
• Encourage public–private partnerships with technology firms and startups to co-develop open-source AI tools tailored to weather and climate challenges.
3. Global Collaboration and Partnerships
Effective AI deployment requires collaboration among governments, UN agencies, academia and the private sector. The WMO will coordinate cross-agency efforts with bodies such as the UN Environment Programme and the International Telecommunication Union, ensure alignment with the UN Framework Convention on Climate Change, and engage technology companies through the AI for Good initiative. The Action Plan also calls for data-sharing agreements that respect national sovereignty while enabling global model training on comprehensive datasets.
4. Closing the Digital Divide
To prevent widening inequality in access to advanced tools, the WMO Action Plan prioritizes support for developing nations. Key measures include:
• Subsidized access to high-performance computing resources via regional meteorological centers.
• Provision of open-source AI software and pre-built model frameworks that can run on modest hardware.
• Dedicated scholarships and fellowships for climate scientists from under-resourced countries.
• Regional hackathons and innovation challenges to stimulate locally relevant AI solutions.
5. Implementation Roadmap and Next Steps
The Action Plan sets a four-year timeline:
Year 1 – Establish governance bodies, finalize ethical guidelines, launch pilot projects in flagship countries.
Year 2 – Roll out global training programmes, deploy AI-enhanced forecasting tools at selected regional centers, refine data-sharing protocols.
Year 3 – Scale up operational integration across all World Meteorological and Hydrological Services, conduct independent audits of AI systems.
Year 4 – Evaluate impacts on forecast accuracy and early warning performance, publish best-practice case studies, update the Plan based on lessons learned.
A dedicated monitoring and evaluation framework will track progress against key performance indicators: improvements in forecast skill scores, reduction in warning lead times, number of trained personnel, and uptake of AI tools in Member States.
3 Key Takeaways
• The WMO AI Action Plan provides a structured, ethical and inclusive roadmap to embed AI in weather, climate and water services worldwide.
• Four pillars—policy, governance, capacity building and innovation—ensure that AI technologies are reliable, transparent and accessible, especially for developing countries.
• Strong global partnerships and a phased implementation schedule will drive rapid improvements in forecast accuracy, early warning lead times and climate-resilient decision-making.
3-Question FAQ
1. What is the WMO AI Action Plan?
The Plan is a strategic framework launched at the WMO’s 19th Congress to guide the responsible integration of AI across meteorology, hydrology and climate services. It outlines policy updates, governance structures, training initiatives and research priorities to enhance prediction capability and disaster preparedness.
2. Who stands to benefit from this initiative?
National meteorological and hydrological services will gain access to advanced AI tools and training, enabling more accurate forecasts and earlier warnings. Governments, emergency managers, farmers and vulnerable communities will benefit from better risk information, while the scientific community and private sector will engage in collaborative innovation.
3. How will ethical and data-privacy concerns be addressed?
An AI Governance Framework and updated Data Policy will enforce transparency, explainability and accountability of AI models. Ethical guidelines will guard against biases and ensure equitable treatment, while data-sharing agreements will balance national sovereignty with the need for comprehensive, interoperable datasets.
