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Artificial intelligence is fast changing the way societies are planning to deal with weather-related hazards. Specialists believe that AI has the potential to improve the accuracy and speed of forecasts. In order to solve both the opportunities and challenges, there was a major conference at the World Meteorological Organization and the National Center of Meteorology in Abu Dhabi. The event was aimed at making sure that AI-driven predictions are advantageous to communities all over the world without violating trust, transparency, and cooperation.
Global Gathering on AI and Weather Forecasting
The World Meteorological Organization (WMO) hosted a three-day AI conference, which was held between 9 and 11 September, where more than 50 global experts were present. The representatives of the European Centre of Medium-range Weather Forecasting, National Meteorological and Hydrological Services, private firms and academic institutions were delegates to the conference. Ecosystem leaders like Google, IBM, Microsoft, NVIDIA, Tomorrow.io, and Brightband came together to share.
Organizers emphasized the urgency of advancing AI-powered climate intelligence. Officials stated that accurate prediction models could strengthen disaster preparedness. WMO Deputy Secretary-General Ko Barrett reported that lives depend on integrating AI into early warning and decision-making systems. According to her, harnessing the power of prediction must remain a top priority for the global community.
Shared Vision for AI in Forecasting
At the end of the conference, the participants made a joint statement with priority points. They emphasized the need to make sure that the gains of AI are evenly distributed in each region. The statement encouraged stakeholders to make investments in common data, open tools and coordinated benchmarks that ensure transparency. Another aspect identified by experts was that service design must be human-centered and designed to suit various users that may — or may not be served by existing systems.
The vision highlighted the need to trust and make AI solutions interoperable and inclusive to scale. Concentrating on open cooperation, the representatives believed that AI could not substitute the existing physics-based forecasting, instead, it could be integrated with them. The statement has placed such core values as equity, transparency, and innovation as the focal points in the responsible integration of AI. This would make sure that progress is equally beneficial to developed economies as well as to the weak areas.
Calls for Capacity Building and Training
One of the motifs throughout the conference was that capacity development was urgently needed. Analysts urged to invest in training and education to assist meteorological agencies to use AI. They suggested the expansion of pilot projects which are more regional in nature. Programs like these would help decrease the digital divide and provide underserved groups with quality access to contemporary forecasting.
Delegates also highlighted the importance of respecting the authoritative role of national meteorological services. These agencies maintain public trust and scientific credibility in issuing official warnings. Strengthening their ability to use AI responsibly was presented as vital for public safety. Speakers agreed that without capacity building, many countries would be left behind in adopting modern forecasting technologies.
Data, Infrastructure, and Responsible Integration
The other theme discussed at the conference was why data is crucial in AI-based forecasting. Experts spoke about the necessity to join the public and private data to bring AI to its full potential. They urged national agencies to become more transparent when it comes to observational and auxiliary data. More cooperation may open the possibilities of more correct and localized forecasts.
It was also a restatement of a belief in the importance of having observation infrastructure and physics-based models. Analysts stated that AI was not to replace the old systems, but complement them. The delegates emphasized common principles that govern responsible integration. The principles that were mentioned to be the basis of long-term trust in the AI-enabled services were transparency, collaboration, sustainability, innovation, and ethics.
Industry, Academia, and Public Partnerships
WMO President Abdulla Al Mandous noted that AI adoption has accelerated rapidly. He observed that forecasts powered by AI have moved from experimental to mainstream within just three years. This acceleration, he said, results from collaboration between the private sector, academia, and national meteorological services. Together, they are shaping tools that could transform global preparedness.
The speakers also put emphasis on the need to continue dialogue at various levels. There was an encouragement of more academic and industry representation in WMO structures. This type of collaboration may permit technical innovation to be matched with operational requirements. The meteorological community wants AI solutions to be both reliable and internationally applicable by developing collaborations with other industries.
Pilot Projects Showcasing AI Potential
Representatives pointed out that there were a number of pilot projects that were in existence. WMO is field testing AI-based flood forecasting models in Nigeria, Viet Nam, Uruguay and Czech Republic. These initiatives will show that AI will save lives and livelihoods through disaster preparedness. In Malawi, another project is being undertaken with MET Norway, to fill the capacity gaps in least developed countries.
WMO is also enabling Regional Climate Centres in Africa, the Caribbean, and the Pacific to use AI for sub-seasonal forecasts. Together with private companies, the organization is piloting AI-based nowcasting tools across three continents. These initiatives illustrate how global cooperation can bridge knowledge gaps. They also show how AI can support both local and regional resilience strategies.
Action Plan and Future Outlook
As much as delegates were celebrating gains, they also realized that there was a problem. Analysts indicated that AI software continues to have difficulties with localized high-impact events. All of these constraints have to be resolved prior to large-scale deployment. Officials emphasized that both reliability and accuracy in early warning systems are needed to build the population’s trust. Ko Barrett reiterated that the world needs to cooperate to solve these issues.
The Executive Council of WMO has already settled an action plan for AI. It involves establishing a Joint Advisory Group to help in responsible adoption. The conference statement will inform the proceedings of the next WMO Extraordinary Congress in October. Leaders are trying to make AI a reliable ally in weather and climate intelligence by influencing policies and technical standards.
Conclusion: Toward Equitable Forecasting
The Abu Dhabi summit highlighted how AI can revolutionize weather forecasting. With the emphasis on mutual good, openness, and fairness, professionals marked the path to international collaboration. AI demonstrated its capacity to build resilience in pilot projects in Africa, Asia, the Pacific, and Europe. Nonetheless, the delegates warned that responsible integration should be done with special care to trust, inclusiveness, and ethics.
The meteorological community has promises of the future with its pledges to capacity building, open data, and cross-sector collaboration to offer a future where AI-driven forecasts are used to secure lives around the world. As AI advances, leaders emphasized the need to make all decisions based on shared responsibility and equity. The conclusion of the conference preconditioned the international discussion of the use of AI in weather and climate forecasting.
