AI in focus: Abu Dhabi launches international weather conference

Abu Dhabi today hosted the opening of the international conference “Artificial Intelligence in Weather Prediction and Environmental Services Enhancement” at the headquarters of the National Center of Meteorology (NCM). The event is organised by NCM under the patronage of the World Meteorological Organization (WMO), with the participation of more than 50 international speakers. The sessions will run until September 11.

The conference, featuring 12 main sessions, serves as a comprehensive scientific platform bringing together leading experts and specialists from WMO, alongside major global technology companies such as Microsoft, Google, NVIDIA and IBM. It also includes representatives from the European Centre for Medium-Range Weather Forecasts and a range of academic and operational institutions.

The event provides an opportunity to exchange knowledge and expertise while exploring the latest developments and challenges related to the application of AI in weather forecasting.

The conference focuses on how artificial intelligence (AI) and machine learning (ML) technologies can advance weather prediction systems in sustainable and scalable ways, particularly to support developing countries. It aims to enhance the accuracy and reliability of forecasts.

Day one featured sessions on Earth system prediction and the evolution of current AI and ML approaches. Discussions highlighted how these technologies open new horizons for forecasting through partnerships between academia, operational agencies, global tech firms and startups—accelerating the development and deployment of innovative solutions.

Speakers also examined the integration of AI and ML into operational meteorology, underscoring the essential role of human expertise in validating outputs and ensuring they are applied in the proper context. They stressed the importance of maintaining trust and ensuring fair and inclusive access to services across communities.

One session highlighted AI-enabled Earth system prediction, which relies on diverse, high-quality datasets—from field weather observations and satellite imagery to Internet of Things (IoT) devices and geospatial data. It also addressed evolving data requirements and the infrastructure needed to build and validate predictive models, ensure data quality, maintain interoperability and guarantee accessibility.

Another session emphasised that as AI and ML increasingly become core pillars in Earth system prediction and other critical applications affecting people’s lives and livelihoods, it is crucial to build trust in these models and their development processes.

Speakers raised key questions: How can we ensure that AI and ML tools perform the right tasks for the right reasons? How should their reliability be validated and evaluated? And how do differences in mandates, incentives and innovation cultures between the public and private sectors shape transparency, openness and participation within the global scientific community?