Artificial intelligence is creating new opportunities to improve weather forecasting and climate analysis, with countries exploring how advanced technologies can support faster, more informed decisions. The World Meteorological Organization (WMO) is highlighting these developments through an upcoming webinar focused on the practical adoption of AI in weather and climate services.

The webinar, titled “AI for Weather and Climate Prediction: From Innovation to Adoption,” is scheduled for 28 October 2026, from 09:00 to 10:00 UTC. The event will examine how the Philippines and Singapore are incorporating AI into their operations and developing the foundations needed for its long-term use.

How AI Is Changing Weather Forecasting

Traditional weather forecasting relies on observations from satellites, weather stations, radar systems, ocean instruments and sophisticated numerical models. AI can complement these methods by identifying patterns in large datasets, processing information efficiently and helping forecasters assess possible weather developments.

Machine-learning systems may also support the interpretation of satellite imagery, the detection of developing storms and the production of more detailed forecasts. Their effectiveness, however, depends on data quality, scientific validation and appropriate integration with established forecasting systems.

Lessons From the Philippines and Singapore

The Philippines regularly faces tropical cyclones, intense rainfall and other weather-related hazards. Improved forecasting tools could help authorities strengthen early-warning systems and provide communities with more timely information for emergency preparation.

Singapore, meanwhile, operates in a highly urbanised environment where accurate rainfall predictions and climate information are important for infrastructure planning, flood management and public safety.

The two countries offer different operational settings for examining how AI can be introduced into meteorological services. Their experiences may help identify practical challenges, technical requirements and opportunities for wider adoption.

Building Reliable AI-Based Climate Services

Introducing AI into weather operations involves more than developing new algorithms. Meteorological agencies need dependable observation networks, computing resources, skilled professionals and systems for testing forecast performance.

Transparency and human oversight also remain important. AI-generated predictions must be assessed against real-world observations, and meteorologists need to understand when a model may be unreliable. International cooperation and the sharing of scientific expertise can help countries with different levels of technological capacity benefit from these developments.

AI should therefore be viewed as a tool that can strengthen scientific forecasting rather than a complete replacement for meteorological expertise.

Why the Initiative Matters

Better weather information can help governments, farmers, transport operators, businesses and emergency services prepare for changing conditions. More effective warnings may also support disaster-risk reduction, particularly in communities exposed to severe storms, flooding and extreme rainfall.

As climate risks evolve, combining scientific knowledge with emerging technologies could help meteorological services improve their operations and reach more people with useful information.

The WMO webinar will provide an opportunity to explore how AI can move from technological experimentation into practical, dependable weather and climate services.