NEW YORK / Content Syndication Services / — Artificial intelligence is moving deeper into global weather forecasting as national meteorological agencies, international climate bodies and research centers use machine learning to improve forecasts, flood alerts and preparation for climate extremes. The World Meteorological Organization has highlighted AI applications presented through national weather and hydrological services, including systems designed to process larger data volumes, strengthen early warnings and support countries facing limited forecasting resources.
WMO has said AI tools are being used to assist forecasters with nowcasting, riverine flood prediction, sub-seasonal outlooks and impact-based warning services. The organization has emphasized that the technology is not a replacement for public weather services, which remain central to issuing official alerts, interpreting model output and communicating risk. Its recent work has also focused on early warnings for all, a global effort intended to expand protection for people exposed to hazardous weather and climate events.
Operational use of AI forecasting has advanced beyond research settings. The European Centre for Medium-Range Weather Forecasts made its Artificial Intelligence Forecasting System operational in 2025 alongside its physics-based Integrated Forecasting System. ECMWF said the model improved many forecast measures, including tropical cyclone track predictions, while using far less computing power than conventional numerical systems. The center also launched an ensemble AI forecast system designed to produce multiple forecast scenarios for uncertainty assessment.
AI enters operations
NOAA has also deployed AI-driven global weather prediction models, including systems built to run alongside traditional forecasting operations. NOAA said the models can reduce computing-resource requirements and improve forecast skill in some areas when compared with existing global systems. The agency has described AI forecasts as part of a broader approach in which machine learning, supercomputing, observations and human expertise are used together to improve national weather prediction and public warning services.
Flood forecasting is one of the clearest areas where AI is being applied to public safety. Google has reported that its flood forecasting work can provide riverine flood forecasts several days in advance and expand alerts in countries where stream gauge data are limited. The company has said its Flood Hub platform covers hundreds of millions of people across more than 100 countries, using hydrological models, rainfall forecasts and AI-based methods to estimate flood risk.
Flood alerts expand
The technology is also being tested for climate resilience in countries with high exposure to extreme weather. WMO has cited AI-supported projects connected to flood forecasting, warning services and low-resource forecasting systems, including work involving developing countries and international partners. These systems are intended to help forecasters identify risks earlier, improve situational awareness and strengthen preparedness before heavy rainfall, river flooding, tropical cyclones or other hazards affect communities.
Officials and scientific centers have said the value of AI depends on reliable observations, national forecasting capacity, communication systems and preparedness planning. Better forecasts alone do not prevent losses when alerts fail to reach at-risk populations or when infrastructure and emergency systems are weak. Current AI weather systems are therefore being integrated with established forecasting institutions, public warning channels and disaster-risk planning as governments and meteorological services respond to increasingly severe weather and climate extremes.