Artificial intelligence for meteorological services in the low-altitude economy: Progress, challenges, and future directions

The rapid development of the low-altitude economy demands better meteorological services to support unmanned aerial vehicles (UAVs), electric vertical take-off and landings aircraft (eVTOLs), and urban air mobility systems (UAM). The current meteorological services are not sufficient to predict highly variable atmospheric conditions at low altitudes, where accurate meteorological data is critical for safe and efficient low-altitude economic activities. Recent advances in artificial intelligence (AI) can enhance low-altitude meteorology by improving atmospheric observation, high-resolution weather prediction, risk assessment, and flight-oriented decision support. However, existing studies have largely focused on individual AI applications, and their contributions to meteorological services for low-altitude operations have not been comprehensively reviewed. This review summarizes recent advances in AI applications to connect low-altitude meteorology, atmospheric observation, weather prediction, and weather risk assessment with low-altitude flight operations. We discuss AI applications in multi-source atmospheric sensing, microscale environmental reconstruction, high-resolution prediction, weather risk quantification, and weather-aware flight operations, and further highlight emerging directions including physics-informed AI, foundation models, digital twins, and autonomous AI agents. Beyond improving meteorological prediction, we emphasize that AI should facilitate the transformation of atmospheric information into flight-relevant knowledge by linking environmental conditions with aircraft responses. Finally, we identify major challenges related to data availability, model generalization, uncertainty quantification, and practical deployment. This review provides a novel perspective on the integration of atmospheric science and AI for developing future meteorological services that support safer and more efficient low-altitude transportation.