“Valluga” weather radar (Photo: Stefan Steiner).
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Real-time data streams and artificial intelligence are changing aviation weather forecasting.

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The digitalization of air traffic is increasingly reaching in-flight weather management. As the Swiss meteorology company Meteomatics reports, the interplay of high-throughput satellite connectivity and artificial intelligence enables the transition from static pre-flight briefings to dynamic, real-time data streams in the cockpit.

Until now, pilots relied primarily on fixed weather reports before takeoff, while updates in the air were only available sporadically via radio or local weather reports. Thanks to modern satellite networks, including those utilizing low-Earth-orbit constellations like Starlink, high-resolution weather data can now be continuously streamed to airlines' operational systems.

Meteomatics' system is based on an API interface that feeds meteorological parameters directly into flight operations and cockpit systems. For Europe, the company uses a proprietary calculation model with a geographical resolution of one kilometer, supplemented by data from low-flying weather drones. This continuous data set enables algorithms to continuously analyze complex weather situations along the route and generate decision support for the crew. As a result, air traffic control, the airline's operations center, and the pilots in the cockpit all work with the same up-to-date information.

Aviation experts and IT analysts view the permanent networking of cockpit systems with external data streams with considerable reservations. The implementation of high-throughput antennas on commercial aircraft requires significant investments from airlines operating in a volatile market environment. Furthermore, linking safety-critical flight control systems with commercial satellite networks poses significant cybersecurity challenges. Critics also point out that a constant flood of visually processed data in the cockpit could lead to information overload for pilots if artificial intelligence fails to reliably filter relevant warnings or produces inaccurate predictions.

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