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- Very short-range forecasting of wind speed and direction for air traffic operations at Madeira AirportPublication . Alves, Décio Damasceno Mendonça; Alves, Decio; Dias, Fernando Manuel Rosmaninho Morgado Ferrão; Mendonça, Fábio Rúben Silva; Mostafa, Sheikh ShanawazAccurate short-term wind forecasting is essential for aviation safety and efficiency, especially at airports situated in mountainous regions. This doctoral research addresses the challenge of rapidly evolving wind conditions by integrating a newly established network of high-frequency meteorological stations with advanced artificial intelligence models. Through sensor calibration and cost-efficient internet of things infrastructures, the work delivers real-time data at different granular resolutions while reducing measurement error. By employing deep learning approaches combined with feature engineering and data augmentation, the system achieves lower wind speed and direction errors than conventional numerical predictions and supports forecast horizons ranging from one minute to several hours. Interpretable architectures with symbolic methods further enhance trust by revealing how complex terrain influences local wind dynamics and enabling spatial-temporal adjustments of numerical weather predictions. Systematic evaluations confirm improvements in safety-critical metrics for runway operations, including robust classification of wind-induced closures and reduced wind prediction errors. The resulting framework adapts readily to other airports with challenging wind conditions and adheres to international standards for forecasting. In doing so, it strengthens decision-making in air traffic management and fosters greater resilience against disruptive weather events.