Surface Wind

Surface wind research focuses on accurately modeling and predicting wind speed and direction, crucial for various applications from optimizing drone flight control to improving weather forecasting. Current research employs advanced machine learning techniques, including convolutional neural networks and model predictive control, often integrated with data assimilation methods to reconstruct high-resolution wind fields from diverse data sources (e.g., satellite imagery, in-situ measurements). These improvements in wind modeling enhance the safety and efficiency of unmanned aerial vehicles (UAVs) operating in challenging conditions and contribute to more accurate climate and weather predictions, particularly at finer spatial scales.