Fluid Dynamics - understanding fluid dynamics to improve our lives

本研究旨在研究东福克兰群岛背风波引起的大气旋翼的结构、动力学和湍流强度。利用机器学习技术，从气象局的扫描多普勒激光雷达获得的现场数据将被分析，以识别模式并对旋翼动态进行预测，并最终应用于当前的天气预报模型，以提高机场预报的准确性，并评估航空湍流风险。

This study aims to investigate the structure, dynamics, and turbulent intensity of atmospheric rotors occurring due to Lee Waves in the East Falklands. Using Machine Learning techniques, on-site data obtained from the Met Office's scanning Doppler LIDAR will be analysed to identify patterns and make predictions about the rotor dynamics, and ultimately apply to current weather forecasting models to improve the accuracy of forecasts in the airfields, and evaluate aviation turbulence risk.