Abstract
AbstractThe operational light detection and ranging (lidar) data from the Hong Kong International Airport (HKIA) in China are assimilated in the six-nest, high-resolution Weather Research and Forecasting (WRF) Model. The existing radar data assimilation schemes in the WRF data assimilation (WRFDA) package have been adapted to accommodate the high temporal frequency and spatial resolution of the lidar observations. The weather data are then used to produce Lagrangian coherent structures to detect atmospheric hazards for flights. The coherent structures obtained from the various datasets are contrasted against flight data measured on aircraft. It is found that both WRF and WRFDA produce coherent structures that are more distinguishable than those obtained from two-dimensional retrieval, which may improve the detection of true wind shear hazards.
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