Impact of Lidar Data Assimilation on Analysis and Prediction of Low-level Wind Shears at Lanzhou Zhongchuan International Airport, China

Low-level wind shear could occur not only in rainy weather conditions but also in non-rainy weather conditions, which is dangerous to aircraft safety for its rapid changes in wind direction or velocity. Recently, dry wind shear occurred in non-rainy condition has drawn more and more attention. Rain-detecting Doppler radar has no capabilities in detecting dry wind shear occurred in non-rainy condition, while Doppler Lidar observations with higher spatial and temporal resolution provide valuable information for dry wind shear. For this, considering dry wind shear cases reported by pilots at Lanzhou Zhongchuan International Airport as study object, lidar observations (radial velocities) were assimilated along with surface data to improve the prediction skill of dry wind shear events.

All experiments were conducted with Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-VAR) system. Three-nested domains were employed with 1-km horizontal resolution in the innermost domain. The model was derived by the NCEP FNL data. Lidar data was processed and only assimilated in the innermost domain. Experimental results show that the low-level wind shear can not be found in the experimental results without lidar data assimilation, while lidar data assimilation experiment successfully represented wind shear small-scale characteristics and simulated radial wind pattern was close to lidar observation. In addition, assimilation cycles with short time intervals effectively improved simulation accuracy of wind shear events.