Predictive Capability of WRF Cycling 3DVAR: LiDAR Assimilation at FINO1

Abstract In this study, we assess tentatively the predictive capability of Weather Research and Forecasting (WRF) model its Three-Dimensional Variational (3DVAR) system. We study impact LiDAR data assimilation on predictions wind speed direction. The simulation domain covers German energy research platform FINO1 in Southern North Sea, at which were recorded. results demonstrate significance applying Data Assimilation (DA) with a short interval (1-hour) to improve prediction temporal spatial representation low level jet events, compared an experiment without DA. Furthermore, briefly examine impacts cycle length performance DA system, variability over area height 250 m.