Adaptive estimation of the stable boundary-layer height using backscatter LiDAR data and a Kalman filter

The nocturnal stable boundary-layer height (SBLH) is estimated from the backscatter lidar data by using an adaptive-filtering approach based on an Extended Kalman Filter (EKF). Height-resolved temporal variance of the lidar data is used as the observables for the processing along with the modelling of minimum-variance regions. The filter is initialized by SBLH estimate from a radio-sonde. The method is applied to the Vaisala CT25K ceilometer data collected during the HD(CP)² Observational Prototype Experiment (HOPE) campaign at Jülich, Germany. Results are compared with SBLH estimates from a collocated microwave radiometer (MWR) and a good degree of agreement is observed.