During the COPS field campaign from June to August 2007 a 2023 nm Doppler lidar (WindTracer) and a scanning 35.5 GHz cloud radar (MIRA36-S) were collocated on top of the Hornisgrinde mountain in the northern Black Forest, Germany. Due to the different wavelengths, the scattering properties of the particles seen by the two instruments differ largely. This is a great advantage in getting wind information under different atmospheric situations from cloud free atmosphere as well as within clouds. Therefore a coordinated scan strategy adapted to the weather situation and to the current wind direction was performed.

Applying VAD algorithm on PPI scans profiles of horizontal wind speed and wind direction were derived. Profiles and power spectra of vertical wind velocity were calculated from vertical stare measurements. Evaluation of this data was focused on three aspects: (1) comparing the velocity calibration and identifying measuring problems, (2) using the instruments synergy by extending wind profiles from the mixed layer into the interior of cumulus clouds and (3) gathering additional information on the size-distribution of scatterers.

Our results show that the horizontal wind speeds are in good agreement (a difference below 2 m/s in over 80 % of all combined measured velocities) after correcting a radar ground clutter problem. The two instruments complement each other very well since the total amount of measurements (wind speed and wind direction in 10 minutes time, 50 m height intervals) within the first 2 km above ground increases from 32 % (only lidar data) to 51 % using data from both instruments. The vertical wind velocity shows significant differences especially during rain events and in clouds, since the scatterers now have an individual size-dependent sedimentation velocity. Together with observed double peaks in the lidar velocity spectra, informations about size-distribution of scatterers may be obtained. During clear air situations the power spectra agree well within their common frequency range. The combined vertical velocity variance profiles are used in the future for studying turbulence intensity in and underneath clouds.