LAUSR

Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi particle backscatter coefficient) are derived. By using thresholds obtained from multi-year, multi-site EARLINET measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly non-spherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical feature (shape and size) instead of a classification by source. The methodology is applied to two months of continuous observations (24 hours, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the HOPE campaign in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24-h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. By analyzing the entire HOPE campaign, almost 1 million pixel (5 min times 30 m) could be successfully classified from the two months data set with the newly developed tool. We find that the majority of the aerosol, trapped in the planetary boundary layer (PBL), were small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed into the atmosphere from ground.