Cloudnet target categorization during PS106

• Main Authors: Griesche, Hannes, Seifert, Patric, Engelmann, Ronny, Radenz, Martin, Bühl, Johannes
• Format: Dataset
• Language: English
• Published: PANGAEA 2020
• Subjects: AC3; Arctic Amplification; ARK-XXXI/1.1,PASCAL; DATE/TIME; Event label; File format; File name; File size; LiDAR; Polarstern; PS106_0_Underway-11; PS106_0_Underway-17; PS106/1; Remote sensing (Light detection and ranging; LiDAR); Uniform resource locator/link to file; Arctic
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.919344; https://doi.org/10.1594/PANGAEA.919344

The dataset contains daily nc-files of the Cloudnet target categorization during Polarstern cruise PS106. The data is retrieved using the instrument synergystic approach Cloudnet (Illingworth, 2007 doi:10.1175/BAMS-88-6-883 ). This dataset is an aggregation of data from cloud radar, lidar, a numerical forecast model and optionally a rain gauge and microwave radiometer. It is intended to facilitate the application of synergistic cloud-retrieval algorithms by performing a number of the preprocessing tasks that are common to these algorithms. Each of the observational datasets has been interpolated onto the same grid, although the model data are provided on a reduced height grid. Radar reflectivity has been corrected for attenuation, where possible, and two additional fields have been added: \"category_bits\" contains a categorization of the targets in each pixel and \"quality_bits\" indicates the quality of the data at each pixel. Finally, estimates of the random and systematic errors in reflectivity factor and attenuated backscatter are provided.