Cloudnet categorization during POLARSTERN cruise PS106

• Main Authors: Griesche, Hannes, Seifert, Patric, Engelmann, Ronny, Radenz, Martin, Bühl, Johannes
• Format: Dataset
• Language: English
• Published: PANGAEA 2019
• Subjects: AC3; Arctic Amplification; ARK-XXXI/1.1,PASCAL; Cloudnet; DATE/TIME; Event label; File format; File name; File size; LiDAR; OCEANET-ATMOSPHERE; PASCAL; Polarstern; PS106; 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.899897; https://doi.org/10.1594/PANGAEA.899897

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 on to 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.