MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall

• Main Authors: Grazioli, Jacopo, Ghiggi, Gionata, Berne, Alexis
• Other Authors: Billault-Roux, Anne-Claire, Gehring, Josué, Roulet, Yves-Alain, Praz, Christophe, Leinonen, Jussi, Ferrone, Alfonso, Durán-Alarcón, Claudio, Cooper, Steven J, Franziska Hellmuth, Trude Storelvmo, Tim Carlsen, Robert Oscar David
• Format: Dataset
• Language: English
• Published: 2023
• Subjects: Snowfall; ice crystals; snow images; snowflakes; multi angle snowflake camera (MASC); image classification; meteorology; Leinonen; Antarc*; Antarctica
• Online Access: https://zenodo.org/record/8083133; https://doi.org/10.5281/zenodo.8083133

Dataset overview This dataset provides data and images of snowflakes in free fall collected with a Multi-Angle Snowflake Camera (MASC) The dataset includes, for each recorded snowflakes: A triplet of gray-scale images corresponding to the three cameras of the MASC A large quantity of geometrical, textural descriptors and the pre-compiled output of published retrieval algorithms as well as basic environmental information at the location and time of each measurement. The pre-computed descriptors and retrievals are available either individually for each camera view or, some of them, available as descriptors of the triplet as a whole. A non exhaustive list of precomputed quantities includes for example: Textural and geometrical descriptors as in Praz et al 2017 Hydrometeor classification, riming degree estimation, melting identification, as in Praz et al 2017 Blowing snow identification, as in Schaer et al 2020 Mass, volume, gyration estimation, as in Leinonen et al 2021 Data format and structure The dataset is divided into four .parquet file (for scalar descriptors) and a Zarr database (for the images). A detailed description of the data content and of the data records is available here. Supporting code A python-based API is available to manipulate, display and organize the data of our dataset. It can be found on GitHub. See also the code documentation on ReadTheDocs. Download notes All files available here for download should be stored in the same folder, if the python-based API is used MASCdb.zarr.zip must be unzipped after download Field campaigns A list of campaigns included in the dataset, with a minimal description is given in the following table Campaign_name Information Shielded / Not shielded DFIR = Double Fence Intercomparison Reference APRES3-2016 & APRES3-2017 Installed in Antarctica in the context of the APRES3 project. See for example Genthon et al, 2018 or Grazioli et al 2017 Not shielded Davos-2015 Installed in the Swiss Alps within the context of SPICE (Solid Precipitation InterComparison ...