Dataset of in-situ and remote sensing measurements of precipitation in the inner Antarctic (Dome-C 75°S 123°E) for the years 2014-2021

• Main Authors: Massimo Del Guasta, Philippe Ricaud
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2023
• Subjects: snow; polar clouds; Antarctica; LIDAR; precipitation; Convolutional Neural Network; machine learning; microwave radiometry; image processing; Antarc*; Antarctic
• Online Access: https://doi.org/10.5281/zenodo.8427614

The database contains original data collected between 2014 and 2021 at the Concordia Station (Dome-C, Antarctica, 75°S, 123°E) using three automatic instruments: 1) A flatbed scanner (ICECAMERA) provides information on the shape and size of precipitation on an hourly basis. 2) An automatic depolarization LIDAR provides the height, structure and phase of the cloud that originated the precipitation on a 5-minute basis. The height range for the LIDAR is between 20 and 7000 meters. 3) A microwave radiometer (HAMSTRAD) provides the local temperature at the altitude where precipitation is formed. The combination of three instruments made it possible to 'label' each precipitation grain with its size, shape parameters, temperature, altitude of formation, and surface meteorological data. Each yearly DATA_YYYY.rar data set is organized into daily directories, where all valid LIDAR false color plots, HAMSTRAD data, and ICECAMERA images are collected, along with processed numerical data for all the ice grains collected. HYSPLIT back trajectories with Dome-C as the final point are also included. The dataset's content is explained in the data legend.doc file MATLAB models.rar includes multiple MATLAB Canonical and SVM models that automatically classify the type of cloud-originating precipitation (at Dome C) based on the relative abundance of different ice grain shapes. Details and instructions for their use can be found in the Legend for MATLAB classifiers.docx document.