Ice and mixed-phase cloud statistics on the Antarctic Plateau

Year: 2021

Authors: Cossich W., Maestri T., Magurno D., Martinazzo M., Di Natale G., Palchetti L., Bianchini G., Del Guasta M.

Autors Affiliation: Alma Mater Studiorum Univ Bologna, Phys & Astron Dept, Bologna, Italy; CNR, Ist Nazl Ott, Rome, Italy.

Abstract: Statistics on the occurrence of clear skies, ice clouds, and mixed-phase clouds over Concordia Station, in the Antarctic Plateau, are provided for multiple timescales and analyzed in relation to simultaneous meteorological parameters measured at the surface. Results are obtained by applying a machine learning cloud identification and classification (CIC) code to 4 years of measurements between 2012-2015 of downwelling high-spectral-resolution radiances, measured by the Radiation Explorer in the Far Infrared – Prototype for Applications and Development (REFIR-PAD) spectroradiometer. The CIC algorithm is optimized for Antarctic sky conditions and results in a total hit rate of almost 0.98, where 1.0 is a perfect score, for the identification of the clear-sky, ice cloud, and mixed-phase cloud classes. Scene truth is provided by lidar measurements that are concurrent with REFIR-PAD. The CIC approach demonstrates the key role of far-infrared spectral measurements for clear-cloud discrimination and for cloud phase classification. Mean annual occurrences are 72.3 %, 24.9 %, and 2.7 % for clear sky, ice clouds, and mixed-phase clouds, respectively, with an inter-annual variability of a few percent. The seasonal occurrence of clear sky shows a minimum in winter (66.8 %) and maxima (75 %-76 %) during intermediate seasons. In winter the mean surface temperature is about 9 degrees C colder in clear conditions than when ice clouds are present. Mixed-phase clouds are observed only in the warm season; in summer they amount to more than one-third of total observed clouds. Their occurrence is correlated with warmer surface temperatures. In the austral summer, the mean surface air temperature is about 5 degrees C warmer when clouds are present than in clear-sky conditions. This difference is larger during the night than in daylight hours, likely due to increased solar warming. Monthly mean results are compared to cloud occurrence and fraction derived from gridded (Level 3) satellite products from both passive and active sensors. The differences observed among the considered products and the CIC results are analyzed in terms of footprint sizes and sensors’ sensitivities to cloud optical and geometrical features. The comparison highlights the ability of the CIC-REFIR-PAD synergy to identify multiple cloud conditions and study their variability at different timescales.

Journal/Review: ATMOSPHERIC CHEMISTRY AND PHYSICS

Volume: 21 (18)      Pages from: 13811  to: 13833

More Information: The present work is in preparation of the FORUM mission. FORUM-related studies are supported by projects of the Italian Space Agency (ASI) and of the European Space Agency (ESA). We thank the Italian PNRA (Programma Nazionale di Ricerche in Antartide) and the Institut Polaire Francais Paul Emile Victor (IPEV). More specifically, data were obtained as a part of the subprojects PRANA (Proprieta Radiative dell’Atmosfera e delle Nubi in Antartide), COMPASS (Concordia Multi-Process Atmospheric Studies), FIRCLOUDS (Far Infrared Radiative Closure Experiment For Antarctic Clouds), and DOCTOR (Dome-C Tropospheric Observer). The authors acknowledge the Antarctic Meteo-Climatological Observatory at Concordia for the meteorological data availability as part of the IPEV/PNRA project Routine Meteorological Observation at Station Concordia. We thank the CALIPSO team and the Atmospheric Science Data Center at NASA Langley Research Center for archiving and hosting CALIPSO data. We thank the CloudSat team and the CloudSat Data Processing Center for archiving and hosting CloudSat data. We thank also the MODIS team and the Level 1 and Atmosphere Archive and Distribution System Distributed Active Archive Center (LAADS DAAC) for making the MODIS data available.
KeyWords: Supercooled Liquid Water; Radiative Properties; Polarization Lidar; Spectral Radiance; Vapor; Identification
DOI: 10.5194/acp-21-13811-2021

Citations: 14
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