A classification of ice crystal habits using combined lidar and scanning polarimeter observations during the seac4rs campaign

Natalie Midzak, John E. Yorks, Jianglong Zhang, Bastiaan Van Diedenhoven, Sarah Woods, Matthew McGill

    Research output: Contribution to journalArticlepeer-review

    4 Scopus citations

    Abstract

    Using collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses a K-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such as CALIPSO and POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

    Original languageEnglish
    Pages (from-to)2185-2192
    Number of pages8
    JournalJournal of Atmospheric and Oceanic Technology
    Volume37
    Issue number12
    DOIs
    StatePublished - Dec 2020

    Keywords

    • Cirrus clouds
    • Lidars/Lidar observations
    • Remote sensing

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