Open AccessEstimating ice content and extinction in precipitating cloud systems from CloudSat radar measurements
Author(s) -
Matrosov Sergey Y.,
Heymsfield Andrew J.
Publication year - 2008
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2007jd009633
Subject(s) - extinction (optical mineralogy) , liquid water content , radar , environmental science , rayleigh scattering , molar absorptivity , ice crystals , reflectivity , atmospheric sciences , remote sensing , content (measure theory) , meteorology , optics , geology , physics , cloud computing , mathematics , mathematical analysis , telecommunications , computer science , operating system
Relations between W band radar reflectivity and ice cloud water content and visible extinction coefficient are developed using a large microphysical data set. These relations are specifically tuned for CloudSat radar to derive ice content and optical thickness of ice parts of precipitating systems where other types of measurements have limitations. Accounting for nonsphericity is essential for larger particles, which produce higher reflectivities ( Z e > 0 dBZ) and often dominate ice content of precipitating clouds. Typical values of median sizes in such clouds are about 1–2 mm, and they vary modestly. The modest particle size variability and strong non‐Rayleigh scattering reduce data scatter in the derived relations and increase an exponent in best fit power law approximations for ice water content–reflectivity and extinction‐reflectivity relations. The data scatter for high‐reflectivity clouds is smaller than for low‐reflectivity nonprecipitating clouds. It is about 33% for the reflectivity‐ice water content relation, and it is about 50% for the reflectivity‐extinction relation. For higher reflectivities, the temperature dependence of the ice water content‐reflectivity relations is not very distinct, and uncertainties due to temperature variations are not expected to be high compared to possible errors due to particle shape variability. Uncertainties in particle aspect ratio, mass‐size relation assumptions, and underrepresentation of smaller particles in samples can produce additional retrieval errors, so cloud ice content estimates can have uncertainties of about 50%, and extinction estimates can have uncertainties as large as a factor of 2.