Open AccessEvaluating CloudSat ice water content retrievals using a cloud‐resolving model: Sensitivities to frozen particle properties
Author(s) -
Woods Christopher P.,
Waliser Duane E.,
Li JuiLin,
Austin Richard T.,
Stephens Graeme L.,
Vane Deborah G.
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 - 10.1029/2008jd009941
Subject(s) - ice cloud , environmental science , snow , remote sensing , graupel , water content , meteorology , radar , satellite , liquid water content , atmospheric sciences , cloud computing , geology , computer science , geography , physics , telecommunications , geotechnical engineering , astronomy , operating system
The A‐Train satellite constellation has dramatically increased the temporal and spatial coverage of atmospheric ice water content estimates. The new data are derived by retrieval algorithms designed to estimate atmospheric cloud ice water content from remotely sensed measurements. Such retrieval algorithms rely on simplifying assumptions regarding the characteristics of ice particles in the atmosphere. In this study, the sensitivities of CloudSat ice water content retrievals to frozen particle characteristics are tested by generating CloudSat‐like retrievals from profiles of known ice water content. CloudSat actively measures vertical profiles of radar reflectivity in clouds with a 94‐GHz cloud‐profiling radar. Ice water content is retrieved in each cloudy profile at temperatures below 0°C. To assess the CloudSat radar‐only ice water content retrieval algorithm (version 5.0 in Release 3 [R03] and version 5.1 in Release 4 [R04] of 2B‐CWC‐RO), we apply a 94‐GHz reflectivity simulator to profiles of ice water content generated by a cloud‐resolving numerical model and comprising various frozen particle species (ice, snow, and graupel). The CloudSat ice water content retrieval algorithm is applied to the profiles of simulated reflectivity, and the results are compared to the modeled profiles of known frozen water mass. The results from each version of the algorithm are shown to be sensitive to the characteristics of the frozen particle size distributions and particle densities. Tests of version 5.0 indicate that height varying information could improve retrievals. Despite the addition of a height varying component implemented in version 5.1, similar positive biases are indicated in the tests of each algorithm.