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Tropical Composition, Cloud and Climate Coupling Experiment validation for...

Deng, M., J. Mace, Z. Wang, and H. Okamoto (2010), Tropical Composition, Cloud and Climate Coupling Experiment validation for cirrus cloud profiling retrieval using CloudSat radar and CALIPSO lidar, J. Geophys. Res., 115, D00J15, doi:10.1029/2009JD013104.

A profiling retrieval algorithm for ice cloud properties, such as effective radius (re), ice water content (IWC), and an extinction coefficient, has been developed to use combined CloudSat radar reflectivity factor (Ze) and CALIPSO attenuated backscattering coefficient measurements based on an optimal estimation framework. Developed as an operational standard data product for the CloudSat project, the algorithm can treat a wide range of ice cloud situations from optically tenuous cirrus in the upper troposphere to geometrically and optically thick anvil clouds. It is designed to consider the attenuation of thick clouds in the radar and lidar forward model equations and multiple scattering in the lidar data. An optimal estimation approach allows for inversion of the forward model equations so that the uncertainty due to the assumptions can be evaluated. A sensitivity study shows that lidar multiple scattering has to be accounted for carefully. As for all ice cloud retrieval algorithms, assumptions regarding particle habits and size distribution shapes are critical to the accuracy of the results. The deviation in simulated Ze among different size distribution assumptions is smaller than among different habit assumptions, which indicates that the uncertainty due to particle habits is larger than the size distribution assumption. Those uncertainties are included in the forward model error covariance matrix to analyze the retrieval error. The algorithm is applied to CloudSat‐CALIPSO data as well as lidar and radar data collected by the ER‐2 during the Tropical Composition, Cloud and Climate Coupling Experiment mission on 22 July 2007. The retrieved re, IWC, and extinction are shown to compare favorably with coincident in situ measurements collected by instruments on the NASA DC‐8. This algorithm is expected to be complementary to the set of standard data products that is already being produced by the CloudSat project.

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