Thursday, 1 July 2010: 11:30 AM
Pacific Northwest Ballroom (DoubleTree by Hilton Portland)
A profiling retrieval algorithm for ice cloud properties such as effective radius (re), ice water content (IWC) and extinction coefficient has been developed to use combined CloudSat and CALIPSO measurements based on an optimal estimation framework. Developed as an operational standard data product for the CloudSat project that will be known as 2C-ICE, the algorithm is designed to 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. Uncertainties due to particle habits and size distribution assumptions are included in the forward model error covariance to analyze the retrieval error. The algorithm is applied to CloudSat/CALIPSO data and validated with in situ measurement during the TC4 mission on July 22 2007. Statistical comparisons of re, IWC, and optical depth with products created from other remote sensors in the A-Train will be explored.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner