A Suite of Retrieval Algorithms for Cirrus Cloud Microphysical Properties Applied To Lidar, Radar, and Radiometer Data Prepared for the A-Train

CloudSat and CALIPSO will be launched in Summer 2005. The constellation of satellites referred to as the A-Train, including Aqua, CloudSat, and CALIPSO, will fly in a formation of matched orbits and the footprints of the three spacecraft will overlap each other within 1 minute. The A-Train provides many opportunities to obtain a global dataset that will allow us to improve our current understanding of clouds. Much of our current global perspective derives from spectral radiances measured by sensors on satellites, and exploiting the synergy of the A-Train observations is a significant opportunity. Retrieval algorithms are needed to convert the data streams from radiance, lidar backscatter, and radar reflectivity into the cirrus properties of interest. Due to the wide range of cirrus properties that can be expected in the global upper troposphere, a suite of algorithms is being prepared for the upcoming A-Train measurements with internal consistency in its formulation.

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Aqua satellite observes spectral radiances from multiple narrowband wavelength channels, while the lidar on Calipso and the radar on Cloudsat will provide vertical profiles of attenuated optical backscatter and radar reflectivity. While MODIS provides an integral constraint on the cirrus layer optical depth, the active remote sensors provide unique information on the second and sixth moments of the particle size distributions within the cirrus layers. The algorithms are capable of treating cirrus layers that range from layers that are very tenuous and below the detection threshold of the radar to layers that can cause significant lidar attenuation. We will show several example case studies of this algorithm suite applied to data collected during Crystal FACE and compared to ground-based algorithm results at the ARM SGP site.