CloudSat is an experimental satellite designed to measure the vertical structure of clouds from space with the Cloud Profiling Radar (CPR). Its orbit will be in formation with the EOS PM1 satellite (Aqua). The Moderate-Resolution Imaging Spectroradiometer (MODIS) in Aqua will provide significant information on the occurrence and horizontal distribution of clouds within the CloudSat footprint.

We develop an algorithm that will be implemented operationally to identify significant radar echo in the CloudSat data stream. This algorithm will (1) examine the characteristics of each range resolution volume to determine if the radar data for that volume is significantly different from the radar noise characteristics and, thus, deemed to contain hydrometeors, (2) quantify the likelihood that a given range resolution volume with characteristics different from noise actually contains hydrometeors, (3) compare the radar significant echo profile with the information from the MODIS cloud mask. The algorithm is tested with the MMCR data from the ARM sites and the MODIS cloud mask product. We will present a detail description of the algorithm and a demonstration of results using a test data set.